CN119603655A - A multi-UAV Internet of Things data collection method and device based on LoRa communication - Google Patents
A multi-UAV Internet of Things data collection method and device based on LoRa communication Download PDFInfo
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- CN119603655A CN119603655A CN202411797763.3A CN202411797763A CN119603655A CN 119603655 A CN119603655 A CN 119603655A CN 202411797763 A CN202411797763 A CN 202411797763A CN 119603655 A CN119603655 A CN 119603655A
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- H—ELECTRICITY
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- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
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- H—ELECTRICITY
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Abstract
The invention discloses a multi-unmanned aerial vehicle internet of things data acquisition method and device based on LoRa communication, aiming at a region with limited large-scale network connection. The method comprises the steps of firstly deploying a group of unmanned aerial vehicles with full electric quantity to start from a ground station, simultaneously considering energy consumption of the unmanned aerial vehicles in a data acquisition process, secondly, positioning a target according to GPS signals of a data acquisition end and hovering at a target position, and then waking up the data acquisition end by the unmanned aerial vehicles and receiving data sent by the data acquisition end. After the data acquisition is completed, the unmanned aerial vehicle continues to fly to the next target point. And finally, the unmanned aerial vehicle returns to the ground station to comprehensively output the data acquisition result and the energy consumption data of all unmanned aerial vehicles. The invention aims to reduce the energy consumption of the unmanned plane and the data acquisition end, improve the data acquisition efficiency to keep the data freshness, help to improve the decision quality and the response speed, and is suitable for application scenes with low power consumption and limited network connection.
Description
Technical Field
The invention relates to a multi-unmanned aerial vehicle internet of things data acquisition method and device based on LoRa communication, and belongs to the field of unmanned aerial vehicles and the internet of things.
Background
In recent years, with the rapid development of internet of things technology and the deepening of the concept of "internet of everything", researchers in the global area continue to increase in interest in internet of things (IoT) device data acquisition technology. The dramatic rise in the number of sensor devices places higher demands on data acquisition and transmission, especially in data intensive applications, where the efficiency and flexibility of the system becomes critical. For the Internet of things equipment deployed in remote, severe environments or dangerous areas, the traditional manual data acquisition mode is low in efficiency, and real-time performance and safety are difficult to guarantee.
In order to solve the bottleneck of communication data transmission, unmanned aerial vehicle auxiliary communication technology gradually becomes the effective way of solving the difficult problem of large-scale internet of things equipment data acquisition. Compared with the traditional fixed base station deployment mode, the unmanned aerial vehicle can dynamically optimize the coverage range by flexibly adjusting the flight track, and provide high-efficiency and low-delay data transmission service for the Internet of things equipment in complex environments (such as deserts, mountainous areas and the like). The method not only improves the efficiency of data acquisition, but also greatly enhances the flexibility and adaptability of the system in various uncertain environments.
Disclosure of Invention
The invention provides a multi-unmanned aerial vehicle internet of things data acquisition method and device based on LoRa communication, which are used for solving the technical problem that stable energy cannot be provided and information transmission in a region with limited network connection is not realized.
The invention provides the following technical scheme:
The method comprises the following steps:
The ground station system distributes a task target area to the unmanned aerial vehicle group, the unmanned aerial vehicle group comprises at least one unmanned aerial vehicle, the task target area comprises a plurality of target acquisition areas, and each target acquisition area is provided with at least one unmanned aerial vehicle.
S1, constructing a data acquisition system of a multi-unmanned aerial vehicle auxiliary Internet of things based on LoRa wireless communication, wherein the data acquisition system device of the multi-unmanned aerial vehicle auxiliary Internet of things based on LoRa wireless communication comprises a data collection and processing server of a ground station, an STM32 single chip of a data acquisition end, a LoRa wireless communication module, a data acquisition sensor and an energy supply device;
S2, when the unmanned aerial vehicle flies over the deployment data acquisition end area, finding the position of the data acquisition end based on a GPS signal of the data acquisition end;
S3, sending a wake-up instruction to the data acquisition end, waiting for data acquisition to be waken up and receiving data sent by the data acquisition end;
s4, after the data acquisition end is activated, the data acquisition end transmits the detected current signal intensity of the data acquisition sensor to the unmanned aerial vehicle group, communication is established, and data is transmitted to the unmanned aerial vehicle group;
S5, the unmanned aerial vehicle returns to the ground station, and the data acquisition result and the energy consumption data of all unmanned aerial vehicles are comprehensively output;
the step S3 specifically comprises the following steps:
S31, broadcasting a wake-up instruction to the position of the data acquisition end equipment by the unmanned aerial vehicle group based on the acquired position information of the data acquisition end equipment;
s41, when the wake-up instruction passes verification, activating the data acquisition end;
s42, the unmanned aerial vehicle group establishes a data communication channel between the unmanned aerial vehicle group and the data acquisition end based on the signal intensity;
s43, the sensor sends the acquired data to the unmanned aerial vehicle group;
in step S42, the data acquisition terminal is set to perform data transmission at the constant transmission power P m only when activated by the unmanned aerial vehicle, otherwise, the data acquisition terminal will remain in the sleep mode to optimize the energy consumption. The perception capability of the unmanned aerial vehicle is defined as the perception range omega, any sensor node (M epsilon M) in the coverage range is regarded as perceived, and the unmanned aerial vehicle is awakened after receiving an awakening instruction and uploads the data of the awakening instruction to the unmanned aerial vehicle. In one time slot, each data acquisition terminal can only acquire data by one unmanned aerial vehicle. In the time slot n, if the data acquisition terminal m is activated by the unmanned aerial vehicle u, the maximum transmission rate that can be achieved between the two can be expressed as:
Wherein B is the system bandwidth, sigma 2 is the received noise power, and the data quantity lambda u,m (n) successfully uploaded by the unmanned plane u from the sensor node m in the time slot n is as follows:
The step S5 specifically includes the following that the energy consumption of the unmanned aerial vehicle is divided into two parts, communication energy and propulsion energy. Since the communication-related energy is relatively small, it is generally negligible. The consumption of propulsion energy is mainly dependent on the speed and acceleration of the unmanned aerial vehicle. In the model, it is assumed that the energy consumption during acceleration or deceleration is negligible, and therefore, for a drone with a speed V, the consumption of its propulsion power can be modeled as follows:
Wherein P 0 is blade profile power in hover state, pi is induced power in hover state, U tip is tip speed of rotor blade, V 0 is induced speed of average rotor blade in hover state, d 0 is fuselage resistance ratio, s is rotor solidity, ρ is air density, A is area of rotor disk, V is flying speed of unmanned aerial vehicle, in hover state flying speed of unmanned aerial vehicle V is 0, tip speed of rotor blade U tip is equal to induced speed of average rotor blade in hover V 0, therefore parasitic power P parasite is also 0 as it is proportional to square of flying speed, at this time total power consumption only includes half blade profile power P 0 and induced power Pi as the induced power term 0, So the power in hover state is:
In unmanned aerial vehicle assisted internet of things data acquisition, data freshness (Age of Information, aoI) is modeled by the following formula to more accurately reflect delays and update rates generated during data transmission. The detailed formula can be expressed as:
Wherein the indicator variable a i (t) is a i (t) =1 if data source i updated data at time t, a i(t)＝0;τi (t) is the time when data i last updated data if data source i did not update data at time t, and N is the total number of data sources. The information freshness in the multi-data source system can be more accurately captured and optimized by using the model, and the real-time performance of data transmission and processing is ensured.
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FIG. 1 is a schematic diagram of a flow structure of the present invention;
FIG. 2 is a schematic diagram of the unit structure of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages thereof more apparent, the present invention will be described in further detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and should not be taken as limiting the invention.
In the drawings of embodiments of the invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that the terms such as "upper", "lower", "left", "right", "front", "rear", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are merely for convenience in description and simplicity in illustration of the present invention, and do not mean that the described device or element must have a specific orientation, be configured or operated in a specific orientation. Accordingly, the positional relationship depicted in the drawings are for illustration only and are not to be construed as limiting the invention. The actual meaning of the above terms can be understood by those of ordinary skill in the art according to the specific circumstances.
Referring to fig. 1-2, the method and the device for acquiring internet of things data of multiple unmanned aerial vehicles based on LoRa communication, disclosed by the invention, specifically comprise the following steps:
The ground station system distributes task target areas to the unmanned aerial vehicle group, the unmanned aerial vehicle group comprises at least one unmanned aerial vehicle, the task target areas comprise a plurality of target acquisition areas, and each target acquisition area is provided with at least one unmanned aerial vehicle.
The method comprises the steps of 1, constructing a multi-unmanned aerial vehicle auxiliary Internet of things data acquisition system based on LoRa wireless communication, wherein the multi-unmanned aerial vehicle auxiliary Internet of things data acquisition system device based on LoRa wireless communication comprises a data collection and processing server of a ground station, an STM32 single chip of a data acquisition end, a LoRa wireless communication module, a data acquisition sensor and an energy supply device;
Step 2, when the unmanned aerial vehicle flies over the deployment data acquisition end area, finding the position of the data acquisition end based on the GPS signal of the data acquisition end;
Step 3, sending a wake-up instruction to the data acquisition end, waiting for data acquisition to be waken up and receiving the data sent by the data acquisition end;
Step 4, after the data acquisition end is activated, the data acquisition end transmits the detected current signal intensity of the data acquisition sensor to the unmanned aerial vehicle group, communication is established, and data is transmitted to the unmanned aerial vehicle group;
Step 5, the unmanned aerial vehicle returns to the ground station, and the data acquisition result and the energy consumption data of all unmanned aerial vehicles are comprehensively output;
The method specifically comprises the following steps:
Step 2.1 consider that the drone flies at a fixed altitude H, its two-dimensional position coordinates within the nth time slot are q u(n)＝[xu(n),yu (n) ]. Unmanned plane u moves a distance l u(n)∈[0,lmax in a certain direction, where l max represents the furthest distance the unmanned plane can move within a time slot.
Step 3.1, broadcasting a wake-up instruction to the position of the data acquisition end equipment by the unmanned aerial vehicle group based on the acquired position information of the data acquisition end equipment;
step 4.1, when the wake-up instruction passes verification, activating the data acquisition end;
step 4.2, the unmanned aerial vehicle group establishes a data communication channel between the unmanned aerial vehicle group and the data acquisition end based on the signal intensity;
step 4.3, the sensor sends the acquired data to the unmanned aerial vehicle group;
In step 4.2, the data acquisition end is set to perform data transmission with constant transmission power P m only when activated by the drone, otherwise, the data acquisition end will remain in sleep mode to optimize energy consumption. The perception capability of the unmanned aerial vehicle is defined as the perception range omega, any sensor node (M epsilon M) in the coverage range is regarded as perceived, and the unmanned aerial vehicle is awakened after receiving an awakening instruction and uploads the data of the awakening instruction to the unmanned aerial vehicle. In one time slot, each data acquisition terminal can only acquire data by one unmanned aerial vehicle. In the time slot n, if the data acquisition terminal m is activated by the unmanned aerial vehicle u, the maximum transmission rate that can be achieved between the two can be expressed as:
Wherein B is the system bandwidth, sigma 2 is the received noise power, and the data quantity lambda u,m (n) successfully uploaded by the unmanned plane u from the sensor node m in the time slot n is as follows:
Step 5 specifically includes the following that the energy consumption of the unmanned aerial vehicle is divided into two parts, namely communication energy and propulsion energy. Since the communication-related energy is relatively small, it is generally negligible. The consumption of propulsion energy is mainly dependent on the speed and acceleration of the unmanned aerial vehicle. In the model, it is assumed that the energy consumption during acceleration or deceleration is negligible, and therefore, for a drone with a speed V, the consumption of its propulsion power can be modeled as follows:
Wherein P 0 is blade profile power in hover state, pi is induced power in hover state, U tip is tip speed of rotor blade, V 0 is induced speed of average rotor blade in hover state, d 0 is fuselage resistance ratio, s is rotor solidity, ρ is air density, A is area of rotor disk, V is flying speed of unmanned aerial vehicle, in hover state flying speed of unmanned aerial vehicle V is 0, tip speed of rotor blade U tip is equal to induced speed of average rotor blade in hover V 0, therefore parasitic power P parasite is also 0 as it is proportional to square of flying speed, at this time total power consumption only includes half blade profile power P 0 and induced power Pi as the induced power term 0, So the power in hover state is:
In unmanned aerial vehicle assisted internet of things data acquisition, data freshness (Age of Information, aoI) is modeled by the following formula to more accurately reflect delays and update rates generated during data transmission. The detailed formula can be expressed as:
Wherein the indicator variable a i (t) is a i (t) =1 if the data source i updates the data at time t. If data source i does not update data at time t, a i(t)＝0;τi (t) is the time at which data i last updated data, N is the total number of data sources. The information freshness in the multi-data source system can be more accurately captured and optimized by using the model, and the real-time performance of data transmission and processing is ensured. Therefore, one of the objectives of the present invention is to minimize Δ (t).
Finally, it should be noted that the above-mentioned embodiments are only for illustrating the technical solution of the present invention, and are not limiting. Although the invention has been described in detail with reference to preferred embodiments, those skilled in the art will understand that changes and equivalents may be made therein without departing from the spirit and scope of the invention, and such changes and substitutions are intended to be included within the scope of the claims.
Claims (5)
1. A method and a device for acquiring Internet of things data of multiple unmanned aerial vehicles based on LoRa communication are characterized in that a ground station system distributes task target areas to an unmanned aerial vehicle group, the unmanned aerial vehicle group comprises at least one unmanned aerial vehicle, the task target areas comprise a plurality of target acquisition areas, each target acquisition area comprises at least one unmanned aerial vehicle, and the method comprises the following steps:
S1, constructing a data acquisition system of a multi-unmanned aerial vehicle auxiliary Internet of things based on LoRa wireless communication, wherein the data acquisition system device of the multi-unmanned aerial vehicle auxiliary Internet of things based on LoRa wireless communication comprises a data collection and processing server of a ground station, an STM32 single chip of a data acquisition end, a LoRa wireless communication module, a data acquisition sensor and an energy supply device;
S2, when the unmanned aerial vehicle flies over the deployment data acquisition end area, finding the position of the data acquisition end based on a GPS signal of the data acquisition end;
S3, sending a wake-up instruction to the data acquisition end, waiting for data acquisition to be waken up and receiving data sent by the data acquisition end;
s4, after the data acquisition end is activated, the data acquisition end transmits the detected current signal intensity of the data acquisition sensor to the unmanned aerial vehicle group, communication is established, and data is transmitted to the unmanned aerial vehicle group;
S5, the unmanned aerial vehicle returns to the ground station, and the data acquisition result and the energy consumption data of all unmanned aerial vehicles are comprehensively output.
2. The method and device for collecting internet of things data of multiple unmanned aerial vehicles based on LoRa communication according to claim 1, wherein the step S3 specifically comprises the following steps:
S31, broadcasting a wake-up instruction to the position of the data acquisition end equipment by the unmanned aerial vehicle group based on the acquired position information of the data acquisition end equipment.
3. The method and device for collecting internet of things data of multiple unmanned aerial vehicles based on LoRa communication according to claim 1, wherein the step S4 specifically comprises the following steps:
s41, when the wake-up instruction passes verification, activating the data acquisition end;
s42, the unmanned aerial vehicle group establishes a data communication channel between the unmanned aerial vehicle group and the data acquisition end based on the signal intensity;
s43, the sensor sends the acquired data to the unmanned aerial vehicle group.
4. A step S42 according to claim 3, wherein in step S42, the group of unmanned aerial vehicles establishes a data communication channel between the group of unmanned aerial vehicles and the data acquisition terminal based on the signal strength, wherein the data acquisition terminal is set to perform data transmission with constant transmission power P m only when activated by the unmanned aerial vehicle, otherwise, the data acquisition terminal will maintain a sleep mode to optimize energy consumption, the perception capability of the unmanned aerial vehicle is defined as its perception range Ω, any sensor node (M e M) within the coverage area is regarded as perceived, and a wake-up instruction is received to wake up and upload its data to the unmanned aerial vehicle. In one time slot, each data acquisition terminal can only acquire data by one unmanned aerial vehicle. In the time slot n, if the data acquisition terminal m is activated by the unmanned aerial vehicle u, the maximum transmission rate that can be achieved between the two can be expressed as:
Wherein B is the system bandwidth, sigma 2 is the received noise power, and the data quantity lambda u,m (n) successfully uploaded by the unmanned plane u from the sensor node m in the time slot n is as follows:
5. The method and the device for acquiring the Internet of things data of the multiple unmanned aerial vehicles based on the LoRa communication, which are disclosed in claim 1, are characterized in that the step S5 specifically comprises the following steps of dividing the energy consumption of the unmanned aerial vehicles into two parts, namely communication energy and propulsion energy. Since the communication-related energy is relatively small and can be ignored, the consumption of propulsion energy mainly depends on the flying speed and acceleration of the unmanned aerial vehicle, and in the model, the energy consumption in the acceleration or deceleration process is assumed to be negligible, so for the unmanned aerial vehicle with the speed V, the consumption of the propulsion power can be modeled as follows:
Wherein P 0 is blade profile power in hover state, pi is induced power in hover state, U tip is tip speed of rotor blade, V 0 is induced speed of average rotor blade in hover state, d 0 is fuselage resistance ratio, s is rotor solidity, ρ is air density, A is area of rotor disk, V is flying speed of unmanned aerial vehicle, in hover state flying speed of unmanned aerial vehicle V is 0, tip speed of rotor blade U tip is equal to induced speed of average rotor blade in hover V 0, therefore parasitic power P parasite is also 0 as it is proportional to square of flying speed, at this time total power consumption only includes half blade profile power P 0 and induced power Pi as the induced power term 0, So the power in hover state is:
In unmanned aerial vehicle assisted internet of things data acquisition, data freshness (Age ofInformation, aoI) is modeled by the following formula to more accurately reflect delay and update rate generated in the data transmission process, the detailed formula can be expressed as:
The indicating variable a i (t) is that if the data source i updates the data at the time t, a i (t) =1, if the data source i does not update the data at the time t, a i(t)＝0;τi (t) is the last time the data i updates the data, and N is the total number of the data sources, so that the information freshness in the multi-data source system can be more accurately captured and optimized by using the model, and the real-time performance of data transmission and processing is ensured.
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| CN116567563A (en) * | 2023-05-09 | 2023-08-08 | 重庆邮电大学 | A multi-UAV assisted Internet of Things data collection method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20180090013A1 (en) * | 2016-09-23 | 2018-03-29 | Sharp Laboratories Of America, Inc. | Unmanned aircraft and operation thereof |
| CN112383935A (en) * | 2020-11-10 | 2021-02-19 | 大连理工大学 | Design method of cooperative unmanned aerial vehicle data acquisition system based on physical layer security |
| CN114867093A (en) * | 2022-05-17 | 2022-08-05 | 电子科技大学 | Uplink power control method for IoT devices based on drone coordination |
| CN116567563A (en) * | 2023-05-09 | 2023-08-08 | 重庆邮电大学 | A multi-UAV assisted Internet of Things data collection method |
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