A multi-unmanned aerial vehicle internet of things data acquisition method based on LoRa communication

Abstract

The application discloses a kind of multi-unmanned aerial vehicle internet of things data acquisition methods based on LoRa communication, for large-scale network connection limited area.The method first deploys a group of full power unmanned aerial vehicle from ground station, while considering its energy consumption in data acquisition process;Second, unmanned aerial vehicle targets according to the GPS signal positioning of data acquisition end, and hovers at target position;Then, unmanned aerial vehicle wakes up data acquisition end and receives the data sent by it.After completing data acquisition, unmanned aerial vehicle continues to fly to the next target point.In view of the target area is broad, multiple unmanned aerial vehicles need to work together to optimize the execution efficiency of data acquisition task;Finally, unmanned aerial vehicle returns to ground station, and comprehensively outputs data acquisition result and the energy consumption data of all unmanned aerial vehicles.The application aims to reduce the energy consumption of unmanned aerial vehicle and data acquisition end, improve data acquisition efficiency to maintain data freshness, help to improve decision quality and response speed, suitable for low-power and network connection limited application scenarios.

Description

TECHNICAL FIELD

[0001] The present application relates to a multi-unmanned aerial vehicle Internet of Things data acquisition method based on LoRa communication, belonging to the field of unmanned aerial vehicle-Internet of Things. BACKGROUND

[0002] In recent years, with the rapid development of Internet of Things technology and the deepening of the concept of "Internet of Everything", researchers worldwide have increasingly focused on Internet of Things (IoT) device data acquisition technology. The sharp increase in the number of sensor devices has placed higher demands on data acquisition and transmission, especially in data-intensive application scenarios, where system efficiency and flexibility are particularly critical. For Internet of Things devices deployed in remote, harsh environments or dangerous areas, traditional manual data acquisition methods are inefficient and difficult to ensure real-time and security.

[0003] To solve the bottleneck of communication data transmission, unmanned aerial vehicle-assisted communication technology has gradually become an effective way to solve the problem of large-scale Internet of Things device data acquisition. Compared with traditional fixed base station deployment mode, unmanned aerial vehicles can dynamically optimize coverage by adjusting flight trajectories flexibly, providing efficient and low-latency data transmission services for Internet of Things devices in complex environments such as deserts and mountainous areas. This approach not only improves data acquisition efficiency but also greatly enhances the flexibility and adaptability of the system in various uncertain environments. SUMMARY

[0004] The present application provides a multi-unmanned aerial vehicle Internet of Things data acquisition method based on LoRa communication to solve the technical problem of information transmission in areas where stable energy and network connection are limited.

[0005] The present application provides the following technical solutions:

[0006] The method comprises the following steps:

[0007] The ground station system assigns a task target area to a group of unmanned aerial vehicles, the group of unmanned aerial vehicles comprising at least one unmanned aerial vehicle, and the task target area comprising a plurality of target acquisition areas, each target acquisition area having at least one unmanned aerial vehicle.

[0008] S1, a multi-unmanned aerial vehicle-assisted Internet of Things data acquisition system based on LoRa wireless communication is constructed, the multi-unmanned aerial vehicle-assisted Internet of Things data acquisition system device comprising a data collection and processing server of a ground station; an STM32 single-chip microcomputer, a LoRa wireless communication module, a data acquisition sensor, and a power supply device of a data acquisition end; and an unmanned aerial vehicle in communication with the multi-unmanned aerial vehicle-assisted Internet of Things data acquisition system;

[0009] S2, when the unmanned aerial vehicle flies over the data collection terminal area, the data collection terminal position is found based on the GPS signal of the data collection terminal;

[0010] S3, sending a wake-up instruction to the data collection terminal, waiting for the data collection terminal to be woken up and receiving the data sent by the data collection terminal;

[0011] S4, after the data collection terminal is activated, the data collection terminal transmits the current signal strength of the data collection sensor detected to the unmanned aerial vehicle group, establishes communication, and transmits data to the unmanned aerial vehicle group;

[0012] S5, the unmanned aerial vehicle returns to the ground station, and the data collection result and the energy consumption data of all unmanned aerial vehicles are comprehensively output;

[0013] The step S3 specifically comprises the following steps:

[0014] S31, the unmanned aerial vehicle group broadcasts a wake-up instruction to the position of the data collection terminal device based on the position information of the data collection terminal device collected;

[0015] S41, when the wake-up instruction is verified, the data collection terminal is activated;

[0016] S42, the unmanned aerial vehicle group establishes a data communication channel between the unmanned aerial vehicle group and the data collection terminal based on the signal strength;

[0017] S43, the sensor sends the collected data to the unmanned aerial vehicle group;

[0018] In step S42, the data collection terminal is set to transmit data at a constant transmission power only when it is activated by the unmanned aerial vehicle ; otherwise, the data collection terminal will remain in sleep mode to optimize energy consumption. The sensing capability of the unmanned aerial vehicle is defined as its sensing range , and any sensor node within the coverage range is considered to have been sensed, receives a wake-up instruction, and wakes up and uploads its data to the unmanned aerial vehicle. In one time slot, each data collection terminal can only be data collected by one unmanned aerial vehicle. In the time slot , if the data collection terminal is activated by the unmanned aerial vehicle , the maximum transmission rate that can be achieved between them can be represented as:

[0019]

[0020] where, is the system bandwidth; is the received noise power; in the time slot , the unmanned aerial vehicle receives the sensor node Amount of data successfully uploaded To:

[0021]

[0022] Step S5 specifically includes the following: the energy consumption of the UAV is divided into two parts, communication energy and propulsion energy. Since the communication-related energy is relatively small, it can usually be ignored. The consumption of propulsion energy mainly depends on the flight speed and acceleration of the UAV. In the model, it is assumed that the energy consumption during acceleration or deceleration process can be ignored, so for the UAV with a speed of , the consumption of propulsion power can be modeled as follows:

[0023]

[0024] Wherein: is the blade profile power in hover state; is the induced power in hover state; is the tip speed of rotor blade; is the average rotor induced velocity in hover; is the fuselage drag ratio; is the rotor solidity; is the air density; is the area of rotor disc; is the flight speed of the UAV, in hover state, the flight speed of the UAV is 0, the tip speed of rotor blade is equal to the average rotor induced velocity in hover , so the parasitic power is also 0 because it is proportional to the square of the flight speed; at this time, the total power consumption only includes the blade profile power and half of the induced power , because in the induced power term is 0, so the power in hover state is:

[0025]

[0026] In the UAV-assisted Internet of Things data collection, the Age of Information (AoI) is modeled by the following formula in order to more accurately reflect the delay and update rate generated during data transmission. The detailed formula can be expressed as:

[0027]

[0028] Where: the indicator variable : if the data source is at time If the data is updated, ; if the data source At the time If the data is not updated, ; The time of the last update of the data; The time of the last update of the data; The total number of data sources. Using this model can more accurately capture and optimize information freshness in multi-data source systems, ensuring real-time data transmission and processing. BRIEF DESCRIPTION OF DRAWINGS

[0029] Fig. 1 The flow structure diagram of the present application;

[0030] Fig. 2 The unit structure diagram of the present application. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical scheme and advantages of the present application clearer, further detailed description will be given in conjunction with the drawings and examples. It should be understood that the specific examples described herein are only for the purpose of explaining the present application, and should not be regarded as a limitation of the present application.

[0032] In the drawings of the embodiments of the present application, the same or similar reference numerals correspond to the same or similar components. In the description of the present application, it should be understood that the terms such as "upper", "lower", "left", "right", "front", "back" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of description and simplification of the present application, and do not mean that the described device or element must have a specific orientation, be constructed or operated in a specific orientation. Therefore, the positional relationship described in the drawings is only for example and cannot be understood as a limitation of the present application. Those skilled in the art can understand the actual meaning of the above terms according to the specific situation.

[0033] Please refer to Figs. 1-2 The multi- unmanned aerial vehicle Internet of Things data acquisition method based on LoRa communication, specifically comprising the following steps:

[0034] The ground station system assigns a task target area to the unmanned aerial vehicle group; the unmanned aerial vehicle group includes at least one unmanned aerial vehicle; the task target area includes a plurality of target acquisition areas; each target acquisition area has at least one unmanned aerial vehicle.

[0035] Step 1: Construct a multi- UAV assisted Internet of Things data acquisition system based on LoRa wireless communication, the multi- UAV assisted Internet of Things data acquisition system based on LoRa wireless communication device includes a data collection, processing server of a ground station; A data acquisition end of STM32 single-chip, LoRa wireless communication module, data acquisition sensor and power supply device; A UAV in communication with the data acquisition device;

[0036] Step 2: When the UAV flies over the deployment data acquisition end area, find the data acquisition end position based on the data acquisition end GPS signal;

[0037] Step 3: Send a wake-up instruction to the data acquisition end, and wait for the data acquisition to be awakened and receive the data sent by the data acquisition end;

[0038] Step 4: After the data acquisition end is activated, the data acquisition end transmits the current signal strength of the data acquisition sensor detected to the UAV group, establishes communication, and transmits data to the UAV group;

[0039] Step 5: The UAV returns to the ground station and outputs the data acquisition results and the energy consumption data of all UAVs;

[0040] Specifically includes the following steps:

[0041] Step 2.1: Consider that the UAV flies at a fixed height , then its two-dimensional position coordinates in the first time slot are . The UAV moves a distance in a certain direction , where represents the farthest distance that the UAV can move in a time slot.

[0042] Step 3.1: The UAV group broadcasts a wake-up instruction to the location of the data acquisition end device based on the collected location information of the data acquisition end device;

[0043] Step 4.1: When the wake-up instruction is verified, activate the data acquisition end;

[0044] Step 4.2: The UAV group establishes a data connection channel between the UAV group and the data acquisition end based on the signal strength;

[0045] Step 4.3: The sensor sends the collected data to the UAV group;

[0046] In step 4.2, set the data acquisition end to transmit at a constant transmission power transmission; otherwise, the data collection end will remain in sleep mode to optimize energy consumption. The sensing capability of the UAV is defined as its sensing range , any sensor node within the coverage is considered to be sensed, receives the wake-up instruction, wakes up and uploads its data to the UAV. In a time slot, each data collection end can only be data collected by one UAV. In the time slot , if the data collection end is activated by the UAV , the maximum transmission rate that can be achieved between them can be represented as:

[0047]

[0048] wherein, is the system bandwidth; is the received noise power; in the time slot , the amount of data successfully uploaded by the UAV from the sensor node is:

[0049]

[0050] Step 5 specifically includes the following: the energy consumption of the UAV is divided into two parts, communication energy and propulsion energy. Since the communication-related energy is relatively small, it can usually be ignored. The consumption of propulsion energy mainly depends on the flight speed and acceleration of the UAV. In the model, it is assumed that the energy consumption during acceleration or deceleration can be ignored, so for the UAV with a speed of , the consumption of propulsion power can be modeled as follows:

[0051]

[0052] wherein, is the blade profile power in hover state; is the induced power in hover state; is the tip speed of the rotor blade; is the average rotor induced velocity in hover; is the fuselage drag ratio; is the rotor solidity; is the air density; is the rotor disc area; is the flight speed of the UAV, in the hover state, the flight speed of the UAV is 0, the tip speed of the rotor blade is equal to the average rotor induced velocity in hover , so the parasitic power ​Also zero, as it is proportional to the square of the flight speed; at this point, the total power consumption includes only the blade profile power and half of the induced power , as the term in the induced power term is zero, so the power in hover is:

[0053]

[0054] In UAV-assisted IoT data collection, the Age of Information (AoI) is modeled by the following formula to more accurately reflect the delay and update rate generated during data transmission. The detailed formula can be expressed as:

[0055]

[0056] Where: the indicator variable : if the data source updates the data at time , then . If the data source does not update the data at time , then ; is the time when the data was last updated; is the total number of data sources. Using this model can more accurately capture and optimize the information freshness in a multi-data source system, ensuring the real-time nature of data transmission and processing. Therefore, one of the goals of the present invention is to minimize .

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail through the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced equivalently without departing from the spirit and scope of the present invention, and these modifications or replacements should be included in the scope of the claims of the present invention.

Claims

1. A multi-UAV Internet of Things data collection method based on LoRa communication, characterized in that: The ground station system assigns a mission target area to a drone swarm, the drone swarm including at least one drone, the mission target area including a plurality of target collection areas, each target collection area having at least one drone; the method comprising the following steps: S1. Construct a multi-UAV-assisted IoT data acquisition system based on LoRa wireless communication. The multi-UAV-assisted IoT data acquisition system based on LoRa wireless communication includes a data collection and processing server at a ground station; an STM32 single chip, a LoRa wireless communication module, a data acquisition sensor, and an energy supply device at the data acquisition end; and a drone that communicates with the multi-UAV-assisted IoT data acquisition system. S2. When the UAV flies over the area where the data collection terminal is deployed, the location of the data collection terminal is found based on the GPS signal of the data collection terminal; S3, sending a wake-up command to the data acquisition terminal, waiting for the data acquisition terminal to be awakened and receiving the data sent by the data acquisition terminal; S4, after the data acquisition terminal is activated, the data acquisition terminal transmits the current signal strength of the data acquisition sensor detected to the drone group, establishes communication, and transmits the data to the drone group; S5. The UAV returns to the ground station and comprehensively outputs the data collection results and energy consumption data. The energy consumption includes communication energy and propulsion energy. The communication-related energy is relatively small and can be ignored. The propulsion energy consumption mainly depends on the flight speed and acceleration of the UAV. In the modeling process, it is assumed that the energy consumption during acceleration and deceleration can be ignored. For the flight speed of The propulsion power consumption of the UAV can be expressed as: ； in: is the blade profile power in the hovering state; is the induced power in the hovering state; is the tip speed of the rotor blade; is the average rotor induced speed in hover; is the fuselage drag ratio; is the rotor robustness; is the air density; is the area of ​​the rotor disk; Is the flight speed of the drone. In the hovering state, the flight speed of the drone is 0, the tip speed of the rotor blade The average rotor induced speed in hover Equal, parasitic power is also 0 because it is proportional to the square of the flight speed. At this time, the total power consumption only includes the blade profile power and induction power half of the induced power term is 0, so the power in the hovering state is: ； In drone-assisted IoT data collection, the data freshness (Age of Information, AoI) is modeled by the following formula, which can be expressed as: ； Among them: indicator variable : If the data source In time If the data is updated, If the data source In time If no data is updated, ; For data The time when the data was last updated; is the total number of data sources.

2. A multi-UAV Internet of Things data acquisition method based on LoRa communication according to claim 1, characterized in that: The step S3 specifically includes the following steps: S31. The drone group broadcasts a wake-up instruction to the location of the data acquisition terminal device based on the collected location information of the data acquisition terminal device.

3. The multi-UAV Internet of Things data acquisition method based on LoRa communication according to claim 1 is characterized in that: The step S4 specifically includes the following steps: S41, when the wake-up instruction is verified to be successful, activating the data acquisition terminal; S42: The drone group establishes a data communication channel between the drone group and the data acquisition terminal based on the signal strength; S43: The sensor sends the collected data to the drone group.

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