TECHNICAL FIELD OF THE INVENTION

The present disclosure relates generally to wireless networks and more particularly, to an environmental parameter sensing and alerting system.

BACKGROUND OF THE INVENTION

Environmental monitoring plays a critical role in disaster risk management and mitigation especially in remotely located areas. This then can be effectively achieved via the strategic deployment of wireless sensor networks in different locations of interest. In a particular example, the wireless sensor network can be deployed in a body of water.

Taiwan Patent No. TWI230218B discloses a system and method for water monitoring wherein the monitoring devices are provided at fixed locations to monitor the depth and flow speed of a river. Since the monitoring devices are deployed in fixed locations, there can be problems in modularity or versatility of the system.

China Patent No. CN1180161A deploys a method and device for measuring river channel section fixed-point current speed. This patent measures water velocity via an underwater system that is wired connected to a shore controller. Due to the underwater deployment of the sensors, the most efficient communications are only through wired or cabling systems. The use of wireless communications in this application will only risk data loss through attenuation.

France Patent No. FR2865802A1 discloses a device that would measure the depth of a river by taking pictures of a fixed vertical scale partially submerged in a river that would then be examined later to view the measurement of that time. This method relies on image processing techniques which can be susceptible to errors introduced to the pictures or image data.

US Patent No. US9514632B2 provides a system and method for disseminating emergency information generated from sensors connected in emergency notification devices. The system only focuses on the transmission of emergency signals to notification devices. This invention then proposes a wireless sensor network for data monitoring and acquisition which aims to improve and solve the problems of the prior art. This wireless sensor network is designed to be portable, interoperable, and modular which allows the addition of new sensor nodes for gathering data at multiple points. This invention utilizes a modulation technique for long range communications. Moreover, the invention proposes the use of light detection and ranging sensor, and other sensing devices to measure morphology data of different bodies of water, both static and non-static.

BRIEF DESCRIPTION OF THE DRAWINGS

Some examples of the system will be described in the following by way of example only, and with reference to the accompanying figures, in which

FIG. 1 is a block diagram of a basic wireless sensor network configuration in accordance with an embodiment of the invention;

FIG. 2 is a block diagram of a wireless sensor network for data monitoring and alerting system in accordance with an embodiment of the invention;

FIG. 3 is an expanded block diagram of a wireless sensor network for data monitoring and alerting system in accordance with an embodiment of the invention;

FIG. 4 is a block diagram of interconnected wireless sensor networks for data monitoring and alerting system in accordance with an embodiment of the invention;

FIG. 5 shows a network topology of a wireless sensor network according to the embodiments of this invention; and

FIG. 6 illustrates a flowchart of a method for data monitoring and acquisition for a wireless sensor network. SUMMARY OF THE INVENTION

It is an object of the present invention to provide a wireless sensor network for data monitoring and acquisition. The wireless sensor network for data monitoring and acquisition comprises an at least one central node; an at least one sensor node wirelessly connected to the at least one central node; an at least one remote node wirelessly connected to the at least one central node; and an at least one alert system wirelessly connected to the at least one central node.

The at least one central node comprises a first communications unit for communicating with the at least one sensor node, a first memory device for storing data, a first processing unit for processing the stored data, an alert device for sending one or more alert signals to the at least one alert system if the stored data exceeds a threshold value, and a first interface for displaying data.

The sensor node comprises one or more sensors for measuring at least one sensor data, a second memory device for storing the measured sensor data, a second processing unit for processing the stored sensor data, a second communications unit for communicating with another sensor node or the at least one central node, and an interface for displaying the stored sensor data.

The sensor data is one of water flow data, water level data, proximity data, topography data, bathymetry data, and survey data.

The remote node receives an alert signal from the central node if an at least one sensor node acquires an at least one sensor data that is outside of a predefined range.

The at least one central node of the wireless sensor network for data monitoring and acquisition is connected to at least one cloud service or remote server.

Accordingly, the present invention also provides a method for data monitoring and acquisition for a wireless sensor network comprises: deploying an at least one sensor node, an at least one central node, and an at least one alert system; initializing the at least one sensor node, the at least one central node, and the at least one alert system; calibrating the at least one sensor node; acquiring an at least one sensor data via the at least one sensor node; storing the acquired at least one sensor data to a memory device; transmitting the stored at least one sensor data to the at least one central node; receiving the at least one transmitted sensor data via the at least one central node; processing the received at least one sensor data via the at least one central node; determining if the processed at least one sensor data indicates an emergency event via the at least one central node; transmitting an at least one alert signal to the at least one alert system if the processed data indicates the emergency event via the at least one central node; and receiving the transmitted at least one alert signal via the at least one alert system.

The method for data monitoring and acquisition for a wireless sensor network further comprises a step of sending an at least one feedback signal to the at least one central node via the at least one alert system. The at least one feedback signal can be an acknowledgment (ACK) signal and/or a negative acknowledgment (NACK) signal. The at least one feedback signal can also be control signals used to actuate an at least one actuator connected to the sensor nodes.

DETAILED DESCRIPTION OF THE INVENTION

Various examples will now be described more fully with reference to the accompanying drawings in which some examples are illustrated. In the figures, the thicknesses of lines, layers and/or regions may be exaggerated for clarity.

FIG. 1 is a block diagram of a basic wireless sensor network configuration in accordance with an embodiment of the invention. The wireless sensor network comprises an at least one central node 100, a sensor node 1 101, a sensor node 2 102, an alert system 103, and a cloud or remote server 104. The central node 100 wirelessly communicates with the sensor node 1 101, the sensor node 2 102, the alert system 103, and the cloud or remote server 104 in a bidirectional manner. It is conceivable that the central node 100, the sensor nodes 101, 102, and the alert system 103 are deployed in separate physical locations or geographical areas. The cloud or remote server 104 is construed as a server, a cloud server, a cloud application, a web server, a remote database, or any processing or storage device which can be accessed wirelessly. Preferably, the cloud or remote server 104 communicates with the alert system 103 or with an at least one notification platform or device. The sensor node can be a plurality of nodes that are deployed in predetermined locations. The sensor nodes can communicate with each other via wireless communication protocols. In some events, some sensor nodes can be coupled in a wired connection if deployed in proximity with each other.

According to the embodiments, the central node 100 receives data from the sensor nodes 101, 102. The central node 100 processes the data and determines if the data exceeds an allowable threshold value. If the data exceeds an allowable threshold value, then the central node 100 sends an alert signal to at least one alert system.

The wireless sensor network, in accordance with this invention, gathers morphology data or data on water flow, water level, distance from one point to another on the surface, survey data, and depth of bodies of water wherein the bodies of water can be static or dynamic. Static bodies of water can be a lake while dynamic bodies of water include rivers. It is also conceivable that the wireless sensor network is also deployable in any body of water.

Preferably, the wireless sensor network is designed to be modular and portable. The modularity allows the addition of new sensor nodes to the wireless sensor network at any time. The wireless sensor network automatically sets up the communication links between the original sensor nodes, the newly added sensor nodes, and to one or more central nodes. The sensor nodes and the central nodes are preferred to be portable to be easily deployable in different locations. The wireless sensor network can also be deployed or installed for standalone use.

FIG. 2 is a block diagram of a wireless sensor network for data monitoring and alerting system in accordance with an embodiment of the invention. A central unit 200 acts as a central node or local server that communicates with sensor nodes and the alert system 103 and cloud or remote server 104. The sensor nodes are the water flow and level encoder (WaFLE) unit 201 and the automated river morphology survey (ARMS) unit 202. The water flow and level encoder (WaFLE) unit 201 and the automated river morphology survey (ARMS) unit 202 are deployed in a monitored location. The sensor nodes can have static or dynamic locations. The sensor nodes having static locations are stationary deployed in specific location. The dynamic sensor nodes can be equipped on-board a moving device or apparatus. The moving device can be a robot, an autonomous or unmanned vehicle, remote controlled vehicle, a manned vehicle, a flying drone, a land rover, buoys, boats, ships, floatation devices, submersible vessels, or any vehicle capable of moving or changing locations. In another embodiment, the at least one sensor node or the water flow and level encoder (WaFLE) unit 201 or the automated river morphology survey (ARMS) unit 202 can be equipped with an at least one actuator or end effector such as but is not limited to a robotic arm, a motor, a control system, a switch, a water valve, a heating device, a cooling device, or combinations thereof.

In a preferred embodiment, the central unit 200 receives the data from the water flow and level encoder (WaFLE) unit 201 and the automated river morphology survey (ARMS) unit 202. The central unit 200 comprises a long range (LoRa) transceiver, a microcontroller, and an interface. The long range (LoRa) transceiver is used to communicate with the sensor nodes such as the water flow and level encoder (WaFLE) unit 201 and the automated river morphology survey (ARMS) unit 202. The long range (LoRa) transceiver is connected to the microcontroller for processing the received data from the sensor nodes 201, 202. The received data are then displayed in an interface of the central unit 200. The interface of the central unit 200 comprises a display panel for showing the received data and at least one button for powering on or turning off the central unit 200. The interface of the central unit

200 may further comprise selection buttons to allow a user to select the data to be displayed in the display panel or perform other actions on the central unit 200.

In an embodiment of the present disclosure, the water flow and level encoder (WaFLE) unit

201 acquires water flow data and water level data. The water flow and level encoder (WaFLE) unit 201 stores the acquired data to a memory device and transmits the data to the central unit 200. Preferably, the water flow and level encoder (WaFLE) unit 201 comprises a microcontroller, a light detection and ranging (LIDAR) sensor, an accelerometer module, a memory device, an anemometer, a long range (LoRa) transceiver, and an interface.

In an embodiment of the present disclosure, the automated river morphology survey (ARMS) unit 202 acquires data such as but is not limited to the length, width, or depth of a body of water. The acquired data is stored in a memory device and is then transmitted to a central unit 200. Preferably, the automated river morphology survey (ARMS) unit 202 comprises a microcontroller, a light detection and ranging (LIDAR) sensor, an accelerometer module, a display module, a memory device, a light amplification by stimulated emission or radiation (LASER) device, a scope, a long range (LoRa) transceiver, and an interface. The interface of the automated river morphology survey (ARMS) unit 202 comprises a display panel for showing the acquired data from the light detection and ranging (Lidar) sensor and the accelerometer module.

In a preferred embodiment, a light detection and ranging (LIDAR) sensor is a remote sensing method using light to generate three-dimensional information of a surface's characteristics. The light detection and ranging (LIDAR) sensor obtain the full width of a freshwater body. The light detection and ranging (LIDAR) sensor comprise a light amplification by stimulated emission or radiation (LASER) device, a scanner, and a global positioning system (GPS) receiver. It is conceivable that the light detection and ranging (LIDAR) sensor can be a topographic type or a bathymetric type. The bathymetric type of Lidar, or a submarine topography type, as used in this invention can map or scan the depths and shape of an underwater terrain. The topographic type of Lidar can also be used herein for scanning overland terrains such as but is not limited to elevations, land contours, depth, slope, and terrain features' orientations. In some embodiments, the light detection and ranging (Lidar) sensor can be used with a hydrography device to measure the characteristics of water such as but is not limited to tides, water currents, waves, salinity, turbidity, and water chemistry.

In the context of the present disclosure, an accelerometer module can be any device used to measure vibration, static acceleration, or dynamic acceleration of an object. The accelerometer module can be a vibration sensor, a piezoelectric accelerometer, a low impedance accelerometer or a high impedance accelerometer.

According to the embodiments, an anemometer is any device used to measure speed and direction of wind or water flow. The anemometer can be a velocity anemometer or a pressure anemometer which includes but is not limited to cup anemometers, vane anemometers, hotwire anemometers, laser doppler anemometer, ultrasonic anemometer, acoustic resonance anemometers, ping-pong ball anemometer, plate anemometer, tube anemometer, or pitot tube anemometer.

In another preferred embodiment, a long range (LoRa) transceiver is a transmitting/receiving device that uses spread-spectrum modulation or long range (LoRa) modulation technique for radio frequency (RF) signals. Typically, LoRa modulation is used for low-power wide area networks (LPWANs) which includes the wireless sensor networks as claimed by this invention. Preferably, the wireless sensor network of this invention which uses LoRa modulation has a communications range of up to 20 kilometers. It is also preferred that the wireless sensor network employing LoRa modulation has a star-topology wherein the sensor nodes are connected to a central node. However, the wireless sensor network in accordance with the embodiments of this invention may also use any type of network topology such as but is not limited to bus topology, ring topology, star topology, mesh topology, tree topology, hierarchal topology, or combinations thereof. Preferably, the bandwidth used by the wireless sensor, in accordance with this invention, is between 100 KHz and 600 KHz for both the uplink channel and the downlink channel.

In yet another preferred embodiment, a light amplification by stimulated emission or radiation (LASER) device is any device that emits light via optical amplification based on the stimulated emission of electromagnetic (EM) radiation. Preferably, the laser as used herein is a device for measuring distance and velocity. In another aspect, the laser may also be used as a guiding device along with a scope, a telescopic sight, or an optical sighting device. The laser and the optical sighting device may assist in accurate data collection or aid a user or human operator in the use of the sensor nodes.

FIG. 3 is an expanded block diagram of a wireless sensor network for data monitoring and alerting system in accordance with an embodiment of the invention. The central unit 100 is wirelessly connected to a water flow and level encoder (WaFLE) unit 201 and to an automated river morphology survey (ARMS) unit 202. The central unit 100 comprises a communications unit 1 300, a processing unit 1 301, a memory device 1 302, an interface 1 304, and a power supply 1 305. The central unit 100 can further comprise a sensor module (not shown) for measuring the internal status or node status of the central unit. The water flow and level encoder (WaFLE) unit 201 comprises a sensor module 2 306, a processing unit 2 307, a memory device 2 308, a communications unit 2 309, an interface 2 310, and a power supply

2 311. The automated river morphology survey (ARMS) unit 202 comprises a sensor module

3 312, a processing unit 3 313, a memory device 3 314, a communications unit 3 315, an interface 3 316, and a power supply 3 317.

The water flow and level encoder (WaFLE) unit 201 can communicate with the automated river morphology survey (ARMS) unit 202. In this case, the units 201, 202 passes data between each other, wherein the data can be indicative of the unit's internal parameters such as but is not limited to battery level, location data, operating temperature, and network status. In an embodiment of the present disclosure, the central node 100 is any hardware device capable of processing data, issuing instructions, or executing calculations. The central node can be a microprocessor or microcontroller such as but is not limited to a laptop, personal computer, desktop computer, a local server, a dedicated server, a sink node, or a gateway.

In some embodiments, the communications units 300, 309, 315 preferably enables communication with other sensor nodes, central or local server, or a remote server. The communications units 300, 309, 315 can be any transmitter, receiver, or transceiver used for long range (LoRa) modulation, radio frequency (RF), wireless fidelity (Wi-Fi), Bluetooth, infrared, near field communication (NFC), visible light communication, microwave communication, satellite communication, Li-Fi, WiMax, ZigBee, cellular communication, code division multiple access (CDMA), 2G, global system for mobiles (GSM), 3G, 4G, long term evolution (LTE), long term evolution advanced (LTE-advanced), 5G, 5.5G, 6G, any other wireless communications protocol, or a combination of thereof.

In the context of the present disclosure, the processing units 301, 307, 313 can be any microcontroller, microprocessor, or any hardware device capable of processing data, issuing instructions, or executing calculations. Preferably, the processing units 307, 313 that are used in the deployed sensor nodes are low-powered or consumes less power than the processing unit 301 used in the central unit 100. Preferably, the processing units 307, 313 that are used in the deployed sensor nodes have an operating voltage between 5 volts to 24 volts which can be provided by a battery, or a solar panel coupled to the sensor node.

According to the embodiments, the memory devices 302, 308, 314 can be any medium or mechanism for storing or transmitting information in a form readable by a machine or computer. The memory device can have a primary memory device and/or a secondary memory device as a backup storage device. The memory device can be a read only memory (ROM), random access memory (RAM), magnetic disk storage media, hard disk storage, optical storage media, flash memory devices, universal serial bus (USB) drive, secure digital (SD) card, memory chip, or a combination thereof.

In another preferred embodiment, the interfaces 304, 310, 316 can be an input device, an input/output device or a display/input device which may include simple analog buttons, a system of switches, digital display, liquid crystal display (LCD), light emitting diode (LED) display, or a multi-point touch input screen. The interfaces 304, 310, 316 can be used to display real time values of the LIDAR sensor and the accelerometer sensors. The central unit's 100 interface 304 can also display incoming data from the water flow and level encoder (WaFLE) unit 201, automated river morphology survey (ARMS) unit 202, cloud or remote server 104, sensor module, another central node, or from any sensor node.

In yet another preferred embodiment, the power supply 305, 311, 317 can be an alternating current (AC) power supply or a direct current (DC) power supply that provides power to the central unit 100 and to the sensor nodes. Preferably, the power supply 305 in the central unit is an alternating current (AC) power supply if the power is readily available in an electrical outlet or mains. In such cases, the supplied power is converted from AC to DC. It is also preferred that a secondary power supply is provided as a backup. The secondary power supply is a battery or any energy storage device. The power supplies 311, 317 that are used in the deployed sensor nodes are mostly direct current (DC) power supplies which can supply power from a plurality of batteries, solar panels, wind power, hydroelectric, other alternative sources of energy, or from any energy storage device. A secondary or backup power supply or power source is also preferred especially for monitoring critical areas.

According to the preferred embodiments, the alert system 103 is configured to receive one or more emergency signals, alert signals, notifications, status, messages, or any data useful to a user. The alert system 103 can also send an acknowledgement data, emergency signals, alert signals, SOS, notifications, status, messages, or any data useful to a user, can be any transmitter, receiver, or transceiver used for long range (LoRa) modulation, radio frequency (RF), wireless fidelity (Wi-Fi), Bluetooth, infrared, near field communication (NFC), visible light communication, microwave communication, satellite communication, Li-Fi, WiMax, ZigBee, cellular communication, code division multiple access (CDMA), 2G, global system for mobiles (GSM), 3G, 4G, long term evolution (LTE), long term evolution advanced (LTE-advanced), 5G, 5.5G, 6G, any other wireless communications protocol, or a combination of thereof. It is conceivable that the alert system 103 is a handheld device, a mobile phone, a smart phone, a personal data assistant (PDA), a tablet, a wearable device, a laptop, personal computer, desktop computer, a local server, a dedicated server, a sink node, or a gateway.

According to a further aspect, the cloud or remote server 104 can be a remotely available complex processing unit that can utilize one or more servers, databases, computers, microcontrollers, microprocessors, or any hardware device capable of processing data, issuing instructions, or executing calculations. It is conceivable that the cloud or remote server 104 can perform parallel computing if complex data, analysis, or decision is required. The cloud or remote server 104 can be accessed via any communications protocol such as but is not limited to long range (LoRa) modulation, radio frequency (RF), wireless fidelity (Wi-Fi), fiber optics, wired communications media, Bluetooth, infrared, near field communication (NFC), visible light communication, microwave communication, satellite communication, Li- Fi, WiMax, ZigBee, cellular communication, code division multiple access (CDMA), 2G, global system for mobiles (GSM), 3G, 4G, long term evolution (LTE), long term evolution advanced (LTE-advanced), 5G, 5.5G, 6G, or a combination of thereof.

According to a yet further aspect, the sensor modules 306, 312 can measure sensor data, environment data or morphology data, and network information. The sensor data can be calibration data, operating temperature, and performance data. The environment data or morphology data may include at least one of the sensor node's internal temperature, sensor node's internal humidity, outdoor temperature, outdoor humidity, climate data, bathymetry data, geographical data, survey data, air quality data, anemometer data, water quality data, water flow data, water level data, accelerometer data, proximity data, water turbidity, pH level, soil moisture data, light intensity data, ambient light data, hazardous waste data, radiation data, electromagnetic radiation data, or sound data. The network information can be network load, network status data, message status data, received signal strength indicator (RSSI) data, or network attenuation data.

According to another embodiment, the sensor module can acquire data in real-time or in predefined time intervals. The sensor module may compile the acquired sensor data in a specific time frame and get the sensor data average before transmitting the sensor data to a central node or to another sensor node.

FIG. 4 is a block diagram of interconnected wireless sensor networks for data monitoring and alerting system in accordance with an embodiment of the invention. The block diagram shows two wireless sensor networks. A first wireless sensor network can be deployed in a geographical location, for example in along a coastal region or a body of water such as a river or lake. The first wireless sensor network comprises central node A 400 wherein central node A 400 communicates with sensor node 1-A 405, sensor node 2-A 406, and sensor node N-A 407. The sensor nodes 405, 406, 407 are deployed within the communication range of central node A 400. The sensor nodes 405, 406, 407 can be adjacent or near with each other. The sensor nodes 405, 406, 407 may also be deployed far from each other as long as the sensor node's distance is within the communication range of the central node. A second wireless sensor network can be deployed in a different geographical location that is still within the communication range of the central node A 400. The second wireless sensor network can be deployed in a mountainous area, for example. The second wireless sensor network comprises a central node B 401 wherein the central node B 401 is wirelessly connected to sensor node 1-B 408, sensor node 2-B 409, and sensor node N-B 410. The sensor nodes 408, 409, 410 may acquire sensor data for the parameters of the area being monitored. The sensor node's sensing modules depend on the area being monitored. If, for example, the sensor node is deployed in a mountainous area, then the sensor node may have modules for sensing temperature, humidity, or fire.

The wireless sensor network, according to the embodiments of this invention, is scalable. Additional sensor nodes can be added any time after the establishment or deployment of the wireless sensor network. In FIG. 4, a sensor node X-B 411 is added to the wireless sensor network. Preferably, the added sensor node connects automatically to the central node and to at least one sensor node of the wireless sensor network. In an event which requires a sensor node to be deployed outside the central node's communication range, the sensor node must be within the communication range of another sensor node with direct connection to the central node. For example, a sensor node 3-B 412 is added to the wireless sensor network. The sensor node 3-B 412 must maintain a communication link with at least one existing sensor node wherein sensor node 3-B 412 connects to either or both sensor node 1-B 408 and sensor node 2-B 409. The sensor node 3-B 412 can then communicate with the central node B 401 via the communication link with either sensor node 1-B 408 and sensor node 2-B 409. The sensor nodes can perform this token passing wherein packets of data are passed from a source node to a destination node wherein any sensor node or the central node can be the source node or a destination node. To achieve the token passing, according to the preferred embodiments, the wireless sensor network further comprises a data addressing system. The data addressing system may include appending address headers on the data sent by the sensor nodes. For example, the data from a source node- sensor node 1-B 408 may have a header "1-B" in a form of a string and a destination address such as "2-B" to indicate the destination of the data within the wireless sensor network.

In the context of the present disclosure, a central node A 400 communicates bidirectionally with a central node B 401, a cloud or remote server 402, an alert system 2 403, and an alert system 1 404. The central node A 400 can exchange data with the central node B 401. The data can be sensor data, environment data or morphology data, and network information. Both central node A 400 and central node B 401 can send alert signals or notifications to either alert system 2403 or alert system 1404. Both central node A 400 and central node B 401 can also send data to a cloud or remote server 402 for data processing. In some events, the cloud or remote server 402 can identify if the data are indicative of an imminent danger or emergency situations. The cloud or remote server 402 may then have advanced processing means such as intelligent systems, predictive algorithm, artificial neural networks, fuzzy logic, genetic algorithm, machine learning, deep learning, or combinations thereof. If the cloud or remote server 402 identifies or predicts an imminent danger or emergency situations, then the cloud or remote server 402 may send notification or emergency signals to central node A 400, central node B 401, or directly to alert system 2403 and/or an alert system 1404.

FIG. 5 shows a network topology of a wireless sensor network according to the embodiments of this invention. In the presented network topology, the central node A 400 is located outside the communication range of central node B 401. Central node A 400 may be located, for example, 25 kilometers away from central node B 401. Central node A 400 may communicate with central node B 401 through a cloud or remote server 402. The central node A 400 may send alert signals or notifications to alert system 2 404 which is in the communication range of central node B 401.

FIG. 6 illustrates a flowchart of the method for data monitoring and acquisition for a wireless sensor network. The method for data monitoring and acquisition for a wireless sensor network comprises deploying an at least one sensor node, an at least one central node, and an at least one alert system (step 600); initializing the at least one sensor node, the at least one central node, and the at least one alert system (step 601); calibrating the at least one sensor node (step 602); acquiring an at least one sensor data via the at least one sensor node (step 603); storing the acquired at least one sensor data to a memory device (step 604); transmitting the stored at least one sensor data to the at least one central node (step 605); receiving the at least one transmitted sensor data via the at least one central node (step 606); processing the received at least one sensor data via the at least one central node (step 607); determining if the processed at least one sensor data indicates an emergency event via the at least one central node (step 608); transmitting an at least one alert signal to the at least one alert system if the processed data indicates the emergency event via the at least one central node (step 609); and receiving the transmitted at least one alert signal via the at least one alert system (step 610).

In some embodiments, the method for data monitoring and acquisition for a wireless sensor network further comprises sending an at least one feedback signal to the at least one central node via the at least one alert system.

In some embodiments, the deployment of an at least one sensor node, an at least one central node, and an at least one alert system (step 600) comprises a deployment algorithm for maximizing the coverage area to be monitored. The deployment algorithm calculates the distances between the sensor nodes and the central nodes. The calculated distance is then optimized to achieve efficient routing of data based on the sensor nodes' battery capacity and rate of data transmission.

In the context of the present disclosure, the calibration of the at least one sensor node (step 602) comprises a step of checking the accuracy of the sensors connected to the sensor node by initially measuring an at least one sensor data and comparing the measured sensor data to a range of predefined normal sensor data range. If the initially measured sensor data is outside the predefined normal sensor data range, then the sensor node undergoes another initialization step. If the sensor node encounters another discrepancy in the initially measured sensor data, then the sensor node emits a warning signal via an at least one visual indicator such as a light emitting device (LED). The sensor node also sends a warning signal to a nearest central node to notify a user or a human operator of a sensor error.

In another preferred embodiment, the calibration of the at least one sensor node (step 602) comprises a self-debugging algorithm for correcting errors on the sensor node's processing unit.

According to the embodiments, the storage of the acquired at least one sensor data to a memory device (step 604) comprises a step of storing the acquired at least one sensor data to a secondary or back-up memory device wherein the secondary or back-up memory device is connected to the sensor node.

In another preferred embodiment, the transmission of the stored at least one sensor data to the at least one central node (step 605) uses an addressing system wherein the transmitted data comprises an address header to determine the destination of the transmitted data. In some embodiments, the transmission of the stored sensor data can use two or more channel frequencies. The sensor nodes can use a unique uplink frequency and/or downlink frequency to communicate with the central node. The uplink frequency and the downlink frequency can be between 100 KHz and 600 KHz. The uplink frequency and the downlink frequency can be identical or different frequencies.

In yet another preferred embodiment, the transmission of the sensor data to an at least one sensor node and/or a central node uses an at least one spreading factor between 1 to 12 and a bit rate between 900 to 28,000 bits per seconds (bps).

According to the preferred embodiments, an at least one sensor node and an at least one central node uses a forward error correction (FEC) method and a coding rate of 4/5 and/or 4/6.

According to a further aspect, the method for data monitoring and acquisition for a wireless sensor network further comprises implementing one or more routing protocols for the efficient communication between an at least one sensor node and an at least one central node. The one or more routing protocols can be an Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR), Optimized Link State Routing Protocol (OLSR), or a combination thereof.

According to a further aspect, the method for data monitoring and acquisition for a wireless sensor network further comprises transmitting and/or receiving an at least one acknowledgment (ACK) signal and/or an at least one negative acknowledgment (NACK) signal between an at least one sensor node and an at least one central node.