FI ELD OF THE PRESENTLY DISCLOSED SUBJECT MATTER

This invention relates to the field of flow monitoring and detection of leaks. BACKGROU ND Water leaks such as those occurring in households and businesses may cause serious damage to the premises. Furthermore, as water costs around the world continue to rise, the mere waste of water may inflict substantial financial loss. Accordingly, it would be advantageous to monitor water consumption, detect leaks as they occur, and enable shutdown of water flow in case a leak is detected. GEN ERAL DESCRI PTION

According to an aspect of the presently disclosed subject matter there is provided a computerized method of monitoring liquid or gas flow, the method comprising, with the help of a processor, performing at least the following operations: obtaining flow information characterizing the flow during a learning phase; the flow information including at least data with respect to consumption flow rate and consumption volume of flow; determining, based on the flow information, at least one threshold value being indicative of flow characterized by a given consumption flow rate and a given consumption volume which is suspected as a leak; during a normal working phase, obtaining additional flow information characterizing water flow; the additional flow information including at least data with respect to consumption flow rate and consumption volume of the flow during the normal working phase; and performing a preventative action, if the flow during the normal working phase is characterized by a consumption flow rate which is the same as the given consumption flow rate and characterized by a consumption volume which is greater than the given consumption volume indicated by the at least one threshold.

Additional to the above features, the method according to this aspect of the presently disclosed subject matter can optionally comprise one or more of features (i) to (xviii) below, in any desired combination or permutation. i) . According to certain embodiments of the presently disclosed subject matter the method further comprising: detecting, based on the flow information, at least one flow event in the flow; determining a respective consumption flow rate and respective consumption volume of the at least one flow event; assigning the at least one flow event to a respective group of flow events based on the respective consumption flow rate of the at least one flow event; the respective group comprising one or more flow events is characterized by consumption flow rate within a certain range and is assigned with a maximal consumption volume; assigning the respective consumption volume of the at least one flow event as a new maximal consumption volume of the respective group instead of the maximal consumption volume, if the respective consumption volume of the at least one flow event is greater than the maximal consumption volume; and determining the at least one threshold value of the respective group based on the maximal consumption volume assigned to the group. ii) . wherein the method further comprises performing, during the normal working phase, at least the following operations: detecting, based on the additional flow information, a flow event in the flow; determining a respective consumption flow rate and respective consumption volume of the flow event; assigning the flow event to a respective group of flow events based on the respective consumption flow rate of the at least one flow event; the respective group comprising one or more flow events is characterized by flow rate within a certain range and is assigned with a maximal consumption volume; obtaining at least one threshold value determined for the respective group; and performing the preventative action if the respective consumption volume of the flow event is equal to or greater than the at least one threshold by a certain predefined value. iii) . Wherein the method further comprises repeatedly reducing the maximal consumption volume of a given group by a certain reduction value. iv) . Wherein the reduction value is determined based on one or more parameters characterizing the given group; the parameters including one or more of: age of the given group; and activity of the given group. v) . Wherein the detection of flow events is based on the ratio between the consumption flow rates of 2 or more consecutive pulses detected in the flow. vi) . Wherein the method further comprises representing the respective group as a bin in a histogram; each bin in the histogram representing a respective group of flow events characterized by a consumption flow rate within a certain range and wherein the y axis of the histogram represents the maximal consumption volume of each bin in the histogram. vii) . Wherein the method further comprises sampling water flow to obtain the flow information. viii) . Wherein the sampling is performed at a resolution in which each detected pulse represents flow of a volume of less than 100 cc. ix). Wherein the sampling is performed at a resolution in which each detected pulse represents flow of a volume as low as 50cc. x). Wherein the preventative actions include one or more of: sending an indication to a client device with respect to a suspected leak; and automatically shutting down flow. xi) . Wherein the method further comprises: obtaining information indicative of a flow profile of a first flow event caused by a given consuming element; detecting a second flow event and determining the respective flow profile of the flow event; identifying the source of the first flow event as the given consuming element if the similarity between the flow profile of the first flow event and the respective flow profile of the second flow event complies with one or more predefined conditions. xii) . Wherein the flow profile characterizes flow consumption rate against time. xiii). Wherein the flow profile characterizes one or more of: sound generated by flow to the given consuming element; and a piezoelectric effect caused by flow to the given consuming element. xiv) . Wherein the liquid is water. xv) . Wherein the flow is water flowing into a given premises. xvi). Wherein the preventative action is to shut down the flow, the method further comprising: sending an indication to a client device with respect to a suspected leak; receiving from the client device, instructions as whether to shutdown the flow or leave it open; and performing an action according to the instructions received from the client. xvii). Wherein the method further comprises sending the indication as an

SMS message. xviii). Wherein the flow information further comprises supplementary flow information; the method further comprising: considering supplementary flow information for determining whether or not to perform a preventative action. According to another aspect of the presently disclosed subject matter there is provided a liquid or gas flow monitoring device, comprising: a processing unit comprising at least one processor and being operatively connected to a flow sensor unit; the flow sensor unit comprising a flow sensor; the flow sensor being configured to sample flow in a respective conductor and provide to the processing unit information indicative of flow in the conductor; the processing unit is configured to: during a learning phase, obtain flow information characterizing the water flow; the flow information including at least data with respect to consumption flow rate and consumption volume of flow; determine, based on the flow information, at least one threshold value being indicative of flow characterized by a given consumption flow rate and a given consumption volume which is suspected as a leak; during a normal working phase, obtain additional flow information characterizing water flow; the flow information including at least data with respect to consumption flow rate and consumption volume of the flow during the normal working phase; and perform a preventative action, if the flow during the normal working phase is characterized by a consumption flow rate which is the same as the given consumption flow rate and characterized by a consumption volume which is greater than the given consumption volume indicated by the at least one threshold.

According to another aspect of the presently disclosed subject matter there is provided a computer program product implemented on a non-transitory computer useable medium having computer readable program code embodied therein for monitoring liquid or gas flow; the computer program product comprises computer readable program code for causing the computer to obtain flow information characterizing the flow during a learning phase; the flow information including at least data with respect to consumption flow rate and consumption volume of flow; computer readable program code for causing the computer to determine, based on the flow information, at least one threshold value being indicative of flow characterized by a given consumption flow rate and a given consumption volume which is suspected as a leak; computer readable program code for causing the computer to obtain, during a normal working phase, additional flow information characterizing water flow; the flow information including at least data with respect to consumption flow rate and consumption volume of the flow during the normal working phase; and computer readable program code for causing the computer to perform a preventative action, if the flow during the normal working phase is characterized by a consumption flow rate which is the same as the given consumption flow rate and characterized by a consumption volume which is greater than the given consumption volume indicated by the at least one threshold. According to another aspect of the presently disclosed subject matter there is provided a non-transitory program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform a method of monitoring liquid or gas flow, the method comprising: obtaining flow information characterizing the flow during a learning phase; the flow information including at least data with respect to consumption flow rate and consumption volume of flow; determining, based on the flow information, at least one threshold value being indicative of flow characterized by a given consumption flow rate and a given consumption volume which is suspected as a leak; during a normal working phase, obtaining additional flow information characterizing water flow; the flow information including at least data with respect to consumption flow rate and consumption volume of the flow during the normal working phase; and performing a preventative action, if the flow during the normal working phase is characterized by a consumption flow rate which is the same as the given consumption flow rate and characterized by a consumption volume which is greater than the given consumption volume indicated by the at least one threshold.

The device, the computer program product, and the computer storage device, disclosed in accordance with the presently disclosed subject matter can optionally comprise one or more of features (i) to (xvii) listed above, mutatis mutandis, in any desired combination or permutation. Operations described with reference to method steps can be performed by respective functional elements in the device.

According to another aspect of the presently disclosed subject matter there is provided a fluid or gas monitoring and control system, comprising: a housing for accommodating a main unit, an actuator unit and a one way valve; the housing being connectible to a conductor; the main unit comprising: a processing unit comprising at least one processor, a flow sensor unit, and a communication unit; the flow sensor unit comprising a flow sensor configured to sample flow in the conductor and provide to the processing unit information indicative of flow in the conductor; the processing unit is configured to process the information and obtain flow information characterizing the flow; the processing unit is further configured to identify, based on at least the flow information, a suspected leak and transmit to a client device, with the help of the communication unit, an indication with respect to the suspected leak, and generate instructions to the actuator unit to shut down a valve and stop flow through the conductor, if one or more conditions are met; the one way valve is configured to allow flow in the conductor in one direction and enable the flow only if consumption volume is greater than a certain value, thereby enabling to detect flow characterized by low consumption flow rate which is otherwise undetectable and improve the accuracy of the flow sensor unit.

According to certain embodiments of the presently disclosed subject matter the system further comprises a data-repository including a non-transitory computer memory configured to enable storage of the flow information.

According to certain embodiments of the presently disclosed subject matter the system further comprises a communication port enabling to directly connect a computer memory device to the system and retrieve flow information stored in the data-repository. According to certain embodiments of the presently disclosed subject matter the communication unit is configured to receive instructions from the client device, the instruction indicating whether or not to close the flow.

According to certain embodiments of the presently disclosed subject matter the main unit further comprises a power source for providing power to the system.

According to certain embodiments of the presently disclosed subject matter the flow is water flow flowing in a water pipe.

According to another aspect of the presently disclosed subject matter there is provided a method of identifying a source of a given flow event, the method comprising: obtaining information indicative of a flow profile of a first flow event caused by a given consuming element; detecting a second flow event and determining a respective flow profile of the flow event; identifying the source of the first flow event as the given consuming element if the similarity between the flow profile of the first flow event and the respective flow profile of the second flow event complies with one or more predefined conditions.

According to certain embodiment of the presently disclosed subject matter the obtaining comprises: modifying flow to a given source thereby generating an identifiable flow pattern.

According to another aspect of the presently disclosed subject matter there is provided a flow modification apparatus: the apparatus comprising a housing characterized by a hollow shape with at least one opening being connectable to a fluid conductor; the opening is configured to allow liquid to flow from the conductor, through the apparatus and back into the conductor or outside the conductor; the internal structure of the apparatus is configured to modify the flow and generate a distinctive flow profile.

According to certain embodiments of the presently disclosed subject matter the internal structure of the apparatus comprises a flow constriction element; the flow constriction element is configured to temporarily decrease consumption flow rate.

According to certain embodiments of the presently disclosed subject matter the wherein the housing comprises a cone located within a sleeve, the sleeve has an inner cavity; the cone is suspended by a biasing member; responsive to turning on the flow at a consuming element connected to the conductor, fluid flows around the cone and through the inner cavity and fills a chamber located within the sleeve causing the cone to be pushed against the biasing member thereby allowing the fluid to flow more freely towards the consuming element. According to certain embodiments of the presently disclosed subject matter the cone is configured with one or more flow constricting rings located around the circumference of the cone; the flow constricting rings are configured to cause a decrease and a following increase in flow consumption rate as the cone is being pushed against the biasing member, thereby modifying the flow and generating the distinctive flow profile.

According to another aspect of the presently disclosed subject matter there is provided a computer program product implemented on a non-transitory computer useable medium having computer readable program code embodied therein for identifying a source of a given flow event; the computer program product comprises computer readable program code for causing the computer to obtain information indicative of a flow profile of a first flow event caused by a given consuming element; computer readable program code for causing the computer to detect a second flow event and determine a respective flow profile of the flow event; computer readable program code for causing the computer to determine a second flow pattern, the second flow pattern comprising at least one feature identifying a flow pattern of the identified flow event; computer readable program code for causing the computer to identify the source of the first flow event as the given consuming element if the similarity between the flow profile of the first flow event and the respective flow profile of the second flow event complies with one or more predefined conditions. According to another aspect of the presently disclosed subject matter there is provided a non-transitory program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform a method of identifying a source of a given flow event, the method comprising: obtaining information indicative of a flow profile of a first flow event caused by a given consuming element; detecting a second flow event and determining a respective flow profile of the flow event; identifying the source of the first flow event as the given consuming element if the similarity between the flow profile of the first flow event and the respective flow profile of the second flow event complies with one or more predefined conditions. BRIEF DESCRIPTION OF THE DRAWINGS

In order to understand the presently disclosed subject matter and to see how it may be carried out in practice, the subject matter will now be described, by way of non-limiting examples only, with reference to the accompanying drawings, in which:

Fig. la is high level view of a flow monitoring and control system, in accordance with the presently disclosed subject matter;

Fig. lb is another high level view of a flow monitoring and control system, in accordance with the presently disclosed subject matter;

Fig. 2 is a functional block diagram schematically illustrating a flow monitoring and control system, in accordance with the presently disclosed subject matter;

Fig. 3 is a flowchart illustration of a general view of an example of a sequence of operations carried out, in accordance with the presently disclosed subject matter; Fig. 4 is a functional block diagram illustrating an example of the architecture of processing unit 250 and sensor unit 240, in accordance with the presently disclosed subject matter;

Fig 5 is a functional block diagram illustrating an example of threshold determination module 429, in accordance with the presently disclosed subject matter;

Fig. 6 is a flowchart illustration of an example of a sequence of operations carried out during the learning phase, in accordance with the presently disclosed subject matter; Fig. 7 is a flowchart illustration of an example of a sequence of operations carried out during the working phase, in accordance with the presently disclosed subject matter;

Fig. 8 shows a graph plotting consumption flow rate against time and demonstrating flow events, in accordance with the presently disclosed subject matter;

Fig. 9 is an example of a flow events histogram after 8 days of flow monitoring, in accordance with the presently disclosed subject matter;

Fig. 10 is a flowchart illustrating an example of a sequence of operations carried out in response to detection of a small leak, in accordance with the presently disclosed subject matter;

Fig. 11 is a flowchart illustrating an example of a sequence of operations carried out in response to detection of a major leak, in accordance with the presently disclosed subject matter;

Figs. 12a to 12d show one example of a flow modification apparatus, in accordance with the presently disclosed subject matter; Fig. 13 is a curve showing consumption flow rate of an irrigation system without a flow modification apparatus, in accordance with the presently disclosed subject matter;

Fig. 14 is a curve showing consumption flow rate of an irrigation system with a flow modification apparatus, in accordance with the presently disclosed subject matter; and

Fig. 15 is a flowchart illustrating operations carried out in accordance with the presently disclosed subject matter.

It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements.

DETAILED DESCRIPTION Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as "obtaining", "determining", "performing", "detecting", "assigning" or the like, include actions and/or processes of a computer processor that manipulate and/or transform data into other data, said data represented as physical quantities, e.g. such as electronic quantities, and/or said data representing the physical objects.

As used herein, the phrase "for example," "such as", "for instance" and variants thereof describe non-limiting embodiments of the presently disclosed subject matter. Reference in the specification to "one case", "some cases", "other cases" or variants thereof means that a particular feature, structure or characteristic described in connection with the embodiment(s) is included in at least one embodiment of the presently disclosed subject matter. Thus the appearance of the phrase "one case", "some cases", "other cases" or variants thereof does not necessarily refer to the same embodiment(s).

It is appreciated that certain features of the presently disclosed subject matter, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the presently disclosed subject matter, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination.

In embodiments of the presently disclosed subject matter, fewer, more and/or different stages than those shown in Figs. 3, 6, 7, 10, 11 and 15 may be executed. In embodiments of the presently disclosed subject matter one or more stages illustrated in Figs. 3, 6, 7, 10, 11 and 15 may be executed in a different order and/or one or more groups of stages may be executed simultaneously. Figs 1, 2, 4 and 5 illustrate general schematics of the system architecture in accordance with an embodiment of the presently disclosed subject matter. Different modules in Figs 1, 2, 4 and 5 can be made up of any combination of software, hardware and/or firmware that performs the functions as defined and explained herein. In other embodiments of the presently disclosed subject matter, the system may comprise fewer, more, and/or different modules than those shown in Figs 1, 2, 4 and 5. Main unit 110 illustrated in Figs. 1 and 2 as well as processing unit 250 illustrated in Fig. 4 comprises or is otherwise operatively connected to one or more computer processors. The term "computer processor" should be expansively construed to cover any kind of electronic device with data processing capabilities, including, by way of non-limiting example, a personal computer, a portable computer, a computing system, a communication device, a processor (e.g. digital signal processor (DSP), a microcontroller, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), etc.), any other electronic computing device, and or any combination thereof. The presently disclosed subject matter includes, inter alia, a method and a device for monitoring water flow. The monitored data is analyzed in order to diagnose the water flow and identify abnormal events which may indicate that a leak is occurring. If a suspected leak is identified, the water flow can be shut down. Water flow shutdown can be done automatically by automatically controlling an electric water valve on the main water line. Alternatively a warning can be sent to a user indicating that a suspected leak is occurring and advising to shut down the water immediately.

Bearing this in mind, attention is drawn to Fig. 1, which is a high level view of a flow monitoring and control system 100 in accordance with the presently disclosed subject matter. Fig. 1 shows main unit 110 which comprises user interface 112, a processing unit and a sensor unit (not shown here). Main unit 110 can further include or be operatively connected to a flow meter configured to generate information with respect to flow through the fluid conductor 118 (e.g. water pipe). Main unit 110 is connected (e.g. via cable 120) to actuator unit 116 which includes an actuator and a valve located in pipe 118 operable to shut down flow in the pipe in response to a command received from the processing unit. System 100 can further include a communication unit and an antenna for enabling communication between main unit 110 and other remote computerized devices. Fig. lb is another high level view of a flow monitoring and control system 100 in accordance with the presently disclosed subject matter. Fig. lb which is a top view image of the system shows main unit 110 (with a cover on top of the user interface) and actuator unit 116. Fig. lb further illustrates a one way valve (OWV, otherwise known as unmeasured flow reducer) 206 which is described in detail below with reference to Fig. 2. The components shown in Fig. 1 can all be integrated in a housing (which can be made for example from a single plastic mold) specifically designed for accommodating main unit 110, actuator unit 116 and OWV 206. System 100 can be connectible (commonly by a screw thread assembly) to a conductor (e.g. pipe) at its two ends marked by the white arrows. The housing can be designed to accommodate the system as a single unit and include the connecting ends for connecting the housing to a conductor. Thus, by connecting system 100 to a pipe the various functionalities of the system 100 are enabled for monitoring and controlling flow (e.g. water flow) through the pipe and into a respective premises.

Fig. 2 is a functional block diagram schematically illustrating flow monitoring and control system, in accordance with the presently disclosed subject matter. Fig. 2 shows water source 202 supplying water through pipe 118 to water consumer 204, which can be for example a private household or a business. The direction of water flow is indicated by the two black arrows.

Main unit 110 of water monitoring and control system is installed at the entrance to consumer 204 property. Unit 110 is operable to monitor the water flowing through pipe 118 towards the consumer's property. As mentioned above, water monitoring enables to determine flow information (flow information including at least consumption volume and consumption flow rate) and can be used by the water distributing company for billing the customer. In addition, as explained in more detail below according to the presently disclosed subject matter, water monitoring is used for detecting deviation of water flow from normal consumption and for detection of suspected leaks. Main unit 110 is operatively connected to an actuator device 116 comprising a controllable actuator 214 which can close and open water valve 220 in response to instructions generated by main unit 110. For example, in case a leak is detected, main unit 110 can send instructions to actuator 214 to close valve 220 in order to avoid further wastage of water and potential damage which may be caused by the water leak.

In general, main unit 110 can be fixed to the external surface of pipe 118 outside to the position of turbine 216 placed within pipe 118 (the turbine can be located in a designated compartment being part of a flow meter). Main unit 110 comprises sensor unit 240 and processing unit 250. Sensor unit 240 is configured to sense the change in magnetic field caused by the rotation of turbine 216 and attached bipolar magnet 218. The turbine's rotational speed is proportional to the water consumption flow rate in the pipe. Based on the detected change in the magnetic field, corresponding flow information with respect to water flow in pipe 118 can be calculated.

One example of a sensor which is commonly used for this purpose is a Hall Effect sensor. In short, a Hall Effect sensor is designed to measure changes in voltage that appear across a conductive material, for example silicon (Si), when an electric current flowing through the conductor is influenced by a magnetic field. In a Hall Effect sensor attached to pipe 118, a transverse voltage is generated perpendicular to the applied current, as a result of a magnetic field generated by revolving magnet 218 attached to turbine 216, which is pushed by the flowing water.

Thus, sensor unit 240 can be configured to periodically sample and detect (e.g. with the help of a Hall Effect sensor) changes in the induced voltage. Based on this information, respective flow information can be determined by processing unit 250.

It is noted that a magnetic field sensor in general and specifically Hall Effect sensors are merely a non-limiting example and the presently disclosed subject matter can be implemented with other types of sensors configured to detect physical quantities other than magnetic field and/or voltage. This may include for example, an optical sensor configured to detect intensities of light (being another type of physical quantity), or an ultrasonic sensor configured to detect sound (being yet another type of physical quantity) with a frequency greater than 20 kHz. According to the presently disclosed subject matter monitoring of water flow is performed at high resolution enabling the detection of water flow pulses of less than 100 cc and as low as 50 cc (and in some cases even lower). As explained below, this type of resolution enables flow monitoring and control system 100 to accurately differentiate between flow events characterized by different consumption flow rates and thereby more accurately detect flow events resulting from leaks.

Today, known flow meter devices (such as those operating with a Hall Effect sensor) can provide high resolution flow information. In order to obtain high resolution flow information, sensor unit 250 must adapt high sampling frequency. High sampling frequency is necessary for detecting information generated in sensor unit 250 when water pressure in pipe 118 is high and accordingly rotation speed of the turbine and attached magnet is high as well. Using a sampling frequency which is lower than the rotation speed of the magnet would not be sufficient for obtaining flow information at the highest possible resolution. Indeed, some water flow monitoring units which are used today can operate at very high frequencies. For example, if a rotating turbine can reach up to 25,000 rpm, a respective Hall Effect sensor can be configured to produce around 50,000 pulses per minute (in case a bipolar magnet is used). However, due to the limited lifetime of power sources which are commonly used for powering flow meter devices, maintaining low power-consumption is necessary for enabling prolonged operation of the device without replenishing or replacing the power source. High frequency sampling is energy consuming and it is therefore counterproductive to the attempt to preserve energy resources. Accordingly, in order to preserve energy, a lower sampling frequency should be used. However, while lower sampling frequency (e.g. less than maximal turning frequency/speed of the turbine) would suffice for monitoring flow and obtaining flow information in lower water pressures, it is not sufficient for obtaining optimal flow information during high pressure flow in the pipe. The presently disclosed subject matter includes a sensor device which enables to perform high resolution sampling of water flow while maintaining low power consumption as described in detail in US Patent Application No. 13/733,341 submitted by the Applicant and which is incorporated herein by reference in its entirety.

Furthermore, in order to improve the detection of sensing device and enable the detection of water flow at low rates which is otherwise undetectable, the presently disclosed subject matter can optionally include a one way valve (OWV) 206. OWV 206 enables sensor unit 250 to detect water flow characterized by low rates which otherwise would not spin the turbine and therefore would pass in pipe 118 undetected. OWV 206 allows water flow only in one direction (towards the customer premises marked by the black arrows). In addition OWV 206 is configured with a valve characterized by an opposing force which can be overcome only by water flowing at a pressure which is greater than that force. Thus, water flowing at low pressure, which is insufficient for overcoming the opposing force of the valve, accumulates at one side of OWV 206. Water continues to accumulate until the pressure of the accumulated water is sufficient for overcoming the force of the valve and is flowing through. The pressure of the water which can flow through OWV 206 is also sufficient for spinning the turbine and therefore the water flow is detected by sensor unit 250.

Main unit 110 can further comprise a communication unit 233 configured for enabling bi-direction (transmitting and receiving) communication of information. Information gathered by the sensor unit as well as data output of the processing unit can be transmitted to a remote computer for further processing and/or storage. Instructions can be received from remote devices. For example, indications generated by the processing unit with respect to suspect leaks can be sent to a client's device and instructions to shut down water flow or alternatively to override an automatic shutdown, can be received from a remote computer or directly from a client device (e.g. cellular phone where communication unit 233 comprises for instance a GSM module). The data which is gathered by the sensor unit can be stored in data- repository 231 to be processed by processing unit 250 in order to monitor the water flow and detect suspected leaks. Data output generated by processing unit can also be stored in data repository 231. The storage capacity of data-repository 231 enables to store information which is collected and/or generated over a long period of time (e.g. months and years). Furthermore, data-repository 231 can also be configured with a data outlet socket (e.g. a USB port) enabling to directly connect to the data- repository 231 and obtain the stored information.

In case a suspected leak is detected, processing unit 250 can be configured to perform a preventive action. A preventive action can include for example sending a warning to a user (e.g. customer) via communication unit 233 (e.g. an SMS to a client device of the user) and/or automatically shutting down the water flow to the monitored premises. Communication between system 200 and a respective client device can be performed directly or via some other server or communication system. Communication can be facilitated via any type of appropriate network and/or protocol.

According to the presently disclosed subject matter flow monitoring and control is based on computer logic for identifying flow information. In case a flow event is characterized by a certain consumption flow rate, and a certain consumption volume is identified, the valve can be shut down.

Flow monitoring and control as disclosed herein includes a learning algorithm configured to adapt the computer logic to regular water usage in a given monitored premises and determine specific parameters for anomalous flow based on the common water usage in the specific monitored premises. The presently disclosed flow monitoring and control system also enables user interaction. For example, if a leak is detected, the system can be configured to communicate with the user and provide the user with the ability to remotely control the status of the water flow. For example, in some cases the user can receive a warning at his client device (e.g. cellphone, PC, portable computer, tablet, etc.) with respect to the detection of a suspected leak. In response, the user can choose to instruct to close the valve or leave it open.

Fig. 3 is a flowchart illustration of a general view of an example of a sequence of operations carried out, in accordance with the presently disclosed subject matter. As shown in Fig. 3 the process includes an initial learning stage (learning phase 310) and a normal working stage (working phase 320).

During the learning phase processing unit 250 is configured to monitor the water flow and obtain flow information (block 301). As mentioned above sampling performed by sensor unit 240 is adapted to enable detection of water flow pulses of as low as 50 cc (and possibly even lower). The information which is obtained by sensor unit 240 is processed by processing unit 250 in order to determine the specific characteristics of water usage in a specific monitored premises. During the learning phase flow information is analyzed to obtain information with respect to normal water usage patterns (block 303). The flow information as well as its processing output can be stored in a data-repository (e.g. in data-repository 231). The stored flow information can be later used for identifying abnormal flow events which deviate from recorded patterns and are therefore indicative of suspected leaks. The term "flow information" is used to include any information with respect to the water flow in a monitored premises. Thus, in addition to flow events and their respective consumption flow rate and consumption volume, flow information can optionally further include additional types of flow information. Additional types of flow information (other than flow events and their respective consumption flow rates and consumption volumes) can include one or more of the following information types, which are provided herein by way of non-limiting example only: the overall consumption volume during certain time periods (e.g. hourly consumption, daily consumption, monthly consumption), the time of occurrence of various flow events, the duration of various flow events, whether the house residents are currently in the house, the number of permanent residents of a given household, the types of flow consuming elements in a given household (e.g. whether there is an irrigation system or not), etc. For simplicity of understanding, additional types of flow information are referred to herein in general as "supplementary flow information".

Based on the obtained flow information, suspected leaks can be identified using default threshold values (block 305). To this end, processing unit is configured to identify flow events. A flow event is a certain pattern of water consumption that continues for a certain duration of time and results from water flow to one or more flow consuming elements (e.g. irrigation system, shower, toilet, kitchen faucet, bathroom faucet, etc.). Alternatively, a flow event can result from a leak. A flow event starts with a change in the water consumption flow rate by a certain degree. A flow event ends (after a certain time duration) when the water consumption flow rate returns back to the consumption flow rate at the time of the start of the flow event. Fig. 8 shows a graph plotting consumption flow rate against time and demonstrates flow events, in accordance with the presently disclosed subject matter. The information obtained by detector unit 240 is processed by processing unit 250 which is configured to generate the respective flow information including the water consumption flow rate as shown in Fig. 8.

The start of a first flow event (master flow event) is indicated by the arrow A on the left hand side of the graph. The end of the flow event is indicated by arrow A' on the right hand side of the graph. Note that the master flow event is comprised of two distinct intermediate events. The distinct intermediate events are called sub flow events. The start of one sub flow event is indicated by arrow B and the end of that flow event is indicated by arrow B'. The start of the second sub flow event is indicated by arrow C and the end of the second sub flow event is indicated by arrow C. The process of detection of flow events is described in more detail below with reference to Fig. 4. ln general, suspected leaks are identified in case the water consumption volume during a given flow event is greater than a certain threshold value. Responsive to the identification of a flow event suspected as a leak, processing unit can be configured to generate instructions for performing some type of preventative action (block 309). As mentioned above, such preventative actions can include for example a warning which can be sent to a user's client device, indicating that a suspected leak has been identified. If water consumption continues to rise above a certain level, processing unit 250 can instruct to shut down the water flowing to the premises. The threshold values which are used for detection of suspected leaks and for water flow shutdown during the learning phase are default threshold values, which are not specifically adapted to normal usage patterns in a respective monitored premises. Optionally, the default values which are used during the learning phase can be set as permissive values enabling the detection of extreme water flow events only (characterized by high water consumption). This would reduce the risk of false positive identification of normal flow events as leaks and unnecessary water flow shutdown during the learning phase.

The information gathered during the initial learning phase with respect to identified flow events can be used for identifying normal water usage patterns (block 304). Models representing the normal water usage patterns can be created based on the flow information obtained during the learning phase. These models (or the respective patterns) can later be compared to real-time events and used for discriminating between flow events representing normal usage and flow events representing suspected leaks. One example of such a model can be water flow patterns which are detected during the flush of a toilet. The toilet flush of a given toilet installed in a given premises is characterized by a certain range of consumption flow rates and a certain range of consumption volume. This information can be recorded and used during normal use in order to identify a toilet flush and negate the possibility of a leak. More examples of other water flow models are provided below.

The learning phase continues for a certain period of time (e.g. 2-4 weeks). Once sufficient flow information with respect to the normal water consumption is accumulated, user adapted threshold values are calculated based on the collected flow information (block 307). Different than the default threshold values, the user adapted threshold values are adapted for the specific normal water consumption of a specific monitored premises.

Similar to the learning phase, during the working phase (block 320) processing unit 250 is configured to continue and monitor the water flow and obtain flow information (block 311) which can be used to identify flow events which are suspected as leaks (block 315). However, during the working phase, user adapted threshold values are used instead of the default values. The user adapted threshold values enable to more accurately discriminate between flow events resulting from normal usage and flow events resulting from actual leaks. As before, responsive to the identification of a flow event suspected as a leak, processing unit 250 can be configured to generate instructions for performing some type of preventative action (block 319).

During the normal working phase, flow information is continued to be analyzed in order to be able to determine water usage patterns over longer periods of time and continuously improve and fine tune the decision rules of the algorithm based on up to date flow information (block 313).

Information which is gathered over time with respect to normal water usage patterns can be used for example for further adapting the user adapted thresholds (block 317). The continuous analysis of water consumption can be advantageous for example in case changes occur in the normal water consumption of a monitored premises (e.g. arrival of a newborn baby, a new irrigation system is installed, one or more residents permanently leave the house, etc.). According to the presently disclosed subject matter, in addition to the user adapted thresholds, supplementary flow information can also be used for determining whether a preventive action should be taken in response to detection of a flow event. For example, during the learning phase, the time and date of various flow events is recorded. A schedule can be generated by processing unit 250 indicating various flow events and the day of the week and time of the day in which they typically occur. The schedule can be used by processing unit 250 during the normal working phase in order to identify normal flow events which occur at the expected time and day. Processing unit 250 can be configured to compare a consumption flow rate and consumption volume of a given flow event to the consumption volume and flow rate of a flow consuming element which is scheduled to operate at the same time the flow event was detected. Based on this comparison, processing unit 250 can obtain additional indication whether the detected flow event is likely to be caused by a leak or not.

The system can also include different settings for times when there are residents in the monitored premises and times when the premises are vacant. For example, when the residents of a monitored household are away, more strict thresholds can be used than when they are at home. Switching from one state to the other can be done from a remote device communicating with main unit 110. For example, the user can send instructions from his cell-phone to main unit 110 to switch from one state to the other.

Fig. 4 is a functional block diagram schematically illustrating an example of processing unit 250 and sensor unit 240, in accordance with the presently disclosed subject matter. Fig. 4 shows a more detailed view of processing unit 250 and sensor unit 240. Processing unit 250 comprises sensor data analyzer 420, T-clock 410 and power controller 405. Power controller 405 is configured to control the power supply to sensor unit. Sensor data analyzer 420 can comprise for example, process controller 421, event detection module 423, actuator controller 425, sampling controller 427, threshold determination module 429, leak detection module 431, graph generator 433 and flow information determination module 435. Sensor data analyzer 420 in processing unit 250 is configured to receive from sensor unit 240 data generated by sensor 245 indicative of water flow in the pipe. As explained above, main unit 110 can be fixed to the external circumference of a fluid conductor (such as water pipe 118) outside the position of a turbine located within the pipe. Sensor 245 is configured to detect information indicative of flow within pipe 118. For example, as mentioned above, sensor 245 can be a Hall Effect sensor, configured to sample and detect changes in the induced electric field in the sensor, resulting from the rotations of a magnet embedded within or fixed to a turbine which spins as a result of the force of flow in the pipe. Sensor 245 is configured to generate a signal in response to a change in the induced electric field detected in the sensor. For example, each time sensor 245 detects a change in the induced voltage, sensor unit 240 can be configured to generate a pulse or switch a bit from 0 to 1 or from 1 to 0 (e.g. with the help of measuring output unit 241).

Process controller 421 is configured to control the process and initiate the different phases of the process. Upon start (or reset) of main unit 110 process controller 421 is configured to initiate the learning phase. The learning phase is executed for a certain period of time. Once the time designated for running the learning phase is terminated (or once sufficient information is accumulated) process controller 421 is configured to terminate the learning phase and initiate the normal working phase. Flow information determination module 435 is configured to determine, based on the information received from sensor unit 240, flow information including the frequency of the detected signals and the respective consumption flow rate and consumption volume of water flowing in the pipe. Flow information determination module 435 can be further configured to determine supplementary flow information parameters. Examples of supplementary flow information parameters were specified above with reference to Fig. 3.

Water consumption flow rate can be calculated as follows:

Each pulse (generated by a full rotation of the magnet) corresponds to 1/20

... l/20 Liter

Liter — ;

pulse

The time between a current pulse and a previous pulse (Δΐ), gives the amount of time it takes for 1/20 of a Liter to flow.

When Δΐ has units of hours, we

Example:

At = 1.8 Seconds = 5 * 10 ^~4 Hours

^■ rLiter pulse 1 Liter 1 Liter Liter

— * - = = = 100

pulse 5 * io ^"4 Hours 20 * 5 * 10 ^"4 Hours 0.01 Hours Hour

Event detection module 423 is configured to identify flow events. Optionally event detection module can be embedded as part of flow information determination module 435. As explained above, a flow event can be detected by identifying a significant change in flow consumption rate over a previous basic (e.g. average) consumption rate. The significant change in flow consumption rate can be identified by calculating the ratio between pulses detected by the sensor unit 240. For example, given three consecutive pulses a^, a.-i and a,, the ratio between the water consumption rate of pulses a, and a,. _! , the ratio between the water consumption rate of pulses a, and a^, and the ratio between the water consumption rate of pulses a.-i and ai-2 can be used for determining a significant change in water consumption rate by comparing the ratios to a derived threshold. The threshold can be a direct function of the water consumption rate of pulse a, (e.g. the threshold can be inversely proportional to the value of a,). For example a flow event can be identified if all the ratios are above the given threshold.

Similarly, the termination of a flow event can be identified by comparing several ratios to a derived threshold. The event termination ratios can be the ratio between the water consumption rate of pulses a, and a^, the ratio between the water consumption rate of pulses a.-i and a,, and the ratio between the water consumption rate of pulse a, and the average water consumption rate of the flow event.

Event detection module 423 can be further configured to identify sub-events embedded within other events as demonstrated by events B and C in fig. 8. Once event A is identified, a significant change in the consumption flow rate which is also significantly different than the consumption flow rate previous to event A (i.e. does not indicate the end of event A), is indicative of a sub-event.

The information obtained by flow information determination module 435 and event detection module 423 is stored in data repository 231 (which can comprise non-transitory computer memory). Optionally, sensor data analyzer 420 can comprise graphs generator 433 configured to generate various types of data display format (such as graphs) for presenting the flow information (e.g. graphs plotting water consumption rate against time). Leak detection module 431 is configured to determine whether the detected flow information is indicative of a suspected leak. Detection of a suspected leak is performed by identifying flow events (e.g. with the help of event detection module 423), determining the consumption flow rate and the consumption volume characterizing the flow event and comparing the result to a respective threshold value. As mentioned above, during the learning phase, default threshold values are used and during the working phase, user adapted threshold values are used. In case the difference between the calculated volume and the threshold is greater than a certain value, a suspect leak is detected. Additional flow information parameters can be used for detecting suspected leaks.

In case a suspected leak is detected, a preventative action can be performed. Processing unit 250 can be configured, responsive to detection of a suspected leak, to generate a user notification, indicating to the user that a suspected leak is detected and that the valve has been shut down or is about to be shut down (e.g. by sending a text message to the user's cellular device via communication unit 233). Furthermore, responsive to detection of a suspected leak, actuator controller 425 can be utilized for closing valve 220 and thereby stopping the leak.

Threshold determination module 429 is configured to calculate one or more threshold values based on the information obtained from sensor unit 240 with respect to the detected flow in the pipe. As explained above, user adapted threshold values are generated based on flow information which is obtained during the learning phase. The generated threshold values are continuously updated during the ensuing working phase.

As mentioned above, the presently disclosed subject matter applies high frequency sampling while maintaining low energy consumption. To this end processing unit 250 can comprise sampling frequency/duty cycle controller 430 which is configured to determine whether the sampling frequency assigned to sensor unit 240 should be modified, and to issue a command instructing sampling frequency/duty cycle adapter 246 to do so if a modification is required. Sampling frequency/duty cycle controller 430 can be configured to store the current sampling frequency and compare between the current sampling frequency and the currently detected frequency. Sampling frequency/duty cycle controller 430 is operable to modify the current sampling frequency of sensor unit 240 (by updating sampling frequency/duty cycle adapter 246) based on a calculated difference between the current sampling frequency and the currently detected frequency. Modification of the current sampling frequency can be accomplished by modulating the duty cycle of the sampling signal of sensor unit 240 and thereby modifying the respective sampling frequency.

Furthermore, according to the presently disclosed subject matter, in order to further reduce power consumption, processing unit 250 is configured to stay in sleep mode when there is no detectable flow in the pipe. Processing unit 250 is configured to wake up to become fully operative, only in response to a predefined number of pulses detected in sensor unit 240. When in sleep mode, only part of the elements in processing unit 250 operate, while the rest of the elements do not operate and therefore processing unit 250 consumes less energy. During sleep mode the currently detected frequency is not calculated and processing unit 250 is only partially operable. To this end, process controller 421 can be configured to control the operating mode of processing unit 250. Process controller 421 can be configured to count the detected signals received from sensor unit 240 and, based on the detected signals, cause the processing unit to switch from sleep mode to full operational mode and vice versa. As mentioned above, control of the sampling frequency and operating mode is described in detail in US Patent Application No. 13/733,341.

Fig. 5 is a functional block diagram exemplifying a more detailed view of the threshold determination module, in accordance with the presently disclosed subject matter. Threshold determination module 429 can comprise for example, histogram generator 501, histogram updating module 503 and threshold updating module 505. Note, that while Fig. 5 is related to a histogram, this is done by way of non-limiting example only and other types of grouping and representation can be used.

Fig. 6 is a flowchart showing an example of a sequence of operations which are performed during the learning phase, in accordance with the presently disclosed subject matter. Fig. 6 includes an example of a process for determining user adapted thresholds. Operations in Fig. 6 are described by way of example with reference to functional elements illustrated in Fig. 4 and Fig. 5.

Flow information is obtained by processing unit 250 and respective flow events are detected (block 601). After a flow event is detected the event is analyzed and flow event information characterizing the event is obtained (block 603). Flow information of a flow event includes the average water consumption flow rate (e.g. volume/hour) and the consumption volume of water flowing during the event. The overall volume of a given event can be calculated as follows:

Multiply the number of pulses received during an event by the number of

—Liters

liters per pulse (— ).

^ ^ ^v pulse '

Example:

If 100 pulses were received during an event, the volume of the event is

—Liters

100 pulses *— = 5 Liters

pulse

A flow event which is identified is assigned to a respective group (block 605). A detected event is classified as part of a given group based on the event's consumption flow rate. Each group comprises flow events characterized by a consumption flow rate within a certain range. According to one example, groups can be represented by bins in a histogram where each bin is assigned for recording flow events characterized by consumption flow rates within a certain range. For instance, a histogram with bins having a range of consumption flow rate value of 8 liters per hour can be used. Each group is associated with a maximal consumption volume, which is the highest consumption volume of all flow events assigned to the same group. According to one example, in case a histogram is used, the height of each bin (i.e. y axis value) can represent the maximal consumption volume of the respective bin. Alternatively, consumption volumes can be represented by x axis values. If the overall consumption volume of a given flow event is greater than the maximal value of the respective group, the maximum value of the group is updated and the volume of the detected event becomes the new maximal value (block 607).

Fig. 9 is an example of a flow events histogram after 8 days of flow monitoring, in accordance with the presently disclosed subject matter. Each bin in the histogram represents flow events characterized by a consumption flow rate within a certain range. The y axis represents the maximal overall volume of all detected events within the range of a given bin.

Optionally, the maximal values in each group (e.g. bin) can undergo a reduction process (block 609). During the reduction process the maximal values of the groups are decreased by a certain reduction value. The reduction process is repeated (e.g. periodically). Operations described with reference to blocks 607 and 609 can be performed by histogram updating module 503 in threshold determination module 429.

The reduction process is performed based on predefined parameters which determine which groups (e.g. bins) should be reduced and the reduction value. These parameters include for example, the activity in a given group and the age of a given group. The activity in a given group corresponds to the number of detected flow events which correspond to a given group. The values of groups which are characterized by greater activity are reduced by greater reduction values than other groups with less activity. The age of a given group corresponds to the time from the first detection of a flow event related to the given group. The values of groups which are older are reduced by greater reduction values than newer groups. The operations described with respect to block 601 to 609 are repeated throughout the learning phase. Thus, during the learning phase the maximal consumption volume of a given group is increased responsive to detection of respective flow events characterized by an overall consumption volume which is greater than the currently recorded maximal consumption volume. The maximal consumption volume of a given group is also repeatedly decreased based on predefined parameters. This process enables to model the flow patterns during normal usage in premises which are monitored. The model provides information with respect to the flow patterns of specific types of flow events which are categorized based on their respective consumption flow rate.

It is noted that optionally, during the learning phase only days which show consumption above a certain threshold are considered valid days. In case the consumption is less than the threshold, such days are ignored and flow information obtained during such days is not used for updating the values in the histogram. For example, if residents of a household are on vacation and therefore the overall detected water consumption volume in the monitored premises is less than a certain threshold value, the flow information recorded during the vacation days is not used for updating the histogram values.

According to the presently disclosed subject matter, the maximal consumption volume in each group (e.g. bin) serves as an indication of the threshold of flow events with a respective consumption flow rate. Thus, given a detected flow event with a given consumption flow rate, the threshold for detecting a suspected leak is set with respect to the maximal consumption volume of a respective bin. For example, a threshold can be set as a value which is greater by a certain percentage than the maximal consumption volume of the respective bin. Thus, according to the presently disclosed subject matter a specific threshold is determined for different flow events depending on the respective consumption flow rate of the event. Furthermore, the threshold is determined based on the typical consumption volume of flow events occurring in specific premises, which are characterized by a similar consumption flow rate.

Upon termination of the learning phase, new user adapted threshold values are determined based on the maximal consumption volume in each group (block 611). This can be performed for example by threshold updating module 505 in threshold determination module 429. Flow events are assigned with respective thresholds based on their respective consumption flow rate. Different flow events which are characterized by different consumption flow rates are assigned with different threshold values depending on the maximal consumption volume of their respective group.

Furthermore, more than one threshold value can be set for flow events corresponding to each group. For example, a first threshold can be set to equal a volume which is greater by 10% than the maximal consumption volume of a respective group. Responsive to detection of a flow event characterized by a consumption volume which is greater than (or equal to) the first threshold, a warning can be sent to the client (e.g. by way of an SMS to the client's cell-phone) indicating that a suspected leak is identified. The client can ignore the warning or alternatively the client can send back a command (to actuator controller 425) to shut down the water flow in the premises. A second threshold can be set to equal a volume which is greater by 25% than the maximal consumption volume of a respective bin. Responsive to detection of a flow event characterized by a consumption volume which is greater than the second threshold, actuator controller 425 automatically shuts down the water flow to the premises.

As mentioned above, during the learning phase the default thresholds are used in order to determine whether a preventative action should be taken responsive to detection of a flow event (block 613). Thus, each group can be assigned with a respective default threshold value. The default threshold value can be selected based on some type of estimation or historical information (for example, based on values obtained from multiple monitored premises in the past).

Optionally, where a histogram is used, a default histogram can be initially generated where default maximal values are assigned to each bin. The default threshold values can be determined with respect to the default values in the histogram. The histogram can be generated for example by histogram generator 501 in threshold determination module 291.

Fig. 7 is a flowchart exemplifying operations performed during the working phase, in accordance with the presently disclosed subject matter. The operations described with reference to blocks 701 to 703 are similar to operations described above with reference to Fig. 6. At block 701 flow information is obtained by processing unit 250 and respective flow events are detected. After a flow event is detected the event is analyzed and flow event information characterizing the event is obtained (block 703). The flow events are associated with a respective group (e.g. bin) based on the event's consumption flow rate (block 704). The user adapted threshold value of the respective group is used for determining whether the consumption volume during the event requires executing a preventative action (705).

In addition, supplementary flow information can also be used when determining whether a preventative action should be carried out. For example, as mentioned above, more strict thresholds can be used when the residents of a household are away than when they are at home. Furthermore, less strict thresholds can be used if a detected flow event of a given consumption flow rate occurs at a time when a flow event with similar consumption flow rate is expected. Both in the learning phase and the working phase, after a flow event is detected, the consumption volume which is accumulated during the event is continuously monitored. An indication of a suspected leak is generated once the consumption volume is equal to (or greater than) the respective threshold. This of course can occur before the flow event is terminated.

As explained below in detail, in addition to using thresholds, a respective source (flow consuming element such as an irrigation system or shower which causes the event) causing a flow event can be determined based on flow profile analysis 713.

During the working phase the threshold values are continuously updated. Similar operations to those described above with reference to blocks 607 to 609 described above with reference to Fig. 6 are performed. At block 707 in case the consumption volume of a detected flow event is greater than the maximal consumption volume of a respective group, the maximal consumption volume of the group is updated and the volume of the detected event becomes the new maximal consumption volume. This is done, for example, in case a maximal value determined during the learning phase was reduced during the reduction process (block 709 below). The operation at block 707 allows increasing the thresholds back to their maximal values after they have been reduced.

At block 709 the maximal values of each group undergo a reduction process, which is executed as described above with reference to block 609. At block 711 the user adapted threshold values are updated based on the updated maximal consumption volume of each respective group (e.g. each bin in a histogram).

As explained above in detail, the categorization of the flow events into groups (e.g. bins) based on their respective water consumption flow rate enables accurate characterization of the expected volume during flow events occurring during normal water usage. The categorization of flow events into groups of the proposed resolution is enabled due to high resolution water monitoring which is disclosed herein. Thus, the flow monitoring and leak detection which is disclosed herein exploit the availability of high resolution information in order to generate flow patterns which comprise sufficient information for discriminating between flow events with high resolution based on their respective consumption flow rates. This approach enables a more accurate characterization of normal water usage in a monitored premises and more accurate discrimination between different flow events, including flow events caused by normal usage and flow events caused by leaks.

According to the presently disclosed subject matter, as a result of the ability to discriminate between different flow events with high resolution, processing unit 250 can be configured to analyze the monitored information and differentiate between very small leaks, small leaks and major leaks. Detected flow events are classified as a respective type of leak based on their respective consumption flow rate. In general, very small and small leaks are leaks which involve a smaller volume of water flow than major leaks and are therefore less likely to cause major immediate damage. Once classified, very small and small leaks can be treated differently than major leaks and different preventative actions are executed depending on the specific type of leak.

In general, very small and small leaks are leaks which involve a smaller volume of water flow than major leaks and are therefore less likely to cause major immediate damage.

The following are numerical examples of different types of leaks. However, it is noted that these examples are provided for the sake of clarity only and should not be construed as limiting.

Micro Leak (very small leaks)

A micro leak flow event is flagged if the water consumption flow rate is between 0.5 L/H (litter per hour) and 10 L/H. Once a micro leak event is flagged, the minimum flow of the micro leak event is stored and used to calculate an estimated volume for the event. In case of a micro leak, a preventative action is initiated if the overall volume exceeds 50 L. The micro leak timers and counters are reset (i.e. the event is aborted) only if the flow drops below 0.5 L/H. Minor Leak (small leak)

A minor leak event is flagged if the water flow is between 10 L/H and 80 L/H. Once a minor leak flow event is flagged, the minimum flow of the minor leak event is stored and used to calculate an estimated volume for the event. In case of a micro leak a preventative action is initiated if the overall volume exceeds 50 L. The minor leak timers and counters are reset only if the flow drops below 10 L/H.

Major Leak

A major leak flow event is flagged when the water flow rises above 50 L/H. Once a major leak event is flagged, the valve will remain open until the volume reaches a specified threshold. The volume threshold for a major leak characterized by a given consumption flow rate, can be defined for example as being 50% greater than the maximal consumption volume of a respective group (e.g. bin in histogram). During a major leak event, if the water flow drops below 50 L/H, the major leak timers and counters are reset.

Fig. 10 is a flowchart showing an example of operations which can be performed in case a small leak (or a very small leak) is detected, in accordance with the presently disclosed subject matter. Fig.10 is an example of preventative actions which can be carried out responsive to detection of a flow event suspected as a micro leak or small leak.

In case a flow event which is suspected as a small leak is detected by processing unit 250 (block 1001) a message is sent to a client device of a respective user. For example an SMS can be sent to his cell-phone. The message informs the client that a suspected leak has been detected and asks whether to close the main valve or not (block 1003). The message can also include information characterizing the suspected leak. ln response, the user can instruct processing unit 250 to close the valve (block 1005). Processing unit 250 can close the valve by controlling actuator 1014. This can be done by a command generated via the client device (e.g. an SMS). Once the valve is closed (block 1007) a respective indication can be sent to the client informing that his instructions have been executed (block 1011).

The valve can then be opened at a later time following another command received from the user (block 1009). If the leak was not fixed (block 1015) the leak will be detected again and the process will start over from block 1001. Optionally, the system can be configured to wait for a given period of time before a leak warning is issued again. During this time the leak can be fixed. Because it is a small leak which does not create immediate damage, the system allows the water leak to continue before sending another warning.

If the user does not instruct to close the valve in response to the indication of a leak (block 1017), the threshold for detecting a leak can be adjusted. Processing unit 250 can be configured to raise the threshold for small leaks. Optionally, processing unit 250 can be configured to send messages reminding the user that the leak has not been fixed and that the system's detection capability of leaks has been degraded. This may occur for example in case there is a small leak in the garden and the user did not fix the leak. The user may wish to continue to irrigate the garden although the leak has not been fixed. Therefore, the threshold for small leaks is updated in order to avoid generating repeating warnings for the same flow events caused by the leak in the garden.

Fig. 11 is a flowchart showing an example of operations which can be performed in case of a major leak, in accordance with the presently disclosed subject matter. Fig.11 provides an example of preventative actions which can be carried out responsive to detection of a flow event suspected as a major leak.

In case a flow event which is suspected as a major leak is detected by processing unit 250 (block 1101), a message is sent to a client device of the user. For example an SMS can be sent to his cell-phone. The message informs the client that a suspected leak has been detected and enquires whether to close the valve or not (block 1103).

In response, the user can instruct processing unit 250 to close the valve (block 1105). This can be done by a command generated via the client device (e.g. an SMS). Once the valve is closed, the timers and counters (of the water flow of the leak) are reset (block 1107) and a respective indication can be sent to the client information that his instructions have been executed (block 1109).

The valve can then be opened at a later time following another command received from the user (block 1111). If the leak was not fixed, the leak will be detected again and the process will restart at block 1101. Optionally, the system can be configured to wait for a given period of time before a leak warning is issued again.

If the user instructs to keep the valve open, or ignores the leak warning in response to the indication of a leak (block 1117) processing unit 250 can be configured to temporarily raise the threshold for a leak by a certain ratio (e.g. by 25%).

If the new limit (threshold) is not reached, the event is terminated (block 1123). Otherwise if the new limit is reached (block 1121) the valve is closed and the timer and counters are reset (block 1107). As mentioned above, normal usage water patterns which are identified during the learning phase are used during the normal working phase for discriminating between flow events resulting from normal usage and flow events resulting from leaks. Another example of using the water flow information during normal usage for more accurately detecting a suspected leak is identification of specific water flow profiles.

In premises where a high water consumption system is operating, it can be a complicated task to determine whether a detected water flow event results from normal water usage or from an actual leak. Water flow patterns can be helpful in quickly identifying the source of various flow events. The term "high water consumption system" as used herein refers to a flow consuming element which is characterized by a flow consumption rate which is greater than a certain threshold. A high water consumption system can include for example an irrigation system or a shower.

One example of this problem is a flow event caused by a leak occurring in premises with an irrigation system. The flow event may be characterized by consumption flow rate values which are similar to water consumption flow rate values of the irrigation system and therefore will be assigned with the same threshold as the irrigation system. In such a case, the main valve will be closed only after the overall consumption volume of the spilled water will be greater than the threshold value assigned to the irrigation system and can therefore result in water wastage and potential damage. According to the presently disclosed subject matter there is provided a method for obtaining information from the flow patterns of specific flow events enabling to associate detected events with their respective sources and discriminating between flow events caused by normal water usage and flow events caused by suspected leaks. As mentioned above, water flow is continuously monitored by main unit 110.

A curve of the water flow plotting the water consumption flow rate against time can be generated (e.g. with the help of graphs generator 433). The plotted curve shows the change in water consumption over time. This change is referred to herein as a "water profile". Different flow events caused by normal usage (e.g. by consuming elements such as an irrigation system, shower, toilet etc.) are characterized by a distinctive flow profile. The flow profile of these events is different to the flow profile of flow events which are caused by a leak. The flow profile is characterized by certain features which can be identified and used to determine the source of the flow event and thereby to discriminate between flow events caused by normal usage and flow events caused by a suspected leak.

Flow profile distinguishing features may include for example:

1. A leap in the water consumption rate - at the onset of a flow event (primarily but not exclusively in high consumption flow rate events such as irrigation or showers), a steep rise in the water consumption rate occurs. For example, when the irrigation system is turned on, the curve representing this flow event will show a substantial leap in the water consumption rate. The onset of different types of flow events are characterized by a different rise in the water consumption rate. It is likely that a random leak would not show exactly the same slope as another specific normal usage flow event such as a specific irrigation system or a specific shower on specific premises. Therefore, this feature can be used for identifying a flow pattern of a specific consuming element.

During the learning phase, the flow profile (including the peak and slope) of water consumption which characterizes the onset of different normal usage flow events can be recorded. This information can later be compared to information gathered during a normal working phase and may be used for discriminating between normal events and suspected leaks.

2. Distance between the peak of the leap in water consumption, followed by a descent - typically, in case of a sudden increase in water consumption

(at the onset of a flow event), after the water reaches a certain peak it is followed by a decrease in water consumption and then it stabilizes more or less around a certain value. This is because initially when the water starts flowing, before it reaches the output cavity (e.g. a hole in a pipe in case of a leak or pipe inlet/outlet, in case, for example, in irrigation), it encounters less resistance. Thus, the size of the respective cavity determines the resistance and imposes a decline on the water flow. As before, it is likely that this feature would not be the same during a given normal water usage flow event such as irrigation or shower, and an actual leak. During the learning phase the distance between the peak water consumption rate and the following descent characterizing the flow pattern of different normal events, can be recorded. This information can later be compared to information gathered during the normal working phase and used for discriminating between normal events and suspected leaks.

3. The peak of the leap of water consumption and the descent which follows - a flow profile distinguishing feature which is similar to the previous feature, only here it is the time between the peak of water consumption rate and the descent which follows in water consumption rate, rather than the distance. One or more of these flow profile distinguishing features (or any other features characterizing the flow profile of specific flow events) can be used for determining whether a detected raise in water flow is likely to be a suspected leak or a normal event, such as irrigation or a shower. As explained above, these features can be monitored, recorded and modeled (in respective flow models) during the initial learning phase and used for discriminating between normal water usage events and suspected leaks. This can be done by comparing the flow models with real-time flow information.

Optionally, the flow profile features of normal flow events can be identified by turning on a certain water source (e.g. water consuming element such as irrigation system or shower) and recording the respective flow profile.

Optionally, information with respect to the above features during normal events can be provided to processing unit 250. This may be necessary for example in case the relevant events did not occur during the initial learning phase and therefore the system was unable to acquire the required information (e.g. the garden was not irrigated during the initial learning stage).

Also, optionally main unit 110 can be switched back into the learning stage for a limited period of time. During this time one or more flow events can be initiated (e.g. the garden can be irrigated) to enable the main unit to acquire the required flow profile information.

Other methods for identifying water flow profile of specific consuming elements can include for example acoustic profiles. Water flowing to different consuming elements may generate different sounds. According to the presently disclosed subject matter, these sounds can be used to aid in discriminating between flow events which are caused by normal usage and flow events which are caused by leaks.

The sounds of water flow to specific water consuming elements can be recorded and provided as input to processing unit 250 (sounds can be stored in data- repository 231). Main unit 110 can further comprise a recorder for recording the sounds of water flow flowing through the pipe. Processing unit 250 can be configured to compare the sound of water flow during a given flow event to the sounds of water flow caused by specific flow consuming elements. If the sounds are sufficiently similar (based on some predefined conditions, for example based on similarity between the sound waveforms) they may serve as an indication as to which consuming element caused the flow event.

Another example of a water flow profile can be based on a piezoelectric element. A piezoelectric element can be used for identifying specific piezoelectric effects which are caused by water events caused by specific consuming elements in a similar manner to that described above. To this end a piezoelectric element can be integrated as part of flow monitoring and control system 100 and configured to generate a piezoelectric effect responsive to water flow. Processing unit 250 can be configured to compare between piezoelectric effects detected in real-time and pre- stored information with respect to other piezoelectric effects which are caused by flow to specific consuming elements.

In addition, the presently disclosed subject matter discloses a method of modifying the flow profile of flow consuming elements (e.g. water facilities) such as irrigation systems and showers. The presently disclosed subject matter further discloses a flow modification apparatus for enabling the modification of flow profiles. A flow modification apparatus can be connected to a conductor (pipe) of a given flow consuming element (e.g. pipe leading water to a water system such as an irrigation system or a shower). The flow modification apparatus is configured to modify the flow towards a respective water consuming element and thereby provide a flow profile with distinguishing flow profile features. Various types of flow modification apparatuses can be used which can provide various respective types of distinguishable flow profiles. For example, one type of flow modification apparatus can be configured to prolong the time from the opening of a valve to the time the water can flow in full capacity through a respective water consuming element.

Figs. 12a to 12c show one example of a flow modification apparatus, in accordance with the presently disclosed subject matter. The structure of the apparatus creates a delay during the onset of water flow. This modification in the water flow would be apparent during the initial stages of water flow (immediately after the water is turned on) and can be detected by the sensor unit and recognized by processing unit 250. It is noted that the flow modification apparatus depicted in Fig. 12 is merely a non-limiting example and various other types of apparatuses (and methods) for modifying the water flow as described herein are within the scope of the subject matter disclosed herein.

Fig. 12a shows an outside view of the flow modification apparatus, in accordance with the presently disclosed subject matter. Fig. 12a II shows a cross section view of the flow modification apparatus, in accordance with the presently disclosed subject matter. The flow modification apparatus can include parts made of any appropriate material such as plastic or metal. As can be seen in Fig. 12a the flow modification apparatus is characterized by a hollow shape element being connectible to a conductor. The flow modification apparatus can be connected at various locations along the conductor near its end, the end being connected to a consuming element. For example, the flow modification apparatuses can be connected before the end (e.g. pipe outlet) or at the end of the conductor (e.g. being integrated as part of the consuming element outlet). Water (or any other liquid or gas), which flows through the pipe, passes through the modification apparatus and continues to flow either through the remaining section of the pipe or outside the pipe (if the apparatus is connected at the end of the pipe). The specific inner design of the modification apparatus generates the specific flow profile. The inner design can include various grooves and/or flow constricting elements which generate the distinctive flow profile.

Fig. 12b shows a more detailed view of one non-limiting example of a flow modification apparatus, in accordance with the presently disclosed subject matter. Flow modification apparatus 1200 comprises housing 1202 accommodating cone 1201 located within a sleeve 1207 having an inner cavity. The cone is suspended by biasing member 1203 (e.g. spring). The cone is designed with a number of flow constricting rings 1209 encircling the cone. Direction of water flow through apparatus 1200 is indicated by arrow 1210.

Fig. 12 c shows another cross section of flow modification apparatus 1200, in accordance with the presently disclosed subject matter. When the water in the pipe is turned on, the water pressure after apparatus 1200 (in the direction of the consuming element) drops. As a result, a water pressure difference is created between the space before the cone 1213 and the space after the cone 1211. As a result of this difference in pressure, the cone is pushed against the spring and creates a gap (1223) between cone 1201 and housing 1202. Water can then flow around the cone and into space 1211 and towards a consuming element connected downstream to apparatus 1200. Arrow 1215 in Fig. 12c illustrates the direction of water flow. The movement of the cone shifts cone 1201 along with o-ring 1205 and creates chamber 1217 within sleeve 1207. As a result of the low pressure in the chamber, water flows through the inner cavity 1221 located within the cone (which serves as a water conductor) and fills up the chamber. Due to the small diameter of the inner cavity, water flow into the conductor is at a low consumption flow rate.

As chamber 1207 is filled with water the cone is pushed further against the spring 1203 and, as a result of the slanted shape of the cone, the gap 1223 between the cone and the housing 1202 increases, allowing more water to flow towards the consuming element. Fig. 12d shows flow modification apparatus in a full open position, in accordance with the presently disclosed subject matter. Note that in Fig. 12d spring 1203 is pushed by the cone as a result of the water pressuring building up in chamber 1217 and gap 1223 between housing 1202 and cone 1201 is larger than in Fig. 12c. As a result, water can flow more freely towards the consuming element.

Once the second flow constricting ring 1209 around the cone reaches the opening section 1225 in the housing, the rise in the water consumption flow rate is reversed resulting from a decrease in the size of the gap between the cone and the housing. As the chamber continues to be filled, the cone is further pushed against the spring and the consumption flow rate rises again once the second flow constricting ring 1227 is moved beyond the opening section 1225.

An additional decrease and a following increase in the flow consumption rate can be observed once the third flow constricting ring 1229 reaches and then passes beyond the opening. Note that the diameter of the second and third flow constricting rings is smaller than the diameter of the opening section and thus reduces the flow consumption rate but does not block the flow entirely.

Various features of the flow modification apparatus can be modified in order to obtain various distinguishable flow profiles. For example, the number of rings encircling the cone can vary, as well as the diameter of the various flow constricting rings. The fluctuations which are caused to the flow consumption rate by the movement of the cone, generate a distinctive flow profile which can be identified by the processing unit. The inner design can further include various other moving parts such as a spinning turbine which is spun by the flowing water. The turbine can be configured to exert opposing force at the onset of the flow. Once flow having a certain pressure flows to the turbine, the opposing force is overridden and the turbine can spin freely. Thus, the turbine is configured to temporarily decrease consumption flow rate and thereby modify the flow profile of the respective flow consuming element.

Fig. 13 is a curve showing flow rate of an irrigation system without a flow modification apparatus, in accordance with the presently disclosed subject matter.

Fig. 14 is a curve showing flow rate of an irrigation system with a flow modification apparatus, in accordance with the presently disclosed subject matter.

As seen in Fig. 13, as the irrigation system is turned on, a single steep rise in water consumption rate is seen from zero to a little above 1600 liters per hour. On the other hand, the graph in Fig. 14 shows a distinctive change of consumption flow rate over time caused by the flow modification apparatus. Obtaining and using the flow profile for discriminating between flow events resulting from different water consuming elements as well as using flow profile modification is made possible due to high resolution water monitoring which is disclosed herein. High resolution water monitoring as disclosed herein enables to generate high resolution flow patterns which comprise sufficient information which enables discriminating between different flow patterns representing flow events generated by different consuming elements.

Since flow profile features can be used for characterizing the water flow profile at the onset of the flow, this technique can provide an indication of suspected leaks immediately as they occur. Fig. 15 is a flowchart illustrating an example of a sequence of operations which are carried out, in accordance with the presently disclosed subject matter. Operations described with reference to Fig. 15 can be performed for example by processing unit 250 with the help of flow profile manager 437. At block 1501 information indicative of at least one flow profile of a respective water consuming element is obtained. Proceeding unit 250 in the main unit can be provided with information indicative of a specific flow profile characterizing the flow of a specific water system in the monitored premises. According to one option, the flow profile can be inputted from an external source. According to another option, the flow profile can be obtained by processing unit 250. For example, processing unit 250 can be synchronized to monitor the operation of a specific water consuming element such as an irrigation system. The flow information which is recorded during the time the irrigation system is operating is recorded and analyzed by processing unit 250 (e.g. with the help of flow profile manager 437) and the respective flow profile can be extracted from the recorded flow information.

As explained above, during the normal working phase, real-time flow information is obtained by processing unit 250 and flow events are identified (block 1503). The flow profile characterizing the detected flow events is determined by processing unit 250 (block 1505). As mentioned above, the flow profile can be detected immediately after the beginning of a flow event is detected. The flow profile can be any type of flow profile including for example a flow profile based on changes in consumption flow rate over time, based on sound and/or based on piezoelectric effect. Optionally, more than one type of profile can be used. The flow profile of the flow events detected in real-time are compared to the at least one flow profile of the respective water consuming element (block 1507). If the flow profile of the flow event detected in real-time is the same (or the similarity between the former and the latter complied with one or more conditions e.g. similarity between the waveforms) as a flow profile of a specific water consuming element, it can be determined that the real-time flow event is caused by the same water consuming element (block 1509).

If the flow profile of the flow event detected in real-time is not the same (or is sufficiently different based on one or more parameters) as any pre-recorded flow profile of a specific water consuming element, it can be determined that the realtime flow event is suspected as a leak (block 1511).

In some cases, the indication based on the flow profile can be used as a conclusive indication. Alternatively it can serve as a partial indication, in which case additional processing may be required in order to determine whether the detected flow is a suspected leak or not. Thus, further processing may be required in order to provide a more conclusive indication as to whether the flow event is caused by a leak or not.

It is to be understood that the presently disclosed subject matter is not limited in its application to the details set forth in the description contained herein or illustrated in the drawings. The presently disclosed subject matter is capable of other embodiments and of being practiced and carried out in various ways. For example, the presently disclosed subject matter is not limited to magnetic sensors, and the modifications disclosed herein are applicable to other types of sensors as well. For instance, an optical sensor providing indication of changes in absorbed light intensity can also be integrated with an appropriate processing unit as disclosed herein, which is configured to adapt the sampling frequency of the sensor based on a currently detected frequency. Furthermore, although the examples in the description are provided with respect to water flow, this is done by way of non- limiting example only and the presently disclosed subject matter is not limited to monitoring and control of water flow, and can be similarly used for monitoring and control of other liquids (e.g. oil or petrol) and gases. Also, the presently disclosed subject matter is not limited to monitoring of water flow or any other liquid or gas into premises and can be used in other systems or structures, such as for example monitoring water flow to a large scale irrigation system with various types of irrigation outlets.

Hence, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting. As such, those skilled in the art will appreciate that the conception upon which this disclosure is based may readily be utilized as a basis for designing other structures, methods, and systems for carrying out the several purposes of the present presently disclosed subject matter. It will also be understood that the system according to the presently disclosed subject matter may be a suitably programmed computer device. Likewise, the presently disclosed subject matter contemplates a computer program being readable by a computer for executing the method of the presently disclosed subject matter. The presently disclosed subject matter further contemplates a machine- readable memory tangibly embodying a program of instructions executable by the machine for executing the method of the presently disclosed subject matter.