Technical Field of the Present Invention

The present disclosure relates to an improved architecturally controlled building automation system.

Background of the Present Invention

Automations systems in signal communication with a plurality of sensor units providing readings in the form of electricity usage as well as temperature or humidity are known per se. Data collected from such monitoring units are processed by a central station in order for implementing advanced real-time control techniques. In addition, occupancy profiles in buildings may provide critical data in order for effectuating building automation management of heating, ventilation, lighting and air conditioning systems.

Typically, sensor readings from various units may be used to detect unforeseen situations in the form of exceptions to normal or foreseen patterns. The heating, ventilation and air conditioning system may be operated according to the specific usage patterns of the building to provide energy saving when possible.

Such automation systems rely on sensor units (such as temperature, or humidity sensors) and communication terminals, i.e. portable or stationary terminals such as computers, smartphones etc.

The attempts made in the state of the art to address building automation system issues are for instance described in US8078330.

US8078330 discloses a computer based method of avoiding a new energy peak, comprising: priming a computer-based system with data as to energy peak(s) already reached in a building system; for current energy usage in the building system, obtaining, in real-time, computer-readable data from which to automatically forecast if a new energy peak is approaching; and real-time automatic processing the obtained computer-readable data to forecast whether or not a new energy peak is approaching.

The present invention, on the other hand, discloses a building automation system in which all inner architectural spaces in a building have their own occupancy patterns. While each inner architectural space's occupancy pattern in a time-dependent manner is used to operate the heating, ventilation, and air conditioning system, any discomfort period due to deviation from the time-dependent temperature, humidity or carbon dioxide patterns is more rapidly compensated by the heating, ventilation, and air conditioning system.

The present invention provides a building automation system as provided by the characterizing features as defined in Claim 1. Objects of the Present Invention

The object of the invention is to provide a building automation system that controls heating, ventilation, and air conditioning systems based on an occupancy pattern of a building.

A further object of the invention is to provide a building automation system that allows automatic switching to energy saving mode when applicable.

A further object of the invention is to provide a building automation system that collects data from a plurality of sensor units to detect deviations from instantaneous time-dependent profile or usage pattern of the building units. Summary of the Present Invention

The present invention discloses a building automation system in which all inner architectural spaces in a building have their own temperature, humidity or carbon dioxide patterns collected over a predetermined time period. All inner architectural spaces in the building comprise a plurality of sensor assemblies comprising sensor units such as temperature, humidity, carbon dioxide and/or illuminance detecting units in communication with a central node. Each inner architectural space's patterns in terms of the above parameters in a time-dependent manner, i.e. in dependence to the specific month of the year and time of the day, is used to operate the heating, ventilation, and air conditioning system.

On the other hand, as a discomfort period for the occupants of a given inner architectural space will occur until any deviation from the time-dependent pattern of said inner architectural space will be compensated by the heating, ventilation, and air conditioning system, the present invention makes use of a real-time occupancy change data between respective inner architectural spaces to generate a second pattern in an effort to make an estimation as to the expected change in occupancy in respect of a certain architectural space in a building. This second pattern is used to operate the heating, ventilation, and/or air conditioning system to shorten the discomfort period in response to deviation of the sensor unit readings from said first pattern.

Brief Description of the Figures of the Present Invention

Accompanying drawings are given solely for the purpose of exemplifying a building automation system, whose advantages over prior art were outlined above and will be explained in brief hereinafter.

The drawings are not meant to delimit the scope of protection as identified in the claims nor should they be referred to alone in an effort to interpret the scope identified in said claims without recourse to the technical disclosure in the description of the present invention.

Figure 1 demonstrates an inner architectural space in the form of a room with lateral walls and having a plurality of activity regions. Figures 2a to 2c demonstrate a plurality of inner architectural spaces in the form of a zone, each one preferably having a plurality of activity regions, each activity region having a sensor assembly according to the present invention. Occupancy changes in respective spaces are shown with varying grey tone colors in Figures 2a to 2c.

Figure 3 demonstrates a plurality of exemplary inner architectural spaces. Although each of sad inner architectural spaces may have a different structural form and number of activity regions according to the present invention, for the sake of clarity, they are represented in the form of identical rectangles in Fig. 3, each one having a single activity region.

Referenced Parts List

The following numerals are referred to in the detailed description of the present invention.

11) Building automation system

12) Inner architectural space

13) First activity region

14) Second activity region

15) Sensor assembly

16) Occupancy sensor

17) Central station

18) First inner architectural zone

19) First-degree inner architectural zone

20) Second-degree inner architectural zone Detailed Description of the Present Invention

The present invention discloses a building automation system (11) in which all inner architectural spaces (12) in a building have their own temperature, humidity and carbon dioxide patterns collected over a predetermined time period. All inner architectural spaces (12) in the building comprise a plurality of sensor assemblies (15) having sensor units such as temperature, humidity, carbon dioxide, illuminance sensing units in communication with a central node. Each inner architectural space's (12) sensor reading pattern in respect of different parameters in a time-dependent manner, i.e. in dependence to the specific month of the year and time of the day, is used to operate the heating, ventilation, and air conditioning system. On the other hand, it is to be noted that a discomfort period for the occupants of a given inner architectural space (12) will occur until any deviation from the pattern of said inner architectural space (12) can be compensated by the heating, ventilation, and air conditioning system. An inner architectural space (12) is basically a closed zone with generally four lateral sides and at least one entry or exit opening, i.e. a door. The inner architectural space (12) may have floor portions where people can or cannot freely walk such as for instance shelves in a supermarket and the free spaces between any shelves. Each zone (=space) may therefore have a plurality of activity regions (first and second activity regions; 13, 14), i.e. areas where people can walk.

According to the present invention, each activity region is provided with at least one sensor assembly (15) comprising a plurality of individual sensor units in the form of occupancy, temperature, humidity, carbon dioxide and illuminance detecting units. It is to be noted that a single activity region may have more than one sensor assembly (15) due to the structural nature of the specific activity region. For instance, while a more central activity region may have a single sensor assembly (15), an activity region with a larger length compared to its width may need more than one sensor assembly (15) in order to accurately detect occupancy changes. Therefore, the layout and borders of activity regions are determined based on the architecture of the inner architectural spaces (12) and their suitability for detecting occupancy changes. By way of example, each inner architectural space (12) generally has a plurality of activity regions, each one with a single sensor assembly (15). Occupancy sensors may typically use infrared, ultrasonic or microwave technology. Operation of temperature, humidity, carbon dioxide, or illuminance detecting units available in the market are also known to the skilled worker and they therefore need not be further mentioned herein.

The building automation system (11) relies on time histories for each and every inner architectural space (12) in the manner that an inner architectural space (12) can be associated with time-dependent monthly and daily time histories by which it is possible to determine real-time deviations from zone- specific pattern data at a certain time period of a day by comparing readings from various sensors with pattern data on a time-dependent basis in an activity region of a certain zone. More specifically, real time data for a certain inner architectural space (12) is compared to pattern data of said inner architectural space (12) for the same month of the year, day of the month and hour of the day.

Thanks to data patterns created by processing data collected from different sensor assemblies (15) monitoring occupancy, temperature, humidity, carbon dioxide and illuminance profiles in an inner architectural space (12) or activity region over the course of a certain time duration, time histories for each activity region or inner architectural space (12) where people are present are known on an hourly and daily basis for working days as well as weekends. Therefore, a predetermined heating, ventilation, and air conditioning system operating scheme is implemented in each inner architectural space (12) or preferably in each activity region based on the these data patterns. Parameter values in the pattern data with respect to daily, monthly or hourly values for a specific time of the day can have different weight coefficients for determining an average value. When a working day is considered, pattern data for weekends is ignored. More precisely, all previous dates with the same date (including public holidays such as Labor Day) forms data patterns if they are under the same weekday or weekend category. In addition, data for all days of the year irrespective of their specific month is also used to form combined daily pattern data. These daily-basis and month-specific daily- basis patterns' effect in generating the final pattern is adjustable. Preferably, the final pattern is generated mainly based on the specific day and time of the specific month in consideration of the current day being a workday or weekend.

However, as already mentioned earlier, a discomfort period will be experienced by the occupants of a given inner architectural space (12) or activity region until any deviation from the data pattern of said space or activity region is compensated by the heating, ventilation, and air conditioning system. Therefore, the present invention is devised under the recognition that any deviation from the data pattern should be compensated so as to create a discomfort period which is substantially reduced.

According to the present invention, while the discomfort period should be shortened as much as possible, energy usage more than necessary should be avoided as well. In other words, any real-time deviation in the sensor readings from data patterns should be compensated using a well-defined amount of energy consumption. More precisely, the building automation system (11) of the present invention responds to any change in the hourly and daily patterns according to the method which will be delineated hereinafter.

In accordance with the present invention, each and every inner architectural space (12) or zone inside a building communicates with other zones through entry or exit points, i.e. doors. Additionally, an inner architectural zone may have more than one activity region in a certain architectural layout. A first inner architectural zone in access communication with a second inner architectural zone are called neighboring inner architectural zones and realtime occupancy changes in the first inner architectural zone are directly related to occupancy changes in the neighboring inner architectural zones.

According to the present invention, each inner architectural zone comprises occupancy sensors (preferably as integrated into said sensor assemblies (15)) preferably at entry or exit points by which real-time occupancy changes in an inner architectural zone can be detected. By way of example, in the event that current temperature sensor readings in an inner architectural zone deviate from the data pattern for the specific month and day of the week on an hourly basis, the building automation system (11) collects real-time occupancy data from all of the neighboring inner architectural zones directly neighboring the inner architectural zone in question and forms an occupancy change pattern between said neighboring inner architectural zones and said inner architectural zone in question.

More precisely, assuming a first inner architectural zone (18), a certain number of neighboring first-degree inner architectural zones (19) and a certain number of second-degree inner architectural zones (20) neighboring said first-degree zones, real-time occupancy change data from said second- degree inner architectural zones (20) to said first-degree inner architectural zones (19) and from said first-degree inner architectural zones (19) to said first inner architectural zone (18) is used to generate a second data pattern in the case of deviation from the first data pattern and a more accurate and refined occupancy prediction can be undertaken by a central station/node (17) in communication with all sensor assemblies (15) having occupancy detecting units in the first and second degree inner architectural zones (19, 20).

It is to be noted that large public buildings such as concert halls or publicly accessible places such as shopping malls have standard occupancy change patterns from a number of neighboring halls to other specified halls during certain events or at certain times. Occupancy change in a certain inner architectural space (12) may have a standard occupancy change pattern such as when a considerably large number of spectators walk out of a given concert hall. Therefore, in accordance with the present invention, a central station (17) first determines a deviation from the first data pattern in a certain inner architectural space (12) in terms of temperature, humidity or carbon dioxide (the three being primarily caused by effects due to human movements) and in that case creates an occupancy change data pattern for that specific inner architectural space (12) in order to make a prediction as to the estimated number of people in that specific inner architectural space (12) in 5, 10, 15, 20, 25 and 30 minutes time.

More particularly, the approach according to the invention provides critical results in terms of energy saving because since any deviation from the first data pattern is only taken into account if the amount of deviation falls outside predefined tolerance limits, the second data pattern provides even more accurate results in terms of expected occupancy changes for each inner architectural zone.

Furthermore, occupancy changes in neighboring activity regions within a single inner architectural zone can also trigger use of the second data pattern. For instance in the case of a very large department store, certain activity regions can attract more and more people compared to other ones with limited number of people. However, this trend can rapidly change if a certain product is promoted by an announcement for a special sale or complimentary gift. In that case, one of the central stations (17) of the building automation system (11) processing real-time collected data from a plurality of temperature, humidity and carbon dioxide sensor units, evaluate whether there is a deviation from the daily and hourly data pattern (first data pattern) and whether revision of the building management parameters is necessary. If the current status reveals that the change in sensor readings exceeds a predetermined limit, real time readings by each occupancy sensor in association with each activity region or inner architectural space (12) is processed to generate the second data pattern. While the first data pattern comprises history information in relation to temperature, humidity and carbon dioxide parameters, the second data pattern comprises real time occupancy change information.

For instance, if the temperature in one of the activity regions in the department store rises beyond predefined limits, the central station in communication with a certain number of sensor assemblies (15) in the activity region in question and in other neighboring activity regions within the given inner architectural space (12) will rely on, to operate the heating scheme, the second data pattern comprising human occupancy changes in all of the first degree and second-degree activity regions around said activity region in question.

The occupancy change pattern (second pattern) is not a time-dependent one and all previous cases during which the first standard pattern is not any more applicable for the subject activity region (or space) and the occupancy changes are monitored for all of the first degree and second-degree activity regions around said activity region are taken into account to generate the second data pattern. By way of example, either an activity region or a zone, if the building management system (11) needs to abandon the management routine created based on the first data pattern, first and second degree neighboring zones' occupancy changes are predicted also based on previously created second pattern data, which is only an occupancy change data pattern and the management routine is revised based on the second data pattern for the subject activity region or zone. It is also possible that there exist no prior data for the case-specific combination of the first inner architectural zone (18), first-degree inner architectural zones (19) and second-degree inner architectural zones (20). In that case, the central station (17) generates the second pattern and estimated occupancy change progress based on the initial data on the speed and direction of the occupancy change.

Any steps of a method according to the present application may be embodied in hardware, in a software module executed by a processor, or in a cloud computer. If implemented in software, the functions described may be stored as one or more instructions on a computer-readable medium.

In a nutshell, the present invention proposes a building automation system (11) comprising a plurality of inner architectural spaces (12), each of said inner architectural spaces (12) having at least one activity region and each of said activity regions having at least one sensor assembly (15), said building automation system (11) further comprising at least one central station (17) in signal communication with said at least one sensor assembly (15). In one embodiment of the present invention, said central station (17) stores a preloaded first sensor reading data pattern for each of said inner architectural spaces (12) and activity regions collected over a predetermined time period from said sensor assemblies (15) in the manner that a heating, ventilation or air conditioning system in association with an inner architectural space (12) or activity region is operated based on said first data pattern.

In a further embodiment of the present invention, real-time deviations from said first data pattern at a certain time of a day in a first inner architectural zone (18) is determined by comparing real-time readings from said sensor assemblies (15) with said first pattern data on a time-dependent basis.

In a further embodiment of the present invention, said building automation system (11) collects real-time occupancy data from said sensor assemblies (15) in first-degree inner architectural zones (19) enclosingly directly neighboring said first inner architectural zone (18) and in second-degree inner architectural zones (20) enclosingly directly neighboring said first- degree inner architectural zones (19), real-time occupancy change data from said second degree inner architectural zones (20) to said first degree inner architectural zones (19) and from said first degree inner architectural zones (19) to said first inner architectural zone (18) is used to generate a second data pattern.

In a further embodiment of the present invention, monthly and daily time histories collected through said sensor assemblies (15) are used to operate heating, ventilation, and air conditioning systems in a time-dependent manner in dependence to the specific month of the year, day of the month and time of the day.

In a further embodiment of the present invention, said sensor assemblies (15) have sensor units in the form of occupancy, temperature, humidity and carbon dioxide sensing units. In a further embodiment of the present invention, an inner architectural space (12) is a closed zone with four lateral sides and at least one entry or exit opening.

In a further embodiment of the present invention, each inner architectural space (12) comprises sensor assemblies (15) with occupancy sensors at entry or exit points of said inner architectural space (12).

In a further embodiment of the present invention, any deviation from the first data pattern is taken into account if the amount of deviation falls outside predefined tolerance limits.

In a further embodiment of the present invention, said central station (17) collects real-time data from a plurality of temperature, humidity and carbon dioxide sensor units and evaluates whether any deviation from said first data pattern in a monthly, daily and hourly basis is required.