Forest fire early detection system based on wireless sensor network
By combining wireless sensor networks with LoRa and NB-IoT technologies, the real-time and accuracy issues of early detection of forest fires have been resolved, enabling efficient fire early warning in complex forest areas and supporting scientific fire prevention management.
Patent Information
- Application Number
- CN202422525241.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-18
- Publication Date
- 2025-10-28
- Estimated Expiration
- 2034-10-18
AI Technical Summary
Existing technologies cannot achieve timely and high-precision prediction in the early detection of forest fires. Conventional satellite monitoring has low spatial resolution and is easily affected by clouds and fog, while ground monitoring solutions such as ZigBee have short communication distances and poor stability.
The system employs a wireless sensor network, including a sensing node system, a routing node system, and a gateway node system. It utilizes LoRa wireless communication and NB-IoT network, combined with various sensors such as temperature, humidity, carbon monoxide, and carbon dioxide sensors, to achieve real-time data acquisition and transmission.
It achieves high-precision, anti-interference, and low-power real-time fire detection in complex forest environments, providing timely fire risk warning information and supporting fire department fire prevention deployment.
Smart Images
Figure CN223486577U_ABST
Abstract
Description
Technical Field
[0001] This utility model relates to wireless sensor networks, wireless communication technology and Internet of Things technology, and belongs to the field of early detection of forest fires, especially early detection and warning of fires in complex forest environments. Background Technology
[0002] In the current field of early forest fire detection, there are three conventional approaches: using multi-source remote sensing from geostationary meteorological satellites to invert environmental meteorological factors and assess forest fire risk; employing video surveillance technology combining visible light and infrared thermal imaging to monitor fires; and using ZigBee-based forest fire alarm systems for monitoring forest fires. Among these, the spatial resolution of aerospace monitoring methods cannot be balanced with the satellite revisit period, resulting in poor accuracy in early forest fire detection. While some polar-orbiting satellites (such as the Landsat and Sentinel series) have a spatial resolution of 20-30 meters, they revisit every three days or more, making it difficult to meet the needs of real-time fire risk warnings. Therefore, ground-based monitoring has become a more feasible approach. However, current ground-based monitoring methods, such as visible light and infrared thermal imaging video surveillance, are easily affected by clouds and fog and cannot observe the occurrence and development of underground and surface fires. Therefore, forest fires detected by these methods are often already difficult to control. Furthermore, while ZigBee-based forest fire alarm schemes can achieve early fire detection, they suffer from significant drawbacks such as short communication range (less than 100 meters) and unstable transmission (in forest environments). Therefore, it is crucial to construct a reliable ground-based wireless sensor network and develop high-precision real-time forest fire early detection and warning schemes. Summary of the Invention
[0003] This invention addresses the shortcomings of current early detection methods for forest fires by employing a wireless sensor network to solve the problem of the inability to predict forest fire risks in a timely and accurate manner.
[0004] The technical solution adopted by this utility model to solve its technical problem is:
[0005] A forest fire early detection system based on a wireless sensor network consists of the following subsystems: a sensing node system for collecting fire line information, a routing node system for relaying signals, a gateway node system for aggregating data and sending it to a data server, and a data server for recording, analyzing data, and issuing early warnings. The sensing node system collects environmental data and transmits it to the routing node system, which then aggregates the data and transmits it to the gateway node system, which in turn transmits the data to the server for analysis.
[0006] The deployment scheme of the system is as follows: First, the detection area is divided into at least one secondary detection area according to the terrain. In any secondary detection area, at least one sensing node system, one routing node system and one gateway node system are deployed.
[0007] The sensing node system includes: a sensor group, a microcontroller module, a LoRa wireless communication terminal module, an NB-IoT wireless communication module, and a power supply module; the sensor group includes: a temperature sensor, a humidity sensor, a carbon monoxide concentration sensor, and a carbon dioxide concentration sensor; the sensor group collects signals and transmits them to the microcontroller module, which processes the signals and then transmits them to the LoRa wireless communication terminal module, which then transmits the signals through the NB-IoT wireless communication module.
[0008] Furthermore, the sensor group of the sensing node system includes: an integrated temperature and humidity sensor SHT30, a flammable gas sensor GM-402B, a carbon monoxide sensor TGS5042, and a carbon dioxide sensor SGP30; the microcontroller uses an HC32L130J8TA single-chip microcomputer, the LoRa terminal RF chip uses an SX1268, and the NB-IoT wireless communication module uses an XY1100.
[0009] Furthermore, the routing node system includes: a positioning module, a microcontroller module, a LoRa wireless communication base station module, and a power supply module; the positioning module is used to obtain the latitude and longitude information of the current node, and its output is connected to the microcontroller module, which is connected to the LoRa wireless communication base station module; the LoRa wireless communication base station module receives the output signal of the sensing node system wirelessly and sends the signal to the microcontroller module, while the power supply module supplies power to the other modules.
[0010] Furthermore, the gateway node system includes: a positioning module, a microcontroller module, a LoRa wireless communication base station module, an NB-IoT wireless communication module, and a power supply module; the output of the positioning module is connected to the microcontroller module, the LoRa wireless communication base station module receives signals from the last-level routing node and outputs them to the microcontroller module for data framing; the output of the microcontroller module is connected to the NB-IoT wireless communication module, the NB-IoT wireless communication module connects to the data server of the forest fire detection and early warning control center through the NB network, and the power supply module supplies power to the other modules.
[0011] The advantages of this utility model compared with the prior art are:
[0012] (1) Anti-interference and high sensitivity. The system uses LoRa technology as the wireless communication method between nodes. Compared with ZigBee wireless communication technology, the transmission distance of LoRa technology is 20 to 80 times that of ZigBee (under the same power). Moreover, the latter has a receiving sensitivity of -148dBm and a power amplifier of +22dBm, which is about 50dBm better than the former. That is, the signal strength that LoRa can demodulate is one ten-thousandth of that of ZigBee. It has the advantages of strong anti-interference ability, high receiving sensitivity, strong diffraction ability and low power consumption. Therefore, LoRa technology is more suitable for wireless communication and data transmission in outdoor scenarios.
[0013] (2) Network Coverage. The gateway node adopts a cellular-based narrowband Internet of Things (NB) network, which overcomes the disadvantage of the remote and undulating terrain of the forest area where there is no mobile communication network coverage. Compared with the traditional GPRS network, the NB network has a significant improvement in transmission speed, making communication between the gateway node and the remote data server faster. Currently, only China Mobile supports the GPRS network, but all three major operators support the NB network.
[0014] (3) Low power consumption. The system incorporates timed sleep mode, programmable shutdown mode, and trigger-activated wake-up mode for sensing nodes, routing nodes, and gateway nodes. After each sensor, wireless communication module, and positioning module completes signal output, the microcontroller module and wireless communication module enter sleep mode, simultaneously shutting off the power to other modules via programmable control. This effectively reduces node power consumption and extends the system's lifespan. The node is also activated when the timed sleep mode ends or when a sudden change in an environmental factor in the detection area triggers a sensor response threshold.
[0015] (4) Real-time performance and accuracy. Various sensors are deployed in the forest to monitor changes in environmental factors in real time. Routing nodes will promptly collect the sensing data and send it to the gateway node. The gateway node then connects to a remote data server via the NB network. The data server ultimately outputs fire hazard and early warning information for the detected area. This allows for the timely detection of potential fire hazards, facilitating fire prevention deployments by fire departments or emergency management departments and reducing fire losses.
[0016] (5) Provide authentic and valid data. The data server records various environmental factor data, time and latitude and longitude data, which can intuitively display the changing trends of various environmental factors, providing authentic and valid data for regional fire risk model analysis and optimization, fire prevention and control law research and fire prediction. Attached Figure Description
[0017] Figure 1 This is a schematic diagram of the principle of this utility model.
[0018] Figure 2This is a schematic diagram of the sensing node of this utility model.
[0019] Figure 3 This is a schematic diagram of the routing node of this utility model.
[0020] Figure 4 This is a schematic diagram of the gateway node of this utility model.
[0021] Figure 5 This is a flowchart of the system networking of this utility model.
[0022] Figure 6 This is a flowchart of the node hibernation process of this utility model.
[0023] Figure 7 This is a flowchart illustrating the node wake-up process of this utility model.
[0024] Figure 8 The diagram shows a forest fire early detection system based on a wireless sensor network, which mainly consists of a sensing node system, a routing node system, a gateway node system, and a data server. Detailed Implementation
[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0026] See Figure 1 A forest fire early detection system based on a wireless sensor network comprises the following subsystems: a sensing node system for collecting fire line information; a routing node system for relaying signals; a gateway node system for aggregating data and sending it to a data server; and a data server for recording, analyzing data, and issuing early warnings. The system deployment scheme is as follows: the detection area is first divided into at least one secondary detection area based on the terrain. Within any secondary detection area, at least one sensing node system, one routing node system, and one gateway node system are deployed. The sensing node system collects various environmental factor signals within the secondary detection area and then wirelessly transmits these signals to the primary routing node system. After aggregating the signals from these sensing node systems, the primary routing node system connects to neighboring secondary routing node systems via single-hop and multi-hop wireless connections and relays the signals to the final routing node system. The final routing node system connects to the gateway node system, which in turn connects to the data server of the forest fire detection and early warning control center via an NB-IoT network. Finally, the data server, based on the collected fire risk factor data and existing fire risk early warning models, outputs the fire risk and early warning information for the detection area.
[0027] See Figure 2The sensing node system includes various sensors, a microcontroller module, a LoRa wireless communication terminal module, an NB-IoT wireless communication module, and a power supply module. The sensor group comprises an integrated temperature and humidity sensor (SHT30), a flammable gas sensor (GM-402B), a carbon monoxide sensor (TGS5042), and a carbon dioxide sensor (SGP30). These are mostly based on a CMOS-MEMS integrated single-chip architecture, featuring ultra-low power consumption and miniaturization. The microcontroller uses the HC32L130J8TA microcontroller, which integrates a 12-bit 1MSPS high-precision SARADC, PWM timer, multiple UARTs, SPI, IIC, and other rich functional communication peripherals. It features high integration, high anti-interference, high reliability, and ultra-low power consumption, and supports low-level development using C language, assembly language, and assembly instructions. The LoRa terminal RF chip uses the SX1268. Compared to the commonly used ZigBee wireless communication technology, LoRa technology has a transmission distance 20 to 80 times longer (at the same power), making it more suitable for complex forest environments. The NB-IoT wireless communication module selected is the XY1100, which supports the three major domestic operators and can communicate with the microcontroller via UART, IIC, SPI, uSIM, and GPIO. The sensing node system's role is to sense and collect various environmental factors, serving as the signal input for the early detection system of forest fires. Its key components are temperature, humidity, carbon monoxide, and carbon dioxide concentration sensors. The sensor outputs are connected to the corresponding signal input terminals of the microcontroller module, which in turn connects to the LoRa wireless communication terminal module. The LoRa wireless communication terminal module connects wirelessly to the primary routing node system. Its operating principle is as follows: after the sensing node system exits sleep mode or is triggered to wake up, it simultaneously activates the temperature, humidity, carbon monoxide, and carbon dioxide concentration sensors to begin data collection. After collection, the ARM controller frames the data, and then the LoRa wireless communication terminal module is activated to wirelessly transmit the framed data. Once the entire process is complete, it enters sleep mode.
[0028] See Figure 3The routing node system includes a positioning module, a microcontroller module, a LoRa wireless communication base station module, and a power supply module. The positioning module obtains the latitude and longitude information of the current node; its output is connected to the microcontroller module, which in turn is connected to the LoRa wireless communication base station module. The LoRa wireless communication base station module wirelessly receives the output signal from the sensing node system and transmits it to the microcontroller module. The power supply module provides power to the other modules. Functionally, the routing node system is divided into primary, secondary, and final-level routing node systems. Specifically, the routing node system that directly receives signals from the sensing node system is called the primary routing node system; the routing node system that communicates with each other via multi-hop communication is called the secondary routing node system; and the routing node system whose output is connected to the gateway node system is called the final-level routing node system. The role of the routing node system is signal relay; functionally, it can be divided into primary, secondary, and final-level routing node systems. The primary routing node system connects its input to the output of the sensing node system, and connects to neighboring secondary routing node systems via a single-hop wireless connection. The secondary routing node systems then connect to other secondary routing node systems via multi-hop wireless connections according to their own routing tables, ultimately connecting to the final routing node system. The output of the final routing node system connects wirelessly to the gateway node system. The subsystem operates as follows: After the LoRa wireless communication terminal module of the sensing node system sends data, the primary routing node system frames the received data frames and transmits the framed data to its neighboring secondary routing node system. The secondary routing node system receives the data, frames the data frames again, and connects to other secondary routing node systems via multi-hop wireless connections according to its own routing table, relaying the data. Finally, the final routing node system frames the data frames transmitted by the secondary routing node system and sends them to the gateway node system. After completing this process, it enters sleep mode.
[0029] See Figure 4The gateway node system includes a positioning module, a microcontroller module, a LoRa wireless communication base station module, an NB-IoT wireless communication module, and a power supply module. The positioning module's output is connected to the microcontroller module. The LoRa wireless communication base station module receives signals from the last-level routing nodes and outputs them to the microcontroller module for data framing. The microcontroller module's output is connected to the NB-IoT wireless communication module, which connects to the data server of the forest fire detection and early warning control center via the NB network. The power supply module powers the other modules. The data framing content of the gateway node system includes the current time, routing table data, battery status data of each node, collected temperature data, collected humidity data, collected carbon monoxide content data, collected carbon dioxide content data, node identification codes, latitude and longitude data of each node, reserved data, and verification codes. The gateway node system's function is to aggregate data and send it to the data server. Its input is connected to the output of the last-level routing node system, aggregating the data from the last-level routing node system and then connecting it to the data server of the forest fire detection and early warning control center via the NB network. Its working principle is as follows: After the LoRa wireless communication base station module in the gateway node system receives the data sent by the last-level routing node system, the ARM controller assembles multiple data frames, and then uploads the assembled data to the data server through the NB-IoT wireless module. After the entire process is completed, it enters sleep mode.
[0030] See Figure 5 Due to the vast detection area and the limited detection range of sensing nodes, a large number of nodes need to be deployed within the area to achieve complete coverage and ensure reliable signal transmission without loss. This system combines star network topologies and mesh network topologies to achieve effective connectivity between nodes. Specifically, the detection area is first divided into at least one secondary detection area. Routing nodes and sensing nodes are deployed sequentially in the secondary detection areas, and finally, gateway nodes are deployed at the boundaries of the detection areas. Upon initial system startup, the gateway node sends a network formation command to the last-level routing nodes, which receive and record the command. Then, the last-level routing nodes send network formation commands to the secondary routing nodes, which complete the network formation and record the command using a wireless multi-hop method. Next, the primary routing nodes receive the network formation command and begin sending network formation commands to the sensing nodes, each of which records a complete routing table. Subsequent data transmission follows this routing table until the gateway node re-initiates a network formation invitation and updates the routing tables of each node.
[0031] See Figure 6While various environmental factors are influenced by the seasons, their changes are relatively stable over short periods. Therefore, regularly shutting down the system's signal acquisition, data transmission, and wireless communication functions can significantly reduce data redundancy and extend the system's lifespan, especially in forest environments where energy replenishment is not readily available. This system incorporates a hibernation function. After completing a data report to the remote data server, all nodes in the system will sequentially enter hibernation mode. Specifically, the temperature and humidity sensors will continue operating, while the microcontroller module, LoRa wireless communication terminal module, LoRa wireless communication base station module, and NB-IoT module will enter hibernation monitoring mode. The carbon monoxide concentration sensor, carbon dioxide concentration sensor, and positioning module will be directly powered off. This significantly reduces system power consumption while substantially extending the system's lifespan.
[0032] See Figure 7 Timed sleep wake-up is the wake-up method for nodes in normal state. An alarm is set before entering sleep mode, and the timer starts upon entering sleep mode. When the alarm arrives, each module automatically wakes up and enters its respective working state. After completing its work, it orderly enters sleep mode again. However, timed sleep wake-up has a drawback: when the system enters sleep mode, sudden conditions in the detection area will not be monitored and responded to in a timely manner, greatly reducing the timeliness of fire hazard prediction. Therefore, this system also includes a trigger wake-up function. In timed sleep mode, the temperature and humidity sensors continue to work, monitoring changes in temperature and humidity in the environment in real time. When the sensor's response threshold is exceeded, the system is immediately woken up to collect signals and transmit data. The data server will promptly output fire hazard and emergency information for the detection area, alerting fire departments or emergency management departments for decision-making and deployment.
[0033] refer to Figure 8 A forest fire early detection system based on wireless sensor networks mainly consists of a sensing node system, a routing node system, a gateway node system, and a data server. The connection relationship between the various node subsystems is shown in the figure. Specifically, the sensing node system transmits the collected fire hazard factor information to the nearest primary routing node system. The primary routing node system is responsible for transmitting data in the complex forest environment, ultimately reaching the final routing node system. The final routing node system summarizes the collected fire hazard factor information and node location information, and transmits it to the data server via the NB network. The core of this system lies in the aforementioned connection relationship; this technical solution enables the collection of fire hazard factor data for corresponding areas in complex forest environments.
[0034] The data server receives and analyzes various sensor data, node identification data, node status data, detection area location data, and various routing table data to obtain fire risk factor data for the detected area. Combined with existing computer programs, a forest combustible moisture content prediction model is used to determine the forest fire combustion level and forecast forest fire risk. Staff can use an interactive interface to filter information, query warnings, generate reports, export backups, and input data, improving fire prevention efficiency and achieving scientific forest fire prevention and management.
Claims
1. A forest fire early detection system based on a wireless sensor network, characterized in that, The system consists of the following subsystems: a sensing node system for collecting fire information, a routing node system for relaying signals, a gateway node system for aggregating data and sending it to a data server, and a data server for recording, analyzing data, and issuing early warnings. The sensing node system collects environmental data and transmits it to the routing node system, which then aggregates the data and transmits it to the gateway node system, which in turn transmits the data to the server for analysis. The deployment scheme of the system is as follows: First, the detection area is divided into at least one secondary detection area according to the terrain. In any secondary detection area, at least one sensing node system, one routing node system and one gateway node system are deployed. The sensing node system includes: a sensor group, a microcontroller module, a LoRa wireless communication terminal module, an NB-IoT wireless communication module, and a power supply module; the sensor group includes: a temperature sensor, a humidity sensor, a carbon monoxide concentration sensor, and a carbon dioxide concentration sensor; the sensor group collects signals and transmits them to the microcontroller module, which processes the signals and then transmits them to the LoRa wireless communication terminal module, which then transmits the signals through the NB-IoT wireless communication module.
2. The forest fire early detection system based on a wireless sensor network as described in claim 1, characterized in that, The sensor group of the sensing node system includes: an integrated temperature and humidity sensor SHT30, a flammable gas sensor GM-402B, a carbon monoxide sensor TGS5042, and a carbon dioxide sensor SGP30; the microcontroller uses an HC32L130J8TA single-chip microcomputer, the LoRa terminal radio frequency chip uses an SX1268, and the NB-IoT wireless communication module uses an XY1100.
3. The forest fire early detection system based on a wireless sensor network as described in claim 1, characterized in that, The routing node system includes: a positioning module, a microcontroller module, a LoRa wireless communication base station module, and a power supply module; the positioning module is used to obtain the latitude and longitude information of the current node, and its output is connected to the microcontroller module, which is connected to the LoRa wireless communication base station module; the LoRa wireless communication base station module receives the output signal of the sensing node system wirelessly and sends the signal to the microcontroller module, while the power supply module supplies power to the other modules.
4. The forest fire early detection system based on a wireless sensor network as described in claim 1, characterized in that, The gateway node system includes: a positioning module, a microcontroller module, a LoRa wireless communication base station module, an NB-IoT wireless communication module, and a power supply module. The output of the positioning module is connected to the microcontroller module. The LoRa wireless communication base station module receives signals from the last-level routing node and outputs them to the microcontroller module for data framing. The output of the microcontroller module is connected to the NB-IoT wireless communication module. The NB-IoT wireless communication module connects to the data server of the forest fire detection and early warning control center through the NB network. The power supply module provides power to the other modules.