Unmanned aerial vehicle sowing type forest meteorological factor wide-area internet-of-things acquisition system

Abstract

The invention belongs to the field of data monitoring, and discloses an unmanned aerial vehicle scattering type forest meteorological factor wide-area Internet of Things acquisition system, which comprises a monitoring terminal, a sink node and an acquisition node, the wireless sensor network consists of a plurality of acquisition nodes with detection environment parameters; the acquisition node comprises a processor module, and a temperature sensor, a humidity sensor, a data acquisition module, a data transmission module and a power supply module which are connected with the processor module. In order to fill up the blank of small-compartment climate monitoring in the forest in China and prevent forest fires caused by unknowability of fire danger factors in the forest, the prevention and control capability of the forest fires is improved. The forest internal fire danger factors are monitored in real time through the forest internal surface meteorological factor acquisition balls, so that problems are found in advance, and forest fire disasters are prevented.

Description

Technical Field

[0001] The present invention relates to a wireless sensor network, in particular to an unmanned aerial vehicle spreading type wide-area Internet of Things collection system for meteorological factors in a forest, belonging to the field of meteorological data monitoring inside a forest. Background Art

[0002] At present, there are few studies on the observation and research of small-scale climate inside forests in China. Most of them use simple ventilation and dryness performance to observe the temperature, humidity and other data inside green spaces.

[0003] At present, the observation of meteorological factors in the forest is generally carried out by parallel observation, comparative observation, flow observation and gradient observation. Most of these observation methods require people to enter the forest to collect data, but it is impossible to collect forest microclimate data under different geomorphic conditions in real time and effectively. Due to the presence of trees and leaves in the forest, diffuse reflection and polycrystalline scattering will occur during the propagation of signals, resulting in significant attenuation of signal strength and multipath interference. This phenomenon makes it difficult for traditional wireless communication technology to work effectively in the forest environment, and the stability and reliability of data transmission are seriously affected.

[0004] With the popularization of remote sensing technology, remote sensing technology and geographic information systems and other advanced means can be used to monitor forest meteorological factors at different spatial scales, from forest stands to regions. Remote sensing technology has become an important means of quickly obtaining forest meteorological factors. However, remote sensing technology also has some shortcomings. The changes in water and chlorophyll content of plants in forests at different growth stages will affect the spectral characteristics of remote sensing images, resulting in a decrease in the accuracy of image interpretation results.

[0005] Valleys and steep slopes can create shadows in remote sensing images, affecting the accuracy of image interpretation. Projection errors and shadow formation errors can affect the quality of images and the accuracy of survey results. Hyperspectral sensors are expensive, which can affect the cost-effectiveness of applications in the forestry field; and the complexity of hyperspectral data collection and analysis requires a higher level of capabilities to obtain such data.

[0006] Combined with the development of current electronic information technology, forest environment monitoring technology has also been transformed from traditional technology to digital monitoring technology under the background of the gradual maturity of network technology. Digital monitoring technology has the advantages of strong anti-interference ability and easy signal storage. For the internal communication problem of the forest, the problem of interconnection is solved through wireless sensor networks, and a large number of sensor nodes with perception, processing and wireless communication capabilities are formed to form a multi-hop self-organizing network system to complete the established tasks.

[0007] If the meteorological factors inside the forest can be analyzed in real time, technicians will be able to grasp the actual forest environment in a timely and accurate manner. To this end, a complete and accurate Internet of Things system is needed to conduct targeted monitoring of the meteorological factors inside the forest. Summary of the invention

[0008] The technical problem to be solved by the present invention is to address the deficiencies of the above-mentioned prior art and propose a drone-spreading forest meteorological factor wide-area Internet of Things collection system for collecting forest meteorological factor data.

[0009] The present invention adopts the following technical solutions to solve the above technical problems

[0010] A wide-area Internet of Things collection system for forest meteorological factors spread by drones, comprising a monitoring terminal, a convergence node, and a collection node; a wireless sensor network is formed through the collection node capable of detecting environmental parameters; the wireless sensor network transmits the environmental parameters collected by the collection node to the convergence node, the convergence node summarizes the received environmental parameters and then uploads them to the monitoring terminal, and the monitoring terminal exchanges information with the control background; the collection node comprises a processor module and a temperature sensor, a humidity sensor, a wireless transmission module, and a power module connected thereto;

[0011] As a further preferred solution of the drone-spreading forest meteorological factor wide-area Internet of Things collection system of the present invention, the monitoring terminal adopts a PC.

[0012] As a further preferred solution of the drone-spreading forest meteorological factor wide-area Internet of Things collection system of the present invention, the processor module adopts an ARM series single-chip microcomputer.

[0013] As a further preferred solution of the drone-spreading forest meteorological factor wide-area Internet of Things collection system of the present invention, the chip model of the temperature sensor is SHT30.

[0014] As a further preferred solution of the drone-spreading forest meteorological factor wide-area Internet of Things collection system of the present invention, the transmission module is a LoRa module.

[0015] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0016] 1. The present invention has reasonable design, simple operation, flexible and convenient network deployment, and the method of spreading sensors by drones saves the cost of manual arrangement of sensors;

[0017] 2. The sensor nodes of the present invention have low energy consumption, strong scalability, and intuitive network location information;

[0018] 3. The sensor nodes form a multi-hop, self-organizing wireless sensor network through wireless communication. The self-organizing network has strong capabilities and can monitor meteorological factors inside the forest in real time and synchronously;

[0019] 4. This device adopts wireless sensor network technology and uses wireless sensor nodes to monitor the temperature and humidity in the acceleration device in real time, avoiding the problems of poor reliability and troublesome monitoring caused by relying entirely on manual operation;

[0020] 5. By monitoring different forest meteorological factors through the UAV-spreading forest meteorological factor wide-area Internet of Things collection system, it is finally possible to monitor the internal meteorological factors of the forest by relying on the UAV-spreading forest meteorological factor wide-area Internet of Things collection system based on wireless sensor network proposed in the present invention, and finally achieve effective prevention of forest fires. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic diagram of the workflow of the wide-area Internet of Things collection system for forest meteorological factors spread by drones of the present invention;

[0022] Figure 2 This is a schematic diagram of the overall structure of the system of the wide-area Internet of Things collection system for forest meteorological factors spread by drones of the present invention;

[0023] Figure 3 This is a schematic diagram of the hardware composition of the wide-area Internet of Things collection system for forest meteorological factors spread by drones of the present invention;

[0024] Figure 4 It is a workflow diagram of data collection of the sensor node of the present invention;

[0025] Figure 5 It is a working flow chart of the sensor temperature threshold adaptive relay of the present invention.

[0026] Figure 6 It is a working flow chart of the sensor relay node of the present invention.

[0027] Figure 7 This is a physical picture of the sensor node housing of the present invention.

[0028] Figure 8 This is a physical diagram of the sensor node of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings:

[0030] The technical solution adopted by the present invention to solve the technical problem is: a wide-area Internet of Things collection system for forest meteorological factors by drone spreading, which is divided into a lower-level computer collection part and a upper-level computer display part. The overall workflow is as follows: Figure 1 shown.

[0031] The invention discloses a wireless sensor network-based UAV-based forest meteorological factor wide-area Internet of Things collection system, such as Figure 1 As shown, the system includes: (1) the device is dropped by a drone and spread into the forest through fixed-point cruise; (2) the collection nodes inside the forest form a wireless sensor self-organizing network; the meteorological factor data of the monitored forest interior area is obtained through the temperature and humidity sensor, and the processed data is sent to the STM32 control unit, and the STM32 control unit can obtain the corresponding value; (3) the meteorological factor data in the forest collected by the collection nodes are summarized through the aggregation nodes scattered at the edge of the forest; (4) the collection nodes upload the received data to the monitoring terminal;

[0032] like Figure 2 As shown in the figure, the overall structure diagram of the system of the wide-area Internet of Things collection system of the meteorological factors in the forest spread by the drone of the present invention is shown, and the wide-area Internet of Things collection system of the meteorological factors in the forest spread by the drone includes a collection device, a wireless transmission device, a nearly closed housing, data collection and storage, and a host computer receiving and displaying data.

[0033] like Figure 3 As shown, the UAV-spreading forest meteorological factor wide-area Internet of Things acquisition system described in the present invention can be seen that the system consists of a temperature sensor, a humidity sensor, a power module, a control unit and a wireless transmission module. The control background includes a data receiving module and a display module. Among them, the monitoring terminal adopts a PC, the processor module adopts an ARM series single-chip microcomputer, the temperature and humidity sensor chip model is SHT30, and the wireless transmission module is a LoRa module, which is powered by a 3.7V battery.

[0034] The temperature and humidity sensor is used to monitor the surface meteorological factor data inside the forest and send it to the monitoring terminal, i.e., a PC, through a wireless network. The control unit is used to collect and process the monitored data and send it to the terminal through a wireless transmission module. The nearly closed spherical shell is a detachable system.

[0035] The monitoring terminal uses a computer, which can collect the data of temperature and humidity system at any time through the wireless transmission module.

[0036] like Figure 4 The data communication workflow of the present invention is as follows: LoRa transmits wirelessly to the host computer and displays it through the serial port 1 and serial port 2 of the STM32 control unit at a baud rate of 1200 bit / s, full-duplex communication, 8-bit word length, and %.1f, i.e., outputting a floating point number with 1 digit retained after the decimal point. By writing a program into the STM32 microcontroller, the monitored data is sent to the host computer every hour, thereby realizing real-time monitoring of the fire risk factors inside the forest.

[0037] Multi-hop communication Figure 5 Therefore, the present invention designs a multi-hop communication device that can automatically control the start and stop of relay sensor nodes according to the ambient temperature. In the signal propagation model in the forest environment, the path loss is: PL(dB)=PL0+10nlog 10 (d)+X f in: PL0 is the free space path loss, which depends on the signal frequency and the reference distance; n is the path loss exponent, which reflects the signal attenuation characteristics when the leaves are dense inside the forest; d is the signal transmission distance; X f Additional losses are caused by leaves and other obstacles inside the forest. In the season when forest leaves are lush, the path loss exponent n and the additional loss X f To ensure the integrity and stability of data transmission, the system turns on the relay node by detecting the temperature. At this time, the system power consumption P total Includes the energy consumption of sensor nodes and relay nodes: P total =P sensor +N relay ×P relay in: P sensor is the energy consumption of the sensor node; N relay is the number of currently enabled relay nodes; P relay is the energy consumption of the relay node. As relay nodes are turned on, they will help overcome high path losses and ensure effective transmission of signals in multi-hop communications. By optimizing the number of relay nodes N relay , the system can adjust power consumption according to the density of the tree canopy to extend the system working time. In the warmer season, when the leaves in the forest are lush, more relay nodes are enabled to overcome the high path loss; while in the colder season, when the leaves fall, some relay nodes are turned off to save power. In this case, the system effectively extends battery life and reduces power consumption by reducing the energy consumption of relay nodes, while ensuring the effectiveness of data transmission. Through this intelligent temperature-controlled relay node management strategy, the system can maintain efficient and stable data transmission when the vegetation is dense, and reduce energy consumption when the vegetation is sparse, maximizing the service life of the system.

[0038] like Figure 6 The system shown in the figure adopts multi-hop communication technology, (1), (2), (3) are the collection nodes respectively; (4) is the aggregation node; when the signal strength is weak, the relay is turned on and the data is transmitted to the aggregation node in sequence. When the signal strength is high, the relay is turned off and the collection node skips the relay and directly reaches the aggregation node. In a forest environment, signals are transmitted step by step through multiple collection nodes to the aggregation node. Due to the presence of trees and vegetation in the forest, the signal will be affected by refraction, reflection and scattering during the propagation process, resulting in attenuation of signal strength. When radio waves pass through the forest, trees, leaves, etc. act as scatterers, causing significant additional loss to signal propagation. According to the vegetation model proposed by the International Telecommunication Union (ITU-R), signal loss can be expressed by the following formula: L(dB)=A·f k ·d m in: L(dB): additional path loss of the signal when passing through vegetation, expressed in dB; A: a constant related to the density and type of trees in the forest, obtained through experiments or empirical data; f: signal frequency, in MHz; d: distance the signal travels, in meters; k and m are empirical parameters that reflect the impact of frequency and propagation distance on loss, and are usually determined through experiments based on the vegetation density, humidity and other factors of the environment. In practical applications, as the signal frequency increases, the loss will also increase significantly. Especially in high-density forests, the leaves and trunks of trees will cause refraction and multipath propagation of signals, further reducing the signal strength. By using the multi-hop communication method of the above self-starting relay node, the impact of the forest environment on signal propagation can be reduced to ensure the integrity and reliability of the data stream.

[0039] The invention has reasonable design, simple operation, flexible and convenient network layout, and the method of spreading sensors by drones saves the cost of manually arranging sensors; the sensor nodes have low energy consumption, strong scalability, and intuitive network location information; the sensor nodes form a multi-hop, self-organizing wireless sensor network through wireless communication, and the self-organizing network has strong ability to monitor meteorological factors inside the forest in real time and synchronously; the device adopts wireless sensor network technology and uses wireless sensor nodes to monitor the temperature and humidity in the acceleration device in real time, avoiding the problems of poor reliability and troublesome monitoring caused by relying entirely on manual operation;

[0040] The present invention uses drones to spread sensor nodes inside the forest, configure wireless sensor nodes that can collect temperature and humidity, monitor the surface meteorological factors inside the forest in real time, infer the possibility of forest fire when the temperature and humidity change in different ranges, and test that various indicators in the forest environment are not affected by changes in the external environment, so as to achieve objective monitoring of temperature and humidity, and ultimately achieve effective prevention of forest fires.

Claims

1. A drone-spreading forest meteorological factor wide-area Internet of Things collection system, comprising a monitoring terminal, a convergence node, and a collection node; a wireless sensor network is formed through the collection nodes capable of detecting environmental parameters; the wireless sensor network transmits the environmental parameters collected by the collection nodes to the convergence nodes, and the convergence nodes summarize the received environmental parameters and upload them to the monitoring terminal, and the monitoring terminal exchanges information with the control background; the collection node comprises a processor module and a temperature sensor, a humidity sensor, a wireless transmission module, and a power module connected thereto.

2. According to claim 1, a spreadable spherical forest internal surface meteorological factor collection device based on a wireless sensor network is characterized in that: The monitoring terminal is a PC.

3. According to claim 1, a spreadable spherical forest internal surface meteorological factor collection device based on a wireless sensor network is characterized in that: The processor module adopts an ARM series single chip microcomputer.

4. According to claim 1, a spreadable spherical forest internal surface meteorological factor collection device based on a wireless sensor network is characterized in that: The chip model of the temperature sensor is SHT30.

5. According to claim 1, a device for collecting meteorological factors inside a spherical forest based on a wireless sensor network, which can be spread, is characterized in that: The transmission module is a LoRa module.

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