Air-ground collaborative environment monitoring system and method

Abstract

The invention relates to the technical field of geographical environment information, in particular to an air-ground collaborative environment monitoring system and method.The system comprises a sensing end, an aerial carrier end, a control end, a cloud end and an application end; the transmission network executes two types of data flow directions: monitoring data flows from the sensing end to the cloud end and the application end through the aerial carrier end and the control end, and task data flows from the application end to the aerial carrier end and the sensing end through the cloud end and the control end. The influence on the environment can be reduced, and the construction cost is reduced; the unattended terminal equipment is free of maintenance for a long time, reduces the outdoor workload, reduces the operation and maintenance cost, can be compatible with different data types, has high expansion performance, and can realize large-capacity data recovery of non-texts such as images. Even real-time data live broadcasting is achieved, and timeliness is guaranteed; and normalized high-autonomy operation can be realized.

Description

Technical Field

[0001] This invention relates to the field of geographic environmental information technology, specifically to an air-ground collaborative environmental monitoring system and method. Background Technology

[0002] Traditional ground surveys and monitoring require a significant investment of time, manpower, material resources, and financial resources due to factors such as terrain, transportation, and network limitations. The scope of data collection is limited, and data application and analysis are relatively lagging.

[0003] In large areas without public networks, the main methods for collecting ground-based environmental monitoring data are as follows: 1) collecting data by a large number of people; 2) setting up tower base stations to access public networks; 3) Mesh self-organizing network mode; 4) satellite communication, etc. First, manual fieldwork is inefficient and difficult to reach remote or dangerous areas; second, tower deployment is limited by terrain and ecological red lines, has a long deployment cycle, high cost (the cost of a single tower is nearly one million yuan), and its location is fixed, leaving many monitoring blind spots; while Mesh self-organizing networks have small coverage and low transmission rates, and their current application is very immature and rare; satellite communication is expensive and cannot be deployed on a large scale.

[0004] In the prior art, the use of drones for communication relay has been reported, such as the relay drone system disclosed in patent publication number CN 108615346 A, which utilizes relay drones to extend the communication link or communication signal between a base station and a working drone. The relay drone can extend the communication link by acting as a node, which relays communication between the base station and the working drone by adding communication signals at each node to compensate for signal energy loss over travel distance and / or by providing a direct line-of-sight path between the base station and the working drone. However, this system is often used for emergency communication or other mission purposes, and no system capable of routine operation has been observed.

[0005] Because large volumes of data require stable connections over extended periods, existing UAV communication relay systems are feasible for transmitting small text data such as SMS messages. However, they pose a significant challenge to endurance when handling image and video data. Furthermore, in current technologies, UAV systems typically act as storage nodes after data collection, downloading the data only after returning to the takeoff point and landing. This method severely limits data timeliness. On the other hand, maintaining high-throughput communication speeds requires high energy consumption, leading to power supply problems for ground data acquisition terminals in remote areas where external power connections are difficult.

[0006] Therefore, there is a need to develop high-performance data transmission systems with high communication capacity and low terminal power consumption, especially when the amount of terminal data surges, to achieve long-term maintenance-free deployment of ground terminals and effective massive data recovery, and to meet the practical application needs of routine operations. Summary of the Invention

[0007] The purpose of this invention is to provide an air-ground collaborative environmental monitoring system and method to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] Land-based collaborative environmental monitoring systems and methods, including:

[0010] The sensing end, carrier end, control end, cloud end, and application end each construct a bidirectional communication transmission network, which executes two types of data flows:

[0011] Monitoring data flows from the sensing end through the carrier end and the control end to the cloud and the application end, while task data flows from the application end through the cloud and the control end to the carrier end and the sensing end.

[0012] The sensing end is configured with an intelligent gateway, and the carrier end is configured with a communication load unit. The intelligent gateway and the communication load unit first establish a low-power wireless network connection by waking up the communication module, and then wake up the high-speed communication module to establish a high-speed communication connection.

[0013] The carrier and control terminals establish a data communication link via a microwave radio.

[0014] Preferably, the wake-up communication module is a LoRa module, and the high-speed communication module is a high-frequency Wi-Fi module;

[0015] The specific collaborative communication mechanism is as follows:

[0016] When the carrier unit approaches the sensor unit, it first establishes a low-power connection through the LoRa module and sends a wake-up command. After the sensor unit responds, it activates the Wi-Fi module to build a high-speed data transmission link.

[0017] Preferably, the sensing end includes a plurality of sensors or monitoring devices, and the smart gateway enables device access through a multi-protocol interface, specifically including:

[0018] (1) RS485 or RS232 interface based on Modbus protocol, used for wired connection of traditional sensors such as temperature, humidity and water quality;

[0019] (2) The wireless interface of the MQTT server supports wireless access for devices using one or more of the following protocols: WiFi, ETH, LoRa, or Zigbee;

[0020] (3) By mounting an SD memory card reading expansion module, the SD memory card reading expansion module is equipped with an SD card slot to connect to an SD card, and leads to connect to the SD card slots of other monitoring devices to share the memory card reading interface; the GPIO interface receives the switching command from the main control module to realize the mounting and switching of the built-in SD card of the smart gateway and the SD card of the external monitoring device, and then transmits the monitoring data in the SD card to the storage unit of the smart gateway through the SPI or SDIO interface.

[0021] Preferably, the smart gateway is configured with a solar power supply unit and a power consumption management module; the solar power supply unit includes a photovoltaic panel and a lithium iron phosphate battery, and the power consumption management module automatically switches between working mode, idle mode and sleep mode by judging the number of tasks and the duration.

[0022] Preferably, the carrier aircraft adopts a pure electric compound wing UAV platform, equipped with low-altitude remote sensing equipment and an optoelectronic pod. The low-altitude remote sensing equipment is used to perform low-altitude inspection operations simultaneously, and the optoelectronic pod is connected to the control terminal in conjunction with a microwave radio to acquire low-altitude images in real time and remotely observe them at the control terminal.

[0023] Preferably, when the carrier aircraft approaches the ground sensing terminal location, it establishes a high-throughput communication link by waking up the communication module and connecting to the high-speed communication module. The carrier aircraft hovers over the location and uses a directional antenna to quickly retrieve the sensing terminal data.

[0024] When dealing with multiple ground sensor nodes in a wide-area environment, flight path planning enables the aircraft to continuously inspect different ground sensor nodes.

[0025] The integrated air-ground environmental monitoring method of the integrated air-ground environmental monitoring system includes the following steps:

[0026] Step S1, Regional gridded deployment: Divide the area to be monitored into several grids, deploy sensors at each grid location, and record the latitude and longitude coordinates of the location;

[0027] Step S2, Multi-source data acquisition: The sensor end acquires ground point data, and the aircraft end acquires regional remote sensing image data according to the planned flight path;

[0028] Step S3, Spatiotemporal Data Fusion: Based on temporal interpolation and spatial resampling algorithms, point data and image data are correlated in a spatiotemporal manner to generate a dataset;

[0029] Step S4, Data Application: The dataset is stored and analyzed in the cloud, and then visualized and alerted for anomalies through the application.

[0030] Preferably, the data recovery process on the carrier side in step S2 is as follows:

[0031] S21. The carrier aircraft arrives at an altitude of 50-100m above the sensor location along a preset route, hovers, and aligns with the sensor via a directional antenna.

[0032] S22. Start the LoRa wake-up module, send a wake-up frame containing the target gateway ID, and activate the 5GHz Wi-Fi module after receiving the response;

[0033] S23. Download the data stored on the sensor at a rate of ≥10Mbps, release the connection and proceed to the next node after the download is complete;

[0034] S24. In normal scenarios, data is transmitted to the control terminal after returning to base; in live streaming scenarios, data is transmitted back in real time via microwave radio.

[0035] Preferably, the spatiotemporal data fusion in step S3 employs the following algorithm:

[0036] Time alignment: Linear interpolation is used to unify asynchronous data to the same timestamp. Linear interpolation is used to unify discrete point data from the sensor end and remote sensing data from the carrier end to the same time base. The linear interpolation formula used is:

[0037] ,

[0038] in, Interpolated data corresponding to the target timestamp;

[0039] , These are two adjacent measured data points before and after the target time.

[0040] , The timestamps of adjacent measured data;

[0041] The target timestamp that needs to be aligned;

[0042] Spatial alignment employs Kriging interpolation to expand point data into surface data matching the resolution of the remote sensing image. Kriging interpolation is used to expand the coordinate data of the sensing endpoints into surface data matching the pixel grid of the remote sensing image, achieving spatial scale uniformity. The Kriging interpolation formula used is:

[0043]

[0044] Constraints:

[0045]

[0046] in, For the grid points to be interpolated The estimated value;

[0047] For the first Weighting coefficients for each sensing endpoint;

[0048] For the first Measured data at each sensing point;

[0049] The number of sensor endpoints participating in the interpolation;

[0050] Fusion Verification: The consistency of corresponding raster data is determined by KL-difference values. Fusion calculations are performed using the KL-difference value calculation formula to assess the consistency between aerial remote sensing data and ground-based sensor data, avoiding interference from outliers in the fusion results. The KL-difference value calculation formula is as follows:

[0051]

[0052] in, This is the KL-difference value, which takes a value ≥ 0. The smaller the value, the higher the data consistency.

[0053] This represents the probability distribution of data from ground-based sensors.

[0054] The probability distribution of aerial remote sensing inversion data;

[0055] This represents the number of grid cells.

[0056] Compared with the prior art, the beneficial effects of the present invention are:

[0057] The system and method of this invention require no wiring or signal tower construction, reducing environmental impact and construction costs; the unattended terminal equipment requires no maintenance for extended periods, reducing outdoor workload and lowering operation and maintenance costs.

[0058] The system of this invention is compatible with different data types and has high scalability. The bottom-surface monitoring terminal, composed of sensing ends, is equipped with multiple data transmission modes, including: general electrical interfaces such as RS485 and RS232 based on the Modbus communication protocol, which can directly connect to various commonly used sensors, such as temperature and humidity sensors and water quality probes; it uses an MQTT server running through a smart gateway to subscribe to complete sets of monitoring equipment supporting communication protocols such as WiFi / ETH / Lora / Zigbee via the MQTT protocol, enabling wireless data acquisition from the monitoring equipment; and the smart gateway uses an SD memory card reading expansion module to transfer monitoring data from the SD card to the smart gateway's storage unit.

[0059] The system of this invention can achieve high-speed communication of >10Mbps to recover large-capacity non-text data such as images; it can quickly acquire data and even broadcast data in real time to ensure timeliness; it can achieve normalized highly autonomous operation, long-distance coverage of >10km, and continuous recovery of multiple nodes. In one embodiment, the wake-up communication module uses LoRa technology, and its power consumption is almost negligible compared to other monitoring devices. It can achieve a connection within a 2km range, facilitating remote handshake between the carrier aircraft and the ground sensor. The high-speed communication module uses a 5GHz high-frequency high-power Wi-Fi module in conjunction with a directional antenna to achieve high-speed communication within a 500m range to ensure data transmission rate, ultimately achieving low-power operation of the ground terminal in daily operations and stable and efficient data transmission during large-capacity data transmission. Sensor data is transmitted back to the ground control terminal in real time via microwave radio, improving the timeliness of data utilization. The carrier aircraft is a pure electric compound wing model, which can meet the requirement of long-duration flight of at least >3 hours per sortie, greatly increasing the distance that the operation can cover.

[0060] The method of this invention can realize integrated air-ground collaborative monitoring and synchronous collection and application of multi-source data in a region. Attached Figure Description

[0061] Figure 1 This is a schematic diagram of the architecture and communication link design of the air-ground collaborative environmental monitoring system described in this invention;

[0062] Figure 2 This is a schematic diagram of the hardware module connection structure of the air-ground collaborative environmental monitoring system described in this invention;

[0063] Figure 3 This is a schematic diagram of the topology of the air-ground collaborative environmental monitoring system described in this invention;

[0064] Figure 4 This is a schematic diagram of data transmission based on the MQTT protocol in the air-ground collaborative environmental monitoring system described in this invention;

[0065] Figure 5 This is a schematic diagram of the extended connection of the storage module described in this invention;

[0066] Figure 6 This is a schematic diagram of the connection structure of the smart gateway hardware module described in this invention;

[0067] Figure 7 This is a structural diagram of the compound-wing UAV described in this invention;

[0068] Figure 8 This is a schematic diagram of the connection structure of the carrier-side hardware module described in this invention;

[0069] Figure 9 This is a schematic diagram of the connection structure of the remote ground control terminal module according to the present invention;

[0070] Figure 10 This is a flowchart illustrating the data recovery operation performed by the carrier aircraft as described in this invention.

[0071] Figure 11 This is a physical diagram of the main sensor-end micro base station of Embodiment 1 of the present invention;

[0072] Figure 12 This is the route planning screen in Embodiment 2 of the present invention;

[0073] Figure 13 This is a screenshot of the regional environmental information analysis in Embodiment 2 of the present invention;

[0074] Figure 14 This is a live streaming application scenario image from Embodiment 2 of the present invention;

[0075] Figure 15 This is another live streaming application scenario in Embodiment 2 of the present invention. Detailed Implementation

[0076] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0077] like Figure 1-15 As shown, the air-ground collaborative environmental monitoring system includes:

[0078] The sensing end, carrier end, control end, cloud end, and application end each construct a bidirectional communication transmission network, which executes two types of data flows:

[0079] Monitoring data flows from the sensing end through the carrier end and the control end to the cloud and the application end, while task data flows from the application end through the cloud and the control end to the carrier end and the sensing end.

[0080] The sensing end is equipped with a smart gateway, and the carrier end is equipped with a communication load unit. The smart gateway and the communication load unit first establish a low-power wireless network connection by waking up the communication module, and then wake up the high-speed communication module to establish a high-speed communication connection.

[0081] The connection design of each hardware module of the system is as follows: Figure 2 As shown, the sensing end consists of a smart gateway that connects various sensors or other complete sets of monitoring equipment; the carrier end is a compound wing type UAV, equipped with a load unit that communicates with the smart gateway; the carrier is remotely controlled by a ground control terminal (UAV ground station) and connects to the external network through the ground control terminal;

[0082] The carrier and control units establish a data communication link via a microwave radio.

[0083] like Figure 6 As shown, a wake-up communication module and a high-speed communication module are built between the smart gateway and the carrier terminal, respectively. The wake-up communication module is a LoRa module and the high-speed communication module is a high-frequency Wi-Fi module. When the carrier terminal approaches the ground sensor terminal from a relatively far distance, a connection can be established to remotely wake up the high-speed communication module of the ground sensor terminal, thereby establishing a short-range, high-power, and high-speed Wi-Fi transmission.

[0084] The specific collaborative communication mechanism is as follows:

[0085] When the carrier unit approaches the sensor unit, it first establishes a low-power connection through the LoRa module and sends a wake-up command. After the sensor unit responds, it activates the Wi-Fi module to build a high-speed data transmission link.

[0086] The wake-up communication module uses LoRa technology, making its power consumption negligible compared to other monitoring devices. It can achieve a connection range of 2km, facilitating remote handshaking between the carrier aircraft and the ground sensor. The high-speed communication module uses a 5GHz high-frequency, high-power Wi-Fi module in conjunction with a directional antenna to achieve high-speed communication within a 500m range, ensuring data transmission rates. Ultimately, this achieves low-power operation on the ground side during daily use and stable and efficient data transmission.

[0087] The wake-up communication module employs a communication link wake-up algorithm, using a preamble duration and sleep cycle matching formula to ensure that the LoRa wake-up signal can be accurately captured by the smart gateway in sleep mode, balancing wake-up success rate and power consumption. Preamble duration and sleep cycle matching formula:

[0088]

[0089] in,

[0090] The duration of the LoRa wake-up frame preamble (≥100ms).

[0091] Set the sleep cycle for the smart gateway (default 5 seconds).

[0092] Sets the periodic wake-up listening duration for the gateway (default 10ms).

[0093] The system's network topology is as follows: Figure 3As shown, the ground control terminal (UAV ground station) remotely controls the carrier aircraft to fly and inspect along the route in the operating environment through a data communication link composed of microwave radios. When the carrier aircraft approaches the intelligent gateway of the sensing terminal, it establishes a wireless data transmission link network based on Wifi / Wifi-halow with the intelligent gateway and transmits the ground monitoring data to the carrier aircraft payload unit through the MQTT message protocol and FTP file transfer protocol.

[0094] After the carrier aircraft completes all data retrieval tasks, the ground control station controls the UAV to return to the management environment. The carrier aircraft and the ground station exchange data via Wi-Fi, USB or a pluggable data card, and finally upload the monitoring data to the cloud.

[0095] For applications where ground sensors require live streaming, the carrier aircraft acts as a relay node. After obtaining ground data, it transmits it in real time to the ground control station via microwave radio and then connects to the network remotely.

[0096] In existing technologies, multiple sets of different types of equipment are often required to obtain different types of environmental data, which greatly limits the application of systems in specific scenarios and the recovery of increasingly rich and massive amounts of data. Furthermore, due to different data formats and the lack of necessary correlation between data, it is difficult to centrally manage and apply the obtained data results.

[0097] The ground monitoring terminal of this invention develops an intelligent gateway for centralized operation and management of remote ground sensing terminals.

[0098] The intelligent gateway integrates multiple data transmission modes and is compatible with most commonly used sensors or other monitoring devices in existing products. It enables access to different types of ground monitoring devices and unifies data formats, completing data acquisition, access, and transfer control.

[0099] The sensing end includes several sensors or monitoring devices, and the smart gateway enables device access through multi-protocol interfaces, specifically including:

[0100] (1) RS485 or RS232 interface based on Modbus protocol, used for wired connection of traditional sensors such as temperature, humidity and water quality;

[0101] (2) The wireless interface of the MQTT server supports wireless access for devices using one or more of the following protocols: WiFi, ETH, LoRa, or Zigbee. The smart gateway runs the MQTT server and subscribes to complete sets of monitoring equipment that support communication protocols such as WiFi / ETH / Lora / Zigbee using the MQTT protocol. Data is obtained from the monitoring equipment through wireless connection, as follows: Figure 4 As shown;

[0102] (3) By mounting an SD memory card reading expansion module, the SD memory card reading expansion module is equipped with an SD card slot to connect to an SD card, and leads to connect to the SD card slots of other monitoring devices, sharing the memory card reading interface; the GPIO interface receives the switching command from the main control module to realize the mounting and switching between the built-in SD card of the smart gateway and the SD card of the external monitoring device, and then transmits the monitoring data in the SD card to the storage unit of the smart gateway through the SPI or SDIO interface, such as Figure 5 As shown.

[0103] The smart gateway is equipped with a solar power supply unit and a power management module. The solar power supply unit includes a photovoltaic panel and a lithium iron phosphate battery. The power management module determines the number of tasks and the duration of the task to automatically switch between working mode, idle mode and sleep mode. It also manages the power supply and sleep of different modules to achieve long-term power supply to each device, thus avoiding the trouble of frequent battery replacements in traditional devices and enabling maintenance-free autonomous operation.

[0104] The power management module adopts a smart gateway low-power management algorithm that uses a sleep-wake trigger formula to dynamically determine whether to enter sleep mode based on the workload and battery level, thus achieving long-term maintenance-free operation.

[0105] Sleep / wake trigger formula:

[0106]

[0107] in, This is the smart gateway operating mode;

[0108] The number of tasks to be processed (such as data collection and upload tasks);

[0109] The threshold for the number of tasks (default 1);

[0110] This refers to the duration of the idle mode.

[0111] This is the idle timeout threshold (default 30 minutes).

[0112] This represents the remaining battery charge percentage.

[0113] , These are the high and low battery thresholds (80% and 20%, respectively).

[0114] To further reduce power consumption, a low-power, wake-up-only operating mode is designed for the high-speed data transmission link between the ground sensing end and the carrier end, thereby reducing the pressure on the ground power supply.

[0115] To address the issues of existing research primarily employing multi-rotor UAVs, which have limited flight ranges to 3-5 kilometers, and the extremely high operational barriers and scheduling difficulties associated with application-level UAV systems, this invention utilizes a pure electric compound wing aircraft as its carrier. Figure 7 As shown, the aircraft operates in two modes: rotorcraft mode for stable autonomous takeoff and landing, and fixed-wing mode for higher energy efficiency during operations. The aircraft is designed for long-duration flights of at least 3 hours per sortie. Equipped with a flight control system, it enables manual-free autonomous takeoff and landing and autonomous inspection operations along preset routes, improving operational efficiency and reducing daily flight risks.

[0116] The carrier aircraft adopts a pure electric compound wing UAV platform, equipped with low-altitude remote sensing equipment and an electro-optical pod. The low-altitude remote sensing equipment is used to carry out low-altitude inspection operations simultaneously, while the electro-optical pod, combined with a microwave radio, connects to the control terminal to acquire low-altitude images in real time and conduct remote observation at the control terminal.

[0117] like Figure 8 and 9 As shown, in addition to a communication payload unit (including a wake-up communication module and a high-speed communication module) for connecting to ground sensors, the carrier aircraft also carries low-altitude remote sensing equipment for simultaneous low-altitude inspection operations. It is equipped with an electro-optical pod combined with a microwave radio for connection to the ground control terminal, enabling real-time acquisition of low-altitude images and remote observation from the ground control terminal. Furthermore, the recovered ground sensor data and image data are transmitted back to the ground control terminal in real time via microwave radio, improving data utilization efficiency.

[0118] When the carrier aircraft cruises close to the ground-based sensor location, it establishes a high-throughput communication link by waking up the communication module and connecting to the high-speed communication module. The carrier aircraft then hovers over the location and uses a directional antenna to quickly retrieve the sensor data.

[0119] When dealing with multiple ground sensor nodes in a wide-area environment, flight path planning enables the aircraft to continuously inspect different ground sensor nodes.

[0120] In terms of route planning, the aircraft-side route planning adopts a multi-node coverage path optimization objective function. Based on the Sparrow Search Algorithm (SSA), the shortest path planning for multiple sensor nodes is achieved under the premise of satisfying obstacle avoidance and endurance constraints.

[0121] formula:

[0122]

[0123] Constraints:

[0124]

[0125]

[0126]

[0127] in, The path cost function (which needs to be minimized);

[0128] , , These are weighting coefficients (corresponding to path length, high security, and mobility, respectively).

[0129] The total path length (normalized).

[0130] The minimum safe distance between flight altitude and terrain (normalized).

[0131] This is the sum of path deflection angles (normalized to reflect maneuverability constraints).

[0132] This represents the maximum range of the carrier aircraft.

[0133] Minimum safe flight altitude (≥50m).

[0134] The specific data recovery process performed on the carrier side is as follows: Figure 10 As shown, the integrated air-ground environmental monitoring method includes the following steps:

[0135] Step S1, Regional gridded deployment: Divide the area to be monitored into several grids, deploy sensors at each grid location, and record the latitude and longitude coordinates of the location;

[0136] Step S2, Multi-source data acquisition: The sensor end acquires ground point data, and the aircraft end acquires regional remote sensing image data according to the planned flight path;

[0137] The data recovery process on the carrier side in step S2 is as follows:

[0138] S21. The carrier aircraft arrives at an altitude of 50-100m above the sensor location along a preset route, hovers, and aligns with the sensor via a directional antenna.

[0139] S22. Start the LoRa wake-up module, send a wake-up frame containing the target gateway ID, and activate the 5GHz Wi-Fi module after receiving the response;

[0140] S23. Download the data stored on the sensor at a rate of ≥10Mbps, release the connection and proceed to the next node after the download is complete;

[0141] S24. In normal scenarios, data is transmitted to the control terminal after returning to base; in live streaming scenarios, data is transmitted back in real time via microwave radio.

[0142] Step S3, Spatiotemporal Data Fusion: Based on temporal interpolation and spatial resampling algorithms, point data and image data are correlated in a spatiotemporal manner to generate a dataset;

[0143] The spatiotemporal data fusion in step S3 employs the following algorithm:

[0144] Time alignment: Linear interpolation is used to unify asynchronous data to the same timestamp. Linear interpolation is used to unify discrete point data from the sensor end and remote sensing data from the carrier end to the same time base. The linear interpolation formula used is:

[0145] ,

[0146] in, Interpolated data corresponding to the target timestamp;

[0147] , These are two adjacent measured data points before and after the target time.

[0148] , The timestamps of adjacent measured data;

[0149] The target timestamp that needs to be aligned;

[0150] Spatial alignment employs Kriging interpolation to expand point data into surface data matching the resolution of the remote sensing image. Kriging interpolation is used to expand the coordinate data of the sensing endpoints into surface data matching the pixel grid of the remote sensing image, achieving spatial scale uniformity. The Kriging interpolation formula used is:

[0151]

[0152] Constraints:

[0153]

[0154] in, For the grid points to be interpolated The estimated value;

[0155] For the first The weighting coefficients of each sensing point (calculated from spatial distance and variogram);

[0156] For the first Measured data at each sensing point;

[0157] The number of sensor endpoints participating in the interpolation;

[0158] Fusion Verification: The consistency of corresponding raster data is determined by KL-difference values. Fusion calculations are performed using the KL-difference value calculation formula to assess the consistency between aerial remote sensing data and ground-based sensor data, avoiding interference from outliers in the fusion results. The KL-difference value calculation formula is as follows:

[0159]

[0160] in, This is the KL-difference value (relative entropy), with a value ≥ 0. The smaller the value, the higher the data consistency.

[0161] This represents the probability distribution of ground-based sensor data (such as the concentration distribution within a grid).

[0162] The probability distribution of aerial remote sensing inversion data;

[0163] This refers to the number of grid cells;

[0164] Step S4, Data Application: The dataset is stored and analyzed in the cloud, and then visualized and alerted for anomalies through the application. Specific Implementation Example 1:

[0166] like Figure 11 The main components of the sensor-end micro base station are as follows:

[0167] 1) Solar power panels

[0168] The dimensions are approximately 40cm*100cm, with a full load power of 40W; the distance between the solar power panel and the micro base station is approximately 20m; the solar power panel has passed the power meter test and is required to provide ≥ 200 mA power; the battery currently uses a 22Ah lithium iron phosphate battery with an operating temperature of 0-60°C, and because it has an aluminum shell, it is explosion-proof.

[0169] 2) Sensor

[0170] It includes four environmental monitoring sensors (light, temperature, humidity, and air pressure).

[0171] 3) Smart Gateway

[0172] There are three operating modes: 1) Hibernation mode (timed full shutdown, 2-3 years); 2) Low-level operating mode (main control on, beacon on, packaged sensor terminal data and waiting to receive wake-up signal, can run for about 200 days); 3) Operating mode (connect to the drone terminal for data transmission, more than 20 days).

[0173] There are two wake-up mechanisms: 1) beacon wake-up (wake-up based on drone beacon signals); 2) timed wake-up (wake-up based on timed tasks).

[0174] It features OTA update capability, allowing for updates to the smart gateway software and firmware.

[0175] It connects to four environmental monitoring sensors (light, temperature, humidity, and air pressure) to perform continuous environmental monitoring and monitor the operation status of the smart gateway.

[0176] It can also support up to 4 infrared trigger cameras at the same time, and theoretically, after modification, it can support up to 16 cameras.

[0177] The outer shell is coated and has an IP68 waterproof rating.

[0178] 4) Infrared camera

[0179] The data transmission wiring is complete, and the interface is waterproofed; the connection distance is within 30m. Specific Implementation Example 2:

[0181] Integrated air-to-ground monitoring methods include:

[0182] 1) Divide the wide-area environment to be monitored into multiple grids, and deploy ground sensors in each grid according to different locations.

[0183] 2) Based on the distribution of ground sensors, first set up the flight path plan, such as... Figure 1 As shown in Figure 2.

[0184] 3) The aircraft-mounted orthophoto camera conducts low-altitude patrols along a pre-set flight path to obtain high-resolution overall image data covering a wide area. The ground-based sensor acquires detailed and comprehensive local ground data. The control or application end uses the ground-based sensor locations as sample points and combines geographic information with the two data systems to analyze the environmental information of the entire area, such as... Figure 13 As shown.

[0185] 4) In addition, for application scenarios requiring live streaming at the ground sensing end, the carrier aircraft acts as a relay node. After obtaining ground data, it transmits it in real time to the ground control end via microwave radio, and then directly transmits it remotely to the cloud and application end via network connection, such as... Figure 14 and 15 .

[0186] 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. An air-ground collaborative environmental monitoring system, characterized by, Comprise: Sensing end, carrier end, control end, cloud end and application end, each node constructs a two-way communication transmission network, and the transmission network executes two types of data flow: Monitoring data flows from the sensing end to the cloud end and the application end through the carrier end and the control end, and task data flows from the application end to the carrier end and the sensing end through the cloud end and the control end; The sensing end is configured with an intelligent gateway, the carrier end is configured with a communication load unit, and the intelligent gateway and the communication load unit first construct a low-power wireless network connection through a wake-up communication module, and then wake up a high-speed communication module to construct a high-speed communication connection; The carrier end and the control end construct a graph communication link through a microwave radio station.

2. The air-ground collaborative environmental monitoring system of claim 1, wherein, The wake-up communication module is a LoRa module, and the high-speed communication module is a high-frequency Wi-Fi module; The cooperative communication mechanism specifically is: When the carrier end is close to the sensing end, first establish a low-power connection through the LoRa module and send a wake-up instruction, and after the sensing end responds, activate the Wi-Fi module to construct a high-speed data transmission link.

3. The air-ground collaborative environmental monitoring system of claim 1, wherein, The sensing end comprises a plurality of sensor devices or monitoring equipment, and the intelligent gateway realizes device access through a multi-protocol interface, specifically comprising: (1) RS485 or RS232 interface based on Modbus protocol, used for wired connection of traditional sensors such as temperature and humidity and water quality; (2) wireless interface running an MQTT server, supporting wireless access of devices supporting one or more of WiFi, ETH, LoRa or Zigbee protocols; (3) SD memory card reading expansion module, which is provided with an SD card slot connected to an SD card, and leads to other monitoring equipment SD card slot to share the storage card reading interface; The switching instruction of the main control module is received by the GPIO interface to realize the mounting switching of the built-in SD card of the intelligent gateway and the external monitoring equipment SD card, and then the monitoring data in the SD card is transmitted to the storage unit of the intelligent gateway through the SPI or SDIO interface.

4. The air-ground collaborative environmental monitoring system of claim 3, wherein, The intelligent gateway is configured with a solar power supply unit and a power consumption management module; The solar power supply unit comprises a photovoltaic panel and a lithium iron phosphate battery, and the power consumption management module realizes automatic switching of working mode, idle mode and sleep mode through task quantity threshold and duration.

5. The air-ground synergistic environmental monitoring system of claim 1, wherein, The carrier end adopts a pure electric composite wing unmanned aerial vehicle platform, carries low-altitude remote sensing equipment and an optoelectronic pod, the low-altitude remote sensing equipment is used for synchronous low-altitude inspection operation, and the optoelectronic pod is connected to the control end through a microwave radio station to realize real-time low-altitude image acquisition and remote observation at the control end.

6. The air-ground collaborative environmental monitoring system of claim 1, wherein, When the carrier end cruises close to the ground sensing end site, the high-throughput communication link is established by connecting the wake-up communication module to wake up the high-speed communication module, and the carrier end hovers in the air above the site and combines a directional antenna to recover the sensing end data at high speed; For multiple ground sensing end nodes in a wide area environment, the carrier end continuously inspects different ground sensing end nodes through route planning.

7. The air-ground integrated environment monitoring method of the air-ground integrated environment monitoring system according to any one of claims 1-6, characterized in that, The method comprises the following steps: Step S1, regional gridding deployment: divide the area to be monitored into a plurality of grids, and arrange sensing ends at the grid sites, and record the latitude and longitude coordinates of the sites; Step S2, multi-source data collection: the sensing end collects ground point data, and the carrier end collects regional remote sensing image data according to the planned route; Step S3, spatio-temporal data fusion: based on the time interpolation and spatial resampling algorithm, the point data and image data are associated according to the spatio-temporal consistency to generate a data set; Step S4, data application: the data set is stored and analyzed in the cloud, and visual display and abnormal early warning are realized through the application end. 8.The air-ground integrated environment monitoring method of claim 7, The data recovery process of the carrier end in step S2 is as follows: S21, the carrier end reaches the sensing end site at an altitude of 50-100m above the sensing end according to the preset route, hovers and aligns the sensing end through the directional antenna; S22, start the LoRa wake-up module, send the wake-up frame containing the target gateway ID, and activate the 5GHz Wi-Fi module after receiving the response; S23, download the sensing end storage data at a speed of ≥10Mbps, release the connection after downloading is completed, and go to the next node; S24, transmit data to the control end after returning under normal circumstances, and transmit data in real time through the microwave radio under live broadcast scenario.

9. The method of claim 7, wherein the method further comprises: The spatio-temporal data fusion of step S3 adopts the following algorithm: Time alignment: linear interpolation method is used to unify non-synchronous data to the same time stamp, linear interpolation method is used to unify the discrete point data of the sensing end and the remote sensing data of the carrier end to the same time reference, and the linear interpolation formula used by the linear interpolation method is: ， wherein, interpolation data corresponding to the target timestamp; , is the two measured data adjacent to the target time; , timestamp of the adjacent measured data; Target time stamp for which alignment is required; Kriging interpolation method is used to expand the point data into surface data matched with the resolution of remote sensing image, Kriging interpolation method is used to expand the point coordinate data of the sensing end into surface data matched with the image element grid of remote sensing image, realize spatial scale unification, Kriging interpolation formula used by Kriging interpolation method is: Constraint condition: wherein, is an estimated value of the grid point to be interpolated; is an estimated value of the grid point to be interpolated; is the weight coefficient for the first sensing end site; The measured data for the first sensing end site; number of sensing end sites participating in interpolation; Fusion verification: the consistency of corresponding grid data is judged by KL-difference value, fusion calculation is performed through KL-difference value calculation formula, which is used to judge the consistency of aerial remote sensing data and ground sensing data, avoid abnormal value interference to fusion result, KL-difference value calculation formula is: wherein, is the KL-divergence value, taking values ≥ 0, the smaller the value the higher the data consistency; a probability distribution of the ground sensor end data; a probability distribution for the remote sensing inversion data; is the number of grid cells.

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