CN115997105A

CN115997105A - Fresh water morphology information collection system

Info

Publication number: CN115997105A
Application number: CN202180002450.2A
Authority: CN
Inventors: 乔·雷尔·L·阿德尔; 汉斯·C·冈萨加; 乔舒亚·肯培斯; 尼科·L·奎明思; 邓恩·詹德·M·阿尔帕; 以色雷尔·约翰·D·佩纳洛萨; 安杰洛·莱恩·S·多琳娜; 尼尔·达斯廷·本尼迪克特·A·阿格纳; 温齐·加布帕
Original assignee: Philippine Science High School East Visayas Campus
Current assignee: Philippine Science High School East Visayas Campus
Priority date: 2021-08-19
Filing date: 2021-08-23
Publication date: 2023-04-21
Also published as: WO2023022612A1

Abstract

The present disclosure relates to wireless sensor networks for data monitoring and acquisition. The wireless sensor network includes at least one central node, at least one sensor node, at least one remote node, and at least one alarm system. The sensor node transmits and receives sensor data from the central node. The central node processes the received sensor data and determines whether the received data exceeds a threshold level. If the received data exceeds a threshold level, the central node sends an alert to at least one alert system. The central node may also communicate with at least one remote node for further data storage and data processing.

Description

Fresh water morphology information collection system

Technical Field

The present disclosure relates generally to wireless networks, and more particularly to environmental parameter sensing and alarm systems.

Background

Environmental monitoring plays a vital role in disaster risk management and mitigation, especially in remote areas. This can be effectively achieved by strategically deploying wireless sensor networks at different locations of interest. In certain examples, the wireless sensor network may be deployed in a body of water.

Taiwan patent No. TWI230218B discloses a system and method for water monitoring wherein monitoring devices are provided at fixed locations to monitor the depth and flow rate of a river. Because the monitoring device is deployed in a fixed location, there may be problems in terms of modularity or versatility of the system.

Chinese patent CN1180161a deploys a method and apparatus for measuring river section setpoint flow rates. This patent measures the water flow rate through an underwater system wired to an onshore controller. Because the sensors are deployed underwater, the most efficient communication can only be through wired or cable systems. The use of wireless communication in such applications only risks attenuation-induced data loss.

French patent FR2865802A1 discloses a device that will measure the depth of a river by taking photographs of a fixed vertical scale partially submerged in the river and later checking these photographs to see the measurements at the time. This method relies on image processing techniques that are susceptible to errors introduced into the photograph or image data.

US patent 9514632B2 provides a system and method for disseminating emergency information generated by sensors connected in an emergency notification device. The system focuses only on transmitting emergency signals to the notification device.

The present invention thus proposes a wireless sensor network for data monitoring and acquisition, which aims to improve and solve the problems of the prior art. The wireless sensor network is designed to be portable, interoperable, and modular, which enables the addition of new sensor nodes to collect data at multiple points. The present invention uses modulation techniques for telecommunications. Furthermore, the present invention proposes to use light detection and ranging sensors and other sensing means to measure morphological data of different bodies of water both static and non-static.

Drawings

Some examples of the system will be described below, by way of example only, with reference to the accompanying drawings, in which:

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

FIG. 2 is a block diagram of a wireless sensor network for a data monitoring and alert system according to an embodiment of the present invention;

FIG. 3 is an expanded block diagram of a wireless sensor network for a data monitoring and alert system according to an embodiment of the present invention;

FIG. 4 is a block diagram of an interconnected wireless sensor network for a data monitoring and alert system according to an embodiment of the present invention;

FIG. 5 shows a network topology of a wireless sensor network according to an embodiment of the present invention; and

fig. 6 shows a flow chart of a method for data monitoring and acquisition of a wireless sensor network.

Disclosure of Invention

The invention aims to provide a wireless sensor network for data monitoring and acquisition. The wireless sensor network for data monitoring and acquisition comprises: at least one central node; at least one sensor node wirelessly connected to the at least one central node; at least one remote node wirelessly connected to the at least one central node; and at least one alarm system wirelessly connected to the at least one central node.

The at least one central node comprises: the system comprises a first communication unit for communicating with at least one sensor node, first storage means for storing data, a first processing unit for processing the stored data, alarm means for sending one or more alarm signals to at least one alarm system when the stored data exceeds a threshold value, and a first interface for displaying the data.

The sensor node includes: one or more sensors for measuring at least one sensor data, a second storage means for storing the measured sensor data, a second processing unit for processing the stored sensor data, a second communication unit for communicating with another sensor node or 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, terrain data, sounding data, and survey data.

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

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.

Correspondingly, the invention also provides a method for monitoring and collecting the data of the wireless sensor network, which comprises the following steps:

-deploying at least one sensor node, at least one central node and at least one alarm system;

-initializing at least one sensor node, at least one central node and at least one alarm system; calibrating the at least one sensor node;

-acquiring at least one sensor data by at least one sensor node;

-storing the acquired at least one sensor data to a storage device;

-transmitting the stored at least one sensor data to at least one central node;

-receiving, by at least one central node, at least one transmitted sensor data;

-processing, by at least one central node, the received at least one sensor data;

-determining, by the at least one central node, whether the processed at least one sensor data is indicative of an emergency event;

-transmitting, by the at least one central node, at least one alarm signal to the at least one alarm system if the processed data indicates an emergency event; and

-receiving the transmitted at least one alarm signal by means of at least one alarm system.

The method for data monitoring and acquisition of a wireless sensor network further comprises the step of transmitting at least one feedback signal to at least one central node through at least one alarm system. The at least one feedback signal may be an Acknowledgement (ACK) signal and/or a Negative Acknowledgement (NACK) signal. The at least one feedback signal may also be a control signal for actuating at least one actuator connected to the sensor node.

Detailed Description

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

Fig. 1 is a block diagram of a basic wireless sensor network configuration according to an embodiment of the present invention. The wireless sensor network comprises at least one central node 100, sensor nodes 1, 101, sensor nodes 2, 102, an alarm system 103, and a cloud or remote server 104. The central node 100 communicates wirelessly in a bi-directional manner with the

sensor nodes

1, 101, 102, alarm system 103, and cloud or remote server 104. It is envisioned that the central node 100, the

sensor nodes

101, 102, and the alarm system 103 are deployed in separate physical locations or geographic areas. Cloud or remote server 104 is interpreted as a server, cloud application, web server, remote database, or any processing or storage device that can be accessed wirelessly. Preferably, the cloud or remote server 104 communicates with the alert system 103 or with at least one notification platform or device. The sensor node may be a plurality of nodes deployed at predetermined locations. The sensor nodes may communicate with each other via a wireless communication protocol. In some cases, some sensor nodes may be coupled by wired connections if deployed close to each other.

According to an embodiment, the central node 100 receives data from the

sensor nodes

101, 102. The central node 100 processes the data and determines whether the data exceeds an allowable threshold. If the data exceeds the allowable threshold, the central node 100 transmits an alarm signal to at least one alarm system.

According to the invention, the wireless sensor network collects morphological data or data about the water flow, water level, distance from one point to another on the water surface, survey data, and depth of the body of water, which may be static or dynamic. The static body of water may be a lake and the dynamic body of water may comprise a river. It is also envisioned that the wireless sensor network may be deployed in any body of water.

Preferably, the wireless sensor network is designed to be modular and portable. The modularization enables new sensor nodes to be added to the wireless sensor network at any time. The wireless sensor network automatically establishes communication links between the original sensor nodes, the newly added sensor nodes, and communication links to one or more central nodes. The sensor nodes and the central node are preferably portable for easy deployment at different locations. The wireless sensor network may also be deployed or installed for independent use.

Fig. 2 is a block diagram of a wireless sensor network for a data monitoring and alert system according to an embodiment of the present invention. The central unit 200 acts as a central node or local server in communication with the sensor nodes and alarm system 103 and the cloud or remote server 104. The sensor nodes are a water flow and level encoder (WaFLE) unit 201 and an Automatic River Morphology Survey (ARMS) unit 202. A water flow and level encoder (waflex) unit 201 and an Automatic River Morphology Survey (ARMS) unit 202 are deployed at the monitored location. The sensor nodes may have static or dynamic locations. Sensor nodes with static locations are fixedly deployed at specific locations. The dynamic sensor node may be mounted on a mobile device or apparatus. The mobile device may be a robot, autonomous or unmanned vehicle, remote vehicle, manned vehicle, flying drone, off-road vehicle, buoy, boat, ship, floatation device, submersible, or any vehicle capable of moving or changing position.

In another embodiment, the at least one sensor node or water flow and level encoder (WaFLE) unit 201 or Automatic River Morphology Survey (ARMS) unit 202 may be equipped with at least one actuator or end effector, such as, but not limited to, a robotic arm, a motor, a control system, a switch, a water valve, a heating device, a cooling device, or a combination thereof.

In the preferred embodiment, the central unit 200 receives data from a water flow and level encoder (WaFLE) unit 201 and an Automatic River Morphology Survey (ARMS) unit 202. The central unit 200 includes a remote (LoRa) transceiver, a microcontroller, and an interface. A remote (LoRa) transceiver is used to communicate with sensor nodes such as a water flow and level encoder (waflex) unit 201 and an Automatic River Morphology Survey (ARMS) unit 202. A remote (LoRa) transceiver is connected to the microcontroller for processing data received from the

sensor nodes

201, 202. The received data is then displayed in the interface of the central unit 200. The interface of the central unit 200 includes a display panel for displaying the received data and at least one button for turning on or off the central unit 200. The interface of the central unit 200 may also include selection buttons to allow a user to select data to be displayed in the display panel or perform other actions on the central unit 200.

In an embodiment of the present disclosure, a water flow and water level encoder (waflex) unit 201 obtains water flow data and water level data. The water flow and level encoder (waflex) unit 201 stores the acquired data to a storage device and transmits the data to the central unit 200. Preferably, the water flow and level encoder (WaFLE) unit 201 includes a microcontroller, light detection and ranging (LIDAR) sensors, accelerometer modules, storage, anemometers, remote (LoRa) transceivers, and an interface.

In an embodiment of the present disclosure, an Automatic River Morphology Survey (ARMS) unit 202 acquires data such as, but not limited to, the length, width, or depth of a body of water. The acquired data is stored in the storage device and then transmitted to the central unit 200. Preferably, the Automated River Morphology Survey (ARMS) unit 202 includes a microcontroller, light detection and ranging (LIDAR) sensors, accelerometer modules, display modules, storage devices, stimulated emission or radiated Light Amplification (LASER) devices, oscilloscopes, remote (LoRa) transceivers, and interfaces. The interface of the Automatic River Morphology Survey (ARMS) unit 202 includes a display panel for displaying data acquired from light detection and ranging (Lidar) sensors and accelerometer modules.

In a preferred embodiment, light detection and ranging (LIDAR) sensors are remote sensing methods that utilize light to generate three-dimensional information of surface features. Light detection and ranging (LIDAR) sensors acquire the full width of a body of fresh water. Light detection and ranging (LIDAR) sensors include stimulated emission or radiated Light Amplification (LASER) devices, scanners, and Global Positioning System (GPS) receivers. It is envisioned that light detection and ranging (LIDAR) sensors may be of the terrain type or depth-sounding type. Depth-finding or submarine topography Lidar used in the present invention can map or scan the depth and shape of the submarine topography. Terrain Lidar may also be used herein to scan land terrain such as, but not limited to, elevation, land contour, depth, grade, and orientation of terrain features. In some embodiments, light detection and ranging (Lidar) sensors may be used with hydrologic devices to measure characteristics of water, such as, but not limited to, tides, currents, waves, salinity, turbidity, and water chemistry.

In the context of the present disclosure, an accelerometer module may be any device for measuring vibration, static acceleration or dynamic acceleration of an object. The accelerometer module may be a vibration sensor, a piezoelectric accelerometer, a low impedance accelerometer, or a high impedance accelerometer.

According to an embodiment, an anemometer is any device for measuring the speed and direction of wind or water flow. The anemometer may be a speedometer or a pressure anemometer including, but not limited to, a cup anemometer, a blade anemometer, a hot wire anemometer, a laser Doppler anemometer, an ultrasonic anemometer, an acoustic resonance anemometer, a ping-pong ball anemometer, a plate anemometer, a tube anemometer, or a pitot tube anemometer.

In another preferred embodiment, the remote (LoRa) transceiver is a transmitting/receiving device that uses spread spectrum modulation or remote (LoRa) modulation techniques on Radio Frequency (RF) signals. Typically, loRa modulation is used for Low Power Wide Area Networks (LPWANs) including the wireless sensor networks as claimed herein. Preferably, the wireless sensor network of the present invention using LoRa modulation has a communication range of up to 20 km. 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, wireless sensor networks according to embodiments of the present invention may also use any type of network topology, such as, but not limited to, a bus topology, a ring topology, a star topology, a mesh topology, a tree topology, a hierarchical topology, or a combination thereof. Preferably, the wireless sensor uses a bandwidth between 100KHz and 600KHz for both the uplink and downlink channels in accordance with the present invention.

In yet another preferred embodiment, the stimulated emission or radiation Light Amplification (LASER) device is any device that emits light by light amplification based on stimulated emission of Electromagnetic (EM) radiation. Preferably, the laser used herein is a device for measuring distance and speed. In another aspect, the laser may also be used as a guide with an oscilloscope, a telescopic sight, or an optical sighting device. Lasers and optical sighting devices can help accurately collect data or assist a user or operator in using the sensor node.

Fig. 3 is an expanded block diagram of a wireless sensor network for a data monitoring and alert system according to an embodiment of the present invention. The central unit 100 is wirelessly connected to a water flow and level encoder (waflex) unit 201 and an Automatic River Morphology Survey (ARMS) unit 202. The central unit 100 comprises a communication unit 1 300, a processing unit 1 301, a storage device 1 302, an interface 1 304, and a power supply 1 305. The central unit 100 may further include a sensor module (not shown) for measuring an internal state or a node state of the central unit. The water flow and level encoder (waflex) unit 201 comprises a sensor module 2 306, a processing unit 2 307, a storage device 2 308, a communication unit 2 309, an interface 2 310, and a power supply 2 311. The Automatic River Morphology Survey (ARMS) unit 202 comprises a sensor module 3 312, a processing unit 3 313, a storage device 3 314, a communication unit 3 315, an interface 3 316, and a power supply 3 317.

The water flow and level encoder (waflex) unit 201 may communicate with an Automatic River Morphology Survey (ARMS) unit 202. In this case, the

units

201, 202 communicate data between each other, where the data may be indicative of internal parameters of the units such as, but not limited to, battery level, location data, operating temperature, and network status.

In embodiments of the present disclosure, central node 100 is any hardware device capable of processing data, issuing instructions, or performing computations. The central node may be a microprocessor or microcontroller such as, but not limited to, a laptop computer, a personal computer, a desktop computer, a local server, a dedicated server, a sink node, or a gateway.

In some embodiments, the

communication unit

300, 309, 315 is preferably capable of communicating with other sensor nodes, a central or local server or a remote server. The

communication units

300, 309, 315 may be any transmitter, receiver, or transceiver for remote (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 Mobile (GSM), 3G, 4G, long Term Evolution (LTE), long term evolution enhancement (LTE-enhancement), 5G, 5.5G, 6G, any other wireless communication protocol, or a combination thereof.

In the context of the present disclosure, the

processing units

301, 307, 313 may be any microcontroller, microprocessor or any hardware device capable of processing data, issuing instructions or performing calculations. Preferably, the

processing units

307, 313 used in the deployed sensor nodes are low power or consume less power than the processing unit 301 used in the central unit 100. Preferably, the operating voltage of the

processing units

307, 313 used in the deployed sensor nodes is between 5 volts and 24 volts, which may be provided by a battery or a solar panel coupled to the sensor nodes.

According to an embodiment, the

storage devices

302, 308, 314 may be any medium or mechanism for storing or transmitting information in a form readable by a machine or computer. The storage device may have a primary storage device and/or a secondary storage device as a backup storage device. The storage device may be 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) drives, secure Digital (SD) cards, memory chips, or a combination thereof.

In another preferred embodiment, the

interfaces

304, 310, 316 may be input devices, input/output devices, or display/input devices, which may include simple analog buttons, a switching system, a digital display, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, or a multi-touch input screen. The

interfaces

304, 310, 316 may be used to display real time values of the LIDAR sensor and the accelerometer sensor. The interface 304 of the central unit 100 may also display input data from a water flow and level encoder (waflex) unit 201, an Automatic River Morphology Survey (ARMS) unit 202, a cloud or remote server 104, a sensor module, another central node, or from any sensor node.

In yet another preferred embodiment, the

power sources

305, 311, 317 may be Alternating Current (AC) power sources or Direct Current (DC) power sources that provide power to the central unit 100 and 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 a power outlet or mains. In this case, the supplied power is converted from alternating current to direct current. It is also preferred that a secondary power source is provided as a backup. The secondary power source is a battery or any energy storage device. The

power sources

311, 317 used in the deployed sensor nodes are mostly Direct Current (DC) power sources, which may be provided with power from multiple batteries, solar panels, wind power, hydropower, other alternative energy sources, or from any energy storage device. The secondary or backup power source or sources of power are also preferably dedicated to monitoring critical areas.

According to a preferred embodiment, alarm system 103 is configured to receive one or more emergency signals, alarm signals, notifications, status, messages, or any data useful to a user. Alarm system 103 may also send confirmation data, emergency signals, alarm signals, SOS, notifications, status, messages, or any data useful to the user. May be any transmitter, receiver, or transceiver for remote (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 Mobile (GSM), 3G, 4G, long Term Evolution (LTE), long term evolution enhancement (LTE-enhancement), 5G, 5.5G, 6G, any other wireless communication protocol, or a combination thereof. It is envisioned that alert system 103 is a handheld device, mobile phone, smart phone, personal Digital Assistant (PDA), tablet, wearable device, laptop, personal computer, desktop computer, local server, dedicated server, sink node, or gateway.

According to another aspect, cloud or remote server 104 may be a remotely available complex processing unit that may utilize one or more servers, databases, computers, microcontrollers, microprocessors, or any hardware device capable of processing data, issuing instructions, or performing calculations. It is envisioned that cloud or remote server 104 may perform parallel computing if complex data, analysis, or decisions are required. The cloud or remote server 104 may be accessed through any communication protocol such as, but not limited to, remote (LoRa) modulation, radio Frequency (RF), wireless fidelity (Wi-Fi), fiber optics, wired communication 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 Mobile (GSM), 3G, 4G, long Term Evolution (LTE), long term evolution enhancement (LTE-enhancement), 5G, 5.5G, 6G, or a combination thereof.

According to yet another aspect, the

sensor modules

306, 312 may measure sensor data, environmental data, or morphology data, as well as network information. The sensor data may be calibration data, operating temperature and performance data. The environmental or morphological data may include at least one of an internal temperature of the sensor node, an internal humidity of the sensor node, an outdoor temperature, an outdoor humidity, climate data, sounding data, geographic data, survey data, air quality data, anemometer data, water quality data, water flow data, water level data, accelerometer data, proximity data, water turbidity, pH value, soil humidity data, illumination intensity data, ambient light data, hazardous waste data, radiation data, electromagnetic radiation data, or sound data. The network information may be network load, network status data, message status data, received Signal Strength Indication (RSSI) data, or network attenuation data.

According to a further embodiment, the sensor module may acquire data in real time or at predefined time intervals. The sensor module may compile the acquired sensor data over a particular time frame and obtain an average of the sensor data before transmitting the sensor data to the central node or another sensor node.

Fig. 4 is a block diagram of an interconnected wireless sensor network for a data monitoring and alert system according to an embodiment of the present invention. The block diagram shows two wireless sensor networks. The first wireless sensor network may be deployed in a geographic location, for example in a body of water such as a river or lake or along a coastal region. The first wireless sensor network includes a central node a400, wherein the central node a400 communicates with sensor nodes 1-a 405, sensor nodes 2-a406, and sensor nodes N-a 407. The

sensor nodes

405, 406, 407 are deployed within communication range of the central node a 400. The

sensor nodes

405, 406, 407 may be adjacent or near each other. The

sensor nodes

405, 406, 407 may also be deployed remotely from each other, as long as the distance of the sensor nodes is within communication range of the central node. The second wireless sensor network may be deployed at a different geographic location that is still within communication range of the central node a 400. For example, the second wireless sensor network may be deployed in a mountain region. The second wireless sensor network comprises a central node B401, wherein the central node B401 is wirelessly connected to sensor nodes 1-B408, sensor nodes 2-B409 and sensor nodes N-B410. The

sensor nodes

408, 409, 410 may acquire sensor data of parameters of the monitored area. The sensing module of the sensor node depends on the area being monitored. For example, if the sensor node is deployed in a mountain area, the sensor node may have a module for sensing temperature, humidity, or fire.

According to an embodiment of the invention, the wireless sensor network is scalable. Additional sensor nodes may be added at any time after the wireless sensor network is established or deployed. In fig. 4, a sensor node X-B411 is added to the wireless sensor network. Preferably, the added sensor node is automatically connected to the central node and to at least one sensor node of the wireless sensor network. In the case where it is necessary to deploy a sensor node outside the communication range of a central node, the sensor node must be located within the communication range of another sensor node directly connected to the central node. For example, sensor node 3-B412 is added to a wireless sensor network. The sensor node 3-B412 must maintain a communication link with at least one existing sensor node, wherein the sensor node 3-B412 is connected to one or both of the sensor node 1-B408 and the sensor node 2-B409. Sensor node 3-B412 can then communicate with central node B401 over a communication link with sensor node 1-B408 or sensor node 2-B409. The sensor node may perform this token passing, wherein the data packet is passed from the source node to the destination node, wherein any sensor node or central node may be the source node or the destination node. To enable token passing, the wireless sensor network further comprises a data addressing system according to a preferred embodiment. The data addressing system may include an additional address header on the data sent by the sensor node. For example, data from source node-sensor nodes 1-B408 may have a header "1-B" in the form of a string and a destination address such as "2-B" to indicate the destination of the data in the wireless sensor network.

In the context of the present disclosure, the central node a400 is in bi-directional communication with the central node B401, the cloud or remote server 402, the alarm system 2 403, and the alarm system 1 404. Central node a400 may exchange data with central node B401. The data may be sensor data, environmental data or morphological data, as well as network information. Both central node a400 and central node B401 may send alarm signals or notifications to alarm system 2 403 or alarm system 1 404. The central node a400 and the central node B401 may also send data to a cloud or remote server 402 for data processing. In some cases, the cloud or remote server 402 may identify whether the data indicates an urgent hazard or emergency. The cloud or remote server 402 may thus have advanced processing means such as intelligent systems, predictive algorithms, artificial neural networks, fuzzy logic, genetic algorithms, machine learning, deep learning, or a combination thereof. If the cloud or remote server 402 identifies or predicts an imminent danger or emergency, the cloud or remote server 402 may send a notification or emergency signal to the central node a400, the central node B401, or directly to the alarm system 2 403 and/or the alarm system 1 404.

Fig. 5 shows a network topology of a wireless sensor network according to an embodiment of the present invention. In the presented network topology, the central node a400 is located outside the communication range of the central node B401. The central node a400 may be located, for example, 25 kilometers from the central node B401. The central node a400 may communicate with the central node B401 through a cloud or remote server 402. The central node a400 may send an alarm signal or notification to the alarm system 2 404 located within communication range of the central node B401.

Fig. 6 shows a flow chart of a method for data monitoring and acquisition of a wireless sensor network. The method for monitoring and collecting the data of the wireless sensor network comprises the following steps: deploying at least one sensor node, at least one central node, and at least one alarm system (step 600); initializing at least one sensor node, at least one central node, and at least one alarm system (step 601); calibrating the at least one sensor node (step 602); acquiring at least one sensor data by at least one sensor node (step 603); storing the acquired at least one sensor data to a storage device (step 604); transmitting the stored at least one sensor data to at least one central node (step 605); receiving, by the at least one central node, at least one transmitted sensor data (step 606); processing the received at least one sensor data by the at least one central node (step 607); determining, by the at least one central node, whether the processed at least one sensor data indicates an emergency event (step 608); transmitting at least one alert signal to at least one alert system through at least one central node if the processed data indicates an emergency event (step 609); and receiving the transmitted at least one alert signal by the at least one alert system (step 610).

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

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

In the context of the present disclosure, the calibration of the at least one sensor node (step 602) comprises the step of checking the accuracy of the sensor connected to the sensor node by initially measuring the at least one sensor data and comparing the measured sensor data with a predefined normal sensor data range. If the initially measured sensor data is outside the predefined normal sensor data range, the sensor node undergoes a further initialization step. If the sensor node encounters an additional discrepancy in the initially measured sensor data, the sensor node issues a warning signal via at least one visual indicator, such as a Light Emitting Device (LED). The sensor node also sends a warning signal to the nearest central node to inform the user or operator of the sensor error.

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

According to an embodiment, storing the acquired at least one sensor data to a storage device (step 604) comprises the step of storing the acquired at least one sensor data to a secondary or backup storage device, wherein the secondary or backup storage 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 includes an address header to determine the destination of the transmitted data. In some embodiments, the transmission of stored sensor data may use two or more channel frequencies. The sensor node may communicate with the central node using a unique uplink frequency and/or downlink frequency. The uplink and downlink frequencies may be between 100KHz and 600 KHz. The uplink frequency and the downlink frequency may be the same or different frequencies.

In a further preferred embodiment, the transmission of sensor data to the at least one sensor node and/or the central node uses at least one spreading factor between 1 and 12 and a bit rate between 900 and 28000 bits per second (bps).

According to a preferred embodiment, the at least one sensor node and the at least one central node use a Forward Error Correction (FEC) method and a coding rate of 4/5 and/or 4/6.

According to another aspect, the method for data monitoring and acquisition of a wireless sensor network further comprises implementing one or more routing protocols for efficient communication between at least one sensor node and at least one central node. The one or more routing protocols may be an ad hoc network on demand distance vector (AODV), a Dynamic Source Routing (DSR), an optimized link state routing protocol (OLSR), or a combination thereof.

According to another aspect, the method for data monitoring and acquisition of a wireless sensor network further comprises sending and/or receiving at least one Acknowledgement (ACK) signal and/or at least one Negative Acknowledgement (NACK) signal between at least one sensor node and at least one central node.

Claims

1. A wireless sensor network for data monitoring and acquisition, comprising:

at least one central node;

at least one sensor node wirelessly connected to the at least one central node;

at least one remote node wirelessly connected to the at least one central node; and

at least one alarm system wirelessly connected to the at least one central node;

wherein the at least one central node comprises:

a first communication unit for communicating with the at least one sensor node,

a first storage means for storing data,

a first processing unit for processing the stored data,

alarm means for transmitting one or more alarm signals to said at least one alarm system when the stored data exceeds a threshold value, and

a first interface for displaying data;

wherein each sensor node comprises:

one or more sensors for measuring at least one sensor data,

a second storage means for storing the measured sensor data,

a second processing unit for processing the stored sensor data,

a second communication unit for communicating with another sensor node or the at least one central node, and

an interface for displaying the stored sensor data; and is also provided with

Wherein the remote node receives an alarm signal from the at least one central node.

2. The wireless sensor network for data monitoring and acquisition of claim 1, wherein the at least one central node is connected to at least one cloud service or remote server.

3. The wireless sensor network for data monitoring and acquisition of claim 1, wherein the sensor data is one of water flow data, water level data, proximity data, terrain data, and sounding data.

4. A method for data monitoring and acquisition of a wireless sensor network, comprising:

deploying at least one sensor node, at least one central node, and at least one alarm system;

initializing the at least one sensor node, the at least one central node, and the at least one alarm system;

calibrating the at least one sensor node;

acquiring at least one sensor data by the at least one sensor node;

storing the acquired at least one sensor data to a storage device;

transmitting the stored at least one sensor data to the at least one central node;

receiving, by the at least one central node, the transmitted at least one sensor data;

processing, by the at least one central node, the received at least one sensor data;

determining, by the at least one central node, whether the processed at least one sensor data indicates an emergency event;

transmitting, by the at least one central node, at least one alert signal to the at least one alert system if the processed data indicates the emergency event; and

the transmitted at least one alarm signal is received by the at least one alarm system.

5. The method for data monitoring and acquisition of a wireless sensor network of claim 4, wherein the method further comprises sending at least one feedback signal to the at least one central node through the at least one alarm system.