A method for fire fighting based on forest natural perception

Abstract

The application provides a method for fire fighting based on forest natural perception, and relates to the technical field of natural perception. The method for fire fighting based on forest natural perception comprises the following steps: S1. probe setting, including making a probe and making a patch, wherein the probe is a conductive and corrosion-resistant metal or a carbon rod, and the patch is a conductive and corrosion-resistant metal or a carbon film; S2. connection with plants, and the specific operation steps are as follows: S2.1. the probe is inserted into a plant body to be connected with plant organs and tissues such as roots, trunks and branches. Through a forest perception and a multi-channel distributed plant micro-current sensing system, a multi-disaster global perception system based on forest perception is established, a global multi-factor imaging system based on a perception atlas is established, visualization of forest perception information is realized, a mapping relationship between plant body electric signals and fire information is constructed based on different forest fire risks, and then a forest fire risk early warning perception atlas is established.

Description

Technical Field

[0001] This invention relates to the field of natural sensing technology, specifically a method for fire fighting based on forest natural sensing. Background Technology

[0002] Perception is the foundation for humans and different life forms to acquire external information and support life activities. It is also the foundation for the Internet of Things to acquire external information and drive information flow. Perception is integrated into all human production practices and life activities. Currently, the process of perceiving the natural environment is developing towards intelligent perception, with the goal of forming an integrated intelligent perception capability of "sky, air, ground, and network" and establishing a natural resource intelligent perception network that covers all elements, multiple scales, multiple levels, and the entire domain.

[0003] Due to the static nature of plants, they have evolved mechanisms based on physical and chemical defenses to deter herbivores and repair damaged tissues. These mechanisms manifest as changes in reactive oxygen species, electrical signals, and cellular solute concentrations within plants. They are an important component of the signaling network that forms the defense response at damaged sites and the systemic defense response. Extremely weak biocurrents exist within plants, and these biocurrents become abnormal when plants are invaded or damaged. The development of technologies such as wearable plant sensors, flexible sensors, smart sensors, and invasive electrodes has provided a technological basis for more accurate measurement of changes in plant currents.

[0004] All life and matter are natural sensors, natural perceptors that integrate self-sensing and information interpretation. However, we still know little about how to acquire, understand, and utilize this information. Research on perception based on the natural perception processes of forests allows us to perceive the occurrence and development of forests and fires from the forest's own perspective, letting the forest tell us the answers. This research aims to identify events occurring in forests based on their natural perception processes. This perception requires establishing a mapping relationship between perceived information and knowledge about forest fires. Plant electrical signals are physiological signals that play an important role in information transmission between plant tissues. They can reflect changes in plant growth and development, nutritional status, and the external environment. However, due to the physiological and environmental noise inherent in forests, it is difficult to interpret effective information. Therefore, it is necessary to screen species sensitive to forest fires, establish perception maps, and build highly sensitive recognition models based on big data and artificial intelligence.

[0005] However, research based on the natural perception process of forests, perceiving the occurrence and development of forests and fires from the perspective of the forest itself, letting the forest tell us the answers, and researching the identification of events occurring in forests based on the natural perception process of forests, requires establishing a mapping relationship between perceived information and forest fire knowledge. Based on different forest fire risks, a mapping relationship between plant electrical signals and fire information is constructed, and then a forest fire risk early warning perception map is established. This invention patent belongs to a completely new approach and original idea, and there are currently no publicly available patents in this regard. Summary of the Invention

[0006] (a) Technical problems to be solved

[0007] To address the shortcomings of existing technologies, this invention provides a method for fire fighting based on forest natural sensing, which solves the problems of the inability to transmit signals through plant sensing and the inability to take timely countermeasures when a forest fire occurs.

[0008] (II) Technical Solution

[0009] To achieve the above objectives, the present invention provides the following technical solution: a method for fire fighting based on forest natural perception, comprising the following steps:

[0010] S1. Probe setup, including probe fabrication and patch fabrication, wherein the probe is a conductive and corrosion-resistant metal or carbon rod, and the patch is a conductive and corrosion-resistant metal or carbon film.

[0011] S2. Establishing a connection with the plant, the specific steps of which are as follows:

[0012] S2.1. Insert the probe into the plant and connect it with the plant's roots, trunk, branches, and other organs and tissues;

[0013] S2.2. Expose the phloem at the plant joint, connect the patch to the phloem of the plant roots, trunk, branches, etc., and connect the patch to the plant leaves at the same time.

[0014] S2.3. The probe and patch are connected to the current metering terminal via wires. A virtual plant is drawn in the computer, corresponding to the physical plant. The current change at each position of the plant is displayed in real time on the virtual plant in the computer.

[0015] S3. Establish a plant library and a virtual forest, including establishing and displaying a corresponding virtual forest, where the virtual plant library in the virtual forest corresponds to the corresponding plant in the forest;

[0016] S4. Signal channel setup: By connecting the host to multiple main signals, each main signal has multiple branch signals. Each main signal corresponds to a plant, and each branch signal corresponds to an organ or tissue on a plant. One main signal is connected to the ground to obtain the ground's electrical signal.

[0017] S5. Host setup: A positioning chip is installed in the host, mainly used to record latitude and longitude. It uses mobile phone signal or Beidou short message communication. At the same time, the host has a storage chip inside, which can store plant electrical signals. The whole system is powered by solar energy or batteries.

[0018] S6. Standard learning field setup: The standard learning field is a controllable experimental field, mainly used to establish a database of recognizable event signals. The standard learning field is equipped with intelligent cameras, infrared and visible light video monitoring, and an automatic weather station. The intelligent cameras are used to synchronously and automatically record fire events; the infrared and visible light video monitoring is used to synchronously monitor fire events; and the automatic weather station is used to synchronously record information such as weather, plant moisture content, soil temperature and humidity, humus temperature and humidity, and drought.

[0019] S7. Signal library establishment and sensitive plant selection: Based on the electrical signals generated under different events recorded in S6, a signal library for different events is established. Events and electrical signals are recorded synchronously to establish a signal library that matches events and signals. A background signal library is recorded synchronously to remove background signals and enhance event signals. At the same time, the sensitivity of different plants to the response to things is recorded, and sensitive plants are selected as the perceptrons and backup perceptrons. Normalization processing can be performed on the sensitivity of different plants, and cloning and seedling cultivation of sensitive plants can also be carried out.

[0020] S8. Signal library settings: generate event ripples with different signals for different events, including the effects of vegetation moisture content, lightning, fire, animal activity, human activity, drought, earthquake, flood, etc. Based on the plant electrical signal library in the signal library, identify and confirm different events, and identify different events through different signal changes and event ripples.

[0021] S9. Setting up a forest sensing network involves the following steps:

[0022] S9.1. Set up the observation field in the field;

[0023] S9.2. Based on the area to be sensed, set up a sensing matrix in the forest at certain spatial intervals;

[0024] S9.3. Plant plants that are sensitive to different events as needed;

[0025] S9.4. Arrange the host, signal probes and patches according to a certain spatial layout;

[0026] S9.5. Obtain the spatial layout of electrical signals in the site;

[0027] S9.6. Establish a virtual forest that corresponds to the real forest;

[0028] S10. Event perception and recognition: When different events occur, different event ripples are obtained. Different signal ripples represent different events and correspond to different waveforms. For example, when a fire occurs, fire ripples are obtained. The obtained ripple signals are transmitted back to the system platform through the host and wireless network. The platform calculates the ripple attributes such as time, intensity, range, and amplitude of the ripple signals, and then determines the event attributes based on the ripple attributes.

[0029] S11. Perception and recognition of combined events: For similar or different types of events occurring simultaneously in the forest, record the signals of combined or integrated events, and deconstruct them according to the ripples and waveforms of the event signals to obtain information about different events;

[0030] S12. Event Response, the specific steps for handling the event are as follows:

[0031] S12.1. Establish an automated hangar for unmanned aerial vehicles (UAVs);

[0032] S12.2. The distance to the drone's automatic airport is within 30 minutes;

[0033] S12.3. Obtain the latitude and longitude of the fire;

[0034] S12.4. Obtain the size and intensity of the fire based on the intensity of the ripples and the degree of signal ablation;

[0035] S12.5. Based on the needs of the fire scene, the drone swarm is automatically released from the drone airport to carry out automatic fire suppression;

[0036] S12.6. Depending on the nature of the event, send the event information to the responding agency and relevant departments;

[0037] S13. According to step S12, corresponding measures such as manual sampling, unmanned vehicles, unmanned vehicles, and intelligent robots can be adopted.

[0038] Preferably, the probe and patch in step S1 can be either contact-type or inductive-type.

[0039] (III) Beneficial Effects

[0040] This invention provides a method for fire fighting based on forest natural perception. It has the following beneficial effects:

[0041] 1. In this invention, the electrical signals reflected by plants are obtained through events of controllable intensity. Using this as a starting point, a perception map of event information and plant electrical signals is gradually established, which will lay the foundation for the subsequent establishment of a model of the relationship between plant electrical signals and environmental factors.

[0042] 2. In this invention, a multi-hazard full-domain perception system based on forest perception is established through a forest perception and multi-channel distributed plant microcurrent sensing system, and a full-domain multi-factor imaging system based on the perception map is established to realize the visualization of forest perception information. Based on different forest fire risks, a mapping relationship between plant electrical signals and fire information is constructed, and then a forest fire risk early warning perception map is established. Detailed Implementation

[0043] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0044] Example 1:

[0045] This invention provides a method for fire fighting based on forest natural perception, comprising the following steps:

[0046] S1. Probe setup, including probe fabrication and patch fabrication, wherein the probe is a conductive and corrosion-resistant metal or carbon rod, and the patch is a conductive and corrosion-resistant metal or carbon film.

[0047] S2. Establishing a connection with the plant, the specific steps of which are as follows:

[0048] S2.1. Insert the probe into the plant and connect it with the plant's roots, trunk, branches, and other organs and tissues;

[0049] S2.2. Expose the phloem at the plant joint, connect the patch to the phloem of the plant roots, trunk, branches, etc., and connect the patch to the plant leaves at the same time.

[0050] S2.3. The probe and patch are connected to the current metering terminal via wires. A virtual plant is drawn in the computer, corresponding to the physical plant. The current change at each position of the plant is displayed in real time on the virtual plant in the computer.

[0051] S3. Establish a plant library and a virtual forest, including establishing and displaying a corresponding virtual forest, where the virtual plant library in the virtual forest corresponds to the corresponding plant in the forest;

[0052] S4. Signal channel setup: By connecting the host to multiple main signals, each main signal has multiple branch signals. Each main signal corresponds to a plant, and each branch signal corresponds to an organ or tissue on a plant. One main signal is connected to the ground to obtain the ground's electrical signal.

[0053] S5. Host setup: A positioning chip is installed in the host, mainly used to record latitude and longitude. It uses mobile phone signal or Beidou short message communication. At the same time, the host has a storage chip inside, which can store plant electrical signals. The whole system is powered by solar energy or batteries.

[0054] S6. Standard learning field setup: The standard learning field is a controllable experimental field, mainly used to establish a database of recognizable event signals. The standard learning field is equipped with intelligent cameras, infrared and visible light video monitoring, and an automatic weather station. The intelligent cameras are used to synchronously and automatically record fire events; the infrared and visible light video monitoring is used to synchronously monitor fire events; and the automatic weather station is used to synchronously record information such as weather, plant moisture content, soil temperature and humidity, humus temperature and humidity, and drought.

[0055] S7. Signal library establishment and sensitive plant selection: Based on the electrical signals generated under different events recorded in S6, a signal library for different events is established. Events and electrical signals are recorded synchronously to establish a signal library that matches events and signals. A background signal library is recorded synchronously to remove background signals and enhance event signals. At the same time, the sensitivity of different plants to the response to things is recorded, and sensitive plants are selected as the perceptrons and backup perceptrons. Normalization processing can be performed on the sensitivity of different plants, and cloning and seedling cultivation of sensitive plants can also be carried out.

[0056] S8. Signal library settings: generate event ripples with different signals for different events, including the effects of vegetation moisture content, lightning, fire, animal activity, human activity, drought, earthquake, flood, etc. Based on the plant electrical signal library in the signal library, identify and confirm different events, and identify different events through different signal changes and event ripples.

[0057] S9. Setting up a forest sensing network involves the following steps:

[0058] S9.1. Set up the observation field in the field;

[0059] S9.2. Based on the area to be sensed, set up a sensing matrix in the forest at certain spatial intervals;

[0060] S9.3. Plant plants that are sensitive to different events as needed;

[0061] S9.4. Arrange the host, signal probes and patches according to a certain spatial layout;

[0062] S9.5. Obtain the spatial layout of electrical signals in the site;

[0063] S9.6. Establish a virtual forest that corresponds to the real forest;

[0064] S10. Event perception and recognition: When different events occur, different event ripples are obtained. Different signal ripples represent different events and correspond to different waveforms. For example, when a fire occurs, fire ripples are obtained. The obtained ripple signals are transmitted back to the system platform through the host and wireless network. The platform calculates the ripple attributes such as time, intensity, range, and amplitude of the ripple signals, and then determines the event attributes based on the ripple attributes.

[0065] S11. Perception and recognition of combined events: For similar or different types of events occurring simultaneously in the forest, record the signals of combined or integrated events, and deconstruct them according to the ripples and waveforms of the event signals to obtain information about different events;

[0066] S12. Event Response, the specific steps for handling the event are as follows:

[0067] S12.1. Establish an automated hangar for unmanned aerial vehicles (UAVs);

[0068] S12.2. The distance to the drone's automatic airport is within 30 minutes;

[0069] S12.3. Obtain the latitude and longitude of the fire;

[0070] S12.4. Obtain the size and intensity of the fire based on the intensity of the ripples and the degree of signal ablation;

[0071] S12.5. Based on the needs of the fire scene, the drone swarm is automatically released from the drone airport to carry out automatic fire suppression;

[0072] S12.6. Depending on the nature of the event, send the event information to the responding agency and relevant departments;

[0073] S13. According to step S12, corresponding measures such as manual sampling, unmanned vehicles, unmanned vehicles, and intelligent robots can be adopted.

[0074] According to step S1, the probe and patch can be either contact-type or inductive-type.

[0075] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for fire fighting based on forest natural perception, characterized in that: Includes the following steps: S1. Probe setup, including probe fabrication and patch fabrication, wherein the probe is a conductive and corrosion-resistant metal or carbon rod, and the patch is a conductive and corrosion-resistant metal or carbon film. S2. Establishing a connection with the plant, the specific steps of which are as follows: S2.

1. Insert a probe into the plant and connect it with plant organs and tissues, including roots, trunks, and branches; S2.

2. Expose the phloem of the plant joint, connect the patch to the plant phloem, and simultaneously connect the patch to the plant leaves, wherein the plant phloem includes the root, trunk, and branches; S2.

3. The probe and patch are connected to the current metering terminal via wires. A virtual plant is drawn in the computer, corresponding to the physical plant. The current change at each position of the plant is displayed in real time on the virtual plant in the computer. S3. Establish a plant library and a virtual forest, including establishing and displaying a corresponding virtual forest, where the virtual plant library in the virtual forest corresponds to the corresponding plant in the forest; S4. Signal channel setup: The host is connected to multiple main signals, each main signal has multiple branch signals, each main signal corresponds to a plant, and each branch signal corresponds to an organ or tissue on a plant. One main signal is connected to the ground to obtain the ground's electrical signal. S5. Host setup: A positioning chip is installed in the host to record latitude and longitude. It uses mobile phone signal or Beidou short message communication. At the same time, the host has a storage chip to store plant electrical signals. The whole system is powered by solar energy or batteries. S6. Standard learning field setup: The standard learning field is a controllable experimental field, mainly used to establish a signal library that can identify different events. The standard learning field is equipped with intelligent cameras, infrared and visible light video monitoring, and an automatic weather station. The intelligent cameras are used to synchronously and automatically record fire events; the infrared and visible light video monitoring is used to synchronously monitor fire events; and the automatic weather station is used to synchronously record weather, plant moisture content, soil temperature and humidity, humus temperature and humidity, and drought information. S7. Signal library establishment and sensitive plant selection: Based on the electrical signals generated under different events recorded in S6, establish signal libraries for different events, synchronously record events and electrical signals, establish a signal library matching events and signals, and synchronously record a background signal library for removing background signals and enhancing event signals. At the same time, record the sensitivity of different plants to the response to things, select sensitive plants as perceptrons and backup perceptrons; normalize the sensitivity of different plants, and clone seedlings of sensitive plants. S8. Signal library settings: generate event ripples with different signals for different events, including the effects of vegetation moisture content, lightning, fire, animal activity, human activity, drought, earthquake, and flood. Based on the plant electrical signal library in the signal library, identify and confirm different events, and identify different events through different signal changes and event ripples. S9. Setting up a forest sensing network involves the following steps: S9.

1. Set up the observation field in the field; S9.

2. Based on the area to be sensed, set up a sensing matrix in the forest at certain spatial intervals; S9.

3. Plant plants that are sensitive to different events as needed; S9.

4. Arrange the host, signal probes and patches according to a certain spatial layout; S9.

5. Obtain the spatial layout of electrical signals in the site; S9.

6. Establish a virtual forest that corresponds to the real forest; S10. Event perception and recognition: When different events occur, different event ripples are obtained. Different signal ripples represent different events and correspond to different waveforms. When a fire occurs, fire ripples are obtained. The obtained ripple signals are transmitted back to the system platform through the host and wireless network. The platform calculates the ripple attributes, which include ripple signal time, intensity, range, amplitude, and ripple attributes. Then, the event attributes are determined based on the ripple attributes. S11. Perception and recognition of combined events: For similar or different types of events occurring simultaneously in the forest, record the signals of combined or integrated events, and deconstruct them according to the ripples and waveforms of the event signals to obtain information about different events; S12. Event Response, the specific steps for handling the event are as follows: S12.

1. Establish an automated hangar for unmanned aerial vehicles (UAVs); S12.

2. The distance to the drone's automatic airport is within 30 minutes; S12.

3. Obtain the latitude and longitude of the fire; S12.

4. Obtain the size and intensity of the fire based on the intensity of the ripples and the degree of signal ablation; S12.

5. Based on the needs of the fire scene, the drone swarm is automatically released from the drone airport to carry out automatic fire suppression; S12.

6. Depending on the nature of the event, send the event information to the responding agency and relevant departments; S13. Adopt the corresponding countermeasures according to step S12, the countermeasures including manual labor, drones, unmanned vehicles or intelligent robots.

2. The method for fire fighting based on forest natural perception according to claim 1, characterized in that: In step S1, the probe and patch can be either contact-type or inductive-type.