Efficient and Secure Transmission Method for Smart City Sanitation UAV Data

Abstract

The present invention relates to the technical field of smart city environmental sanitation, and discloses an efficient and secure data transmission method for environmental sanitation drones in a smart city. This method determines the environmental sanitation drone (the first node) for data to be transmitted and the adjacent environmental sanitation drone (the second node), obtains the transmission parameters of both, calculates the actual delay and the expected delay between the transmission path of the first node at the current moment and the specified historical moment of the second node, and determines a correction amount according to the transmission volume of the second node to improve the expected delay. Based on the delay difference and the encryption parameter at the specified historical moment of the second node, the target encryption parameter at the current moment of the first node is determined, and the data transmission protocol is adjusted. This method can effectively improve the data transmission efficiency of environmental sanitation drones, ensure data security, enhance the adaptive ability of the system to the dynamic network environment, solve the problems of efficiency and security faced by the existing data transmission of environmental sanitation drones, and is applicable to the data transmission scenario in the smart city environmental sanitation business.

Description

Technical Field

[0001] The present invention relates to the technical field of smart city environmental sanitation, and specifically to a method for efficient and secure transmission of data of smart city environmental sanitation drones. Background Art

[0002] At present, with the accelerating process of smart city construction, the intelligent upgrade of the environmental sanitation field has become an important development direction. Environmental sanitation drones play a key role in garbage monitoring, cleaning planning, environmental inspection, etc. due to their flexibility, convenience, wide coverage and other advantages. However, environmental sanitation drones face many severe challenges in the data transmission link, which greatly restricts the effective play of their functions.

[0003] In terms of data transmission efficiency, the environmental sanitation operation environment is complex and diverse, and the signals of drones are easily interfered during flight. High-rise buildings, trees and other obstacles in the city will block the signal propagation, resulting in weakened signal strength, transmission interruption or increased delay. In some areas with dense building clusters, the signals between drones and base stations are reflected and refracted multiple times, making the transmission path unstable and the data transmission rate drop significantly. In addition, with the expansion of the environmental sanitation business scale, the amount of data collected by drones has increased exponentially, and the existing transmission methods are difficult to meet the demand for rapid transmission of large amounts of data. The traditional transmission method based on fixed frequency bands is prone to congestion in the case of limited spectrum resources, resulting in data queuing for transmission, further reducing the transmission efficiency and unable to provide timely support for environmental sanitation decision-making.

[0004] In terms of data security, environmental sanitation data contains a large amount of sensitive information, such as urban garbage distribution, environmental quality monitoring data, etc. Once these data are leaked, it may cause serious consequences such as incorrect risk assessment of environmental pollution and chaos in urban environmental sanitation planning. At present, the encryption means adopted by most environmental sanitation drones are relatively simple and difficult to resist increasingly complex network attacks. The fixed encryption algorithms used by some drones are easily cracked when hackers use advanced cracking techniques, and the data security cannot be guaranteed. Moreover, there is no unified standard for the security protocols of environmental sanitation drones of different brands and models, resulting in security vulnerabilities in the data interaction process and bringing great security risks to data transmission.

[0005] Furthermore, existing data transmission methods for sanitation drones often lack the ability to adapt to dynamic network environments. During the flight of the drone, the network bandwidth changes dynamically with the location and environment. Existing transmission mechanisms cannot adjust the transmission strategy in a timely manner according to the real-time network conditions, making it difficult to achieve efficient transmission while ensuring data security. For example, when the drone flies from an open area to an area with severe signal occlusion, it cannot automatically optimize the transmission path and encryption method, resulting in data loss or low transmission efficiency. These problems seriously hinder the intelligent development of the sanitation business in smart cities and urgently require an innovative technology to solve the efficiency and security problems of data transmission for sanitation drones, promoting the sanitation industry to move towards a more efficient and intelligent direction. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for efficient and secure data transmission of sanitation drones in smart cities to solve the problems raised in the above background technology.

[0007] To achieve the above purpose, the present invention provides the following technical solution: A method for efficient and secure data transmission of sanitation drones in smart cities, the method includes:

[0008] Determine the sanitation drone with data to be transmitted as the first node, and the sanitation drone adjacent to the first node in the communication network as the second node;

[0009] According to the obtained transmission parameters of the first node and the transmission parameters of the second node, determine the actual delay between the transmission path of the first node at the current moment and the transmission path of the second node at the specified historical moment, and determine the expected delay between the first node at the current moment and the second node at the specified historical moment;

[0010] Determine the correction amount according to the transmission amount completed by the second node from the specified historical moment to the current moment at the data transmission rate at the specified historical moment;

[0011] Determine the expected delay according to the basic delay and the correction amount;

[0012] According to the difference between the actual delay and the expected delay, and the determined encryption parameters of the second node at the specified historical moment, determine the encryption parameters for the first node at the current moment as the target encryption parameters, and adjust the data transmission protocol of the first node according to the target encryption parameters.

[0013] Preferably, the determination of the expected delay between the first node at the current moment and the second node at the specified historical moment specifically includes:

[0014] Determine the actual delay between the transmission link of the first node at the current moment and the receiving link of the second node at the specified historical moment according to the transmission path state of the first node at the current moment, the transmission path state of the second node at the specified historical moment, and a preset network bandwidth threshold. Determining the expected delay between the first node at the current moment and the second node at the specified historical moment includes determining the basic delay between the first node at the current moment and the second node at the specified historical moment according to the transmission volume reached by the first node at the current moment's data transmission rate within a preset buffer period and a preset minimum delay threshold.

[0015] Preferably, the transmission parameters include: link state parameters and security parameters; the link state parameters include: signal strength between adjacent nodes in the communication network, stability of the data transmission path, and location information of the nodes; the security parameters include: the type of encryption algorithm and key length used during data transmission;

[0016] Obtaining the transmission parameters of the first node and the second node specifically includes:

[0017] Collect and store the link state parameters of the first node and the second node during data transmission through a monitoring module deployed on the first node;

[0018] Obtain the security parameters for protecting the data of the second node itself sent by the second node through a security module deployed on the first node.

[0019] Preferably, the duration between the specified historical moment and the current moment is not less than the maximum value of the communication delay for the second node to send security parameters through the security module and the response delay for the first node to collect link state parameters through the monitoring module.

[0020] Preferably, determining the encryption parameters of the second node at the specified historical moment specifically includes:

[0021] Determine the encryption parameters of the first node at the specified historical moment, obtain the first encryption weight and the first verification weight corresponding to the first node, and obtain the second encryption weight and the second verification weight corresponding to the second node;

[0022] Determine the combined value obtained by weighting the encryption parameters of the second node at the specified historical moment with the first encryption weight and weighting the verification parameters of the second node at the specified historical moment with the first verification weight as the first combined value, and determine the combined value obtained by weighting the encryption parameters of the first node at the specified historical moment with the second encryption weight and weighting the verification parameters of the first node at the specified historical moment with the second verification weight as the second combined value;

[0023] Taking the matching relationship between the first combined value and the second combined value as a constraint condition, determine the encryption parameters of the second node at the specified historical moment through a preset weighted calculation rule.

[0024] Preferably, the method further includes:

[0025] After determining the target encryption parameters, delete the transmission parameters of the second node stored before the specified historical moment.

[0026] Preferably, when determining the actual delay between the transmission path of the first node and the transmission path of the second node, it further includes:

[0027] According to the number of hops of multiple relay nodes in the current transmission path of the first node and the number of hops of multiple relay nodes in the historical transmission path of the second node, calculate the path complexity difference, and multiply the path complexity difference by a preset delay correction coefficient to correct the actual delay.

[0028] Preferably, when determining the expected delay, it further includes:

[0029] According to the fluctuation range between the current transmission rate of the first node and the historical transmission rate of the second node, and a preset dynamic adjustment factor, dynamically compensate the basic delay to obtain the compensated expected delay.

[0030] Preferably, the present invention further includes a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the efficient and secure data transmission method for smart city sanitation drones as described.

[0031] Preferably, the present invention further includes an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the efficient and secure data transmission method for smart city sanitation drones as described.

[0032] Compared with the prior art, the beneficial effects of the present invention are:

[0033] In terms of improving data transmission efficiency, this method calculates the actual delay and expected delay accurately by determining the transmission parameters of the first node (the sanitation drone to transmit data) and the second node (the adjacent sanitation drone). Based on these delay data, the data transmission path and rate can be adjusted flexibly. For example, when it is calculated that the current transmission path has too large a delay, it can be quickly switched to a path with a smaller delay, effectively avoiding transmission congestion caused by improper path selection. Moreover, by comprehensively considering the transmission volume reached by the first node within the preset buffer period at the current data transmission rate and the preset minimum delay threshold to determine the basic delay, and then combining the transmission volume completed by the second node from the specified historical moment to the current moment at the specified historical moment data transmission rate to determine the correction amount, and finally determining a more reasonable expected delay. This series of operations enables data transmission to better fit the actual network situation, reduces unnecessary waiting time, greatly improves the data transmission efficiency, ensures that sanitation data can be transmitted back in a timely and accurate manner, and provides real-time and effective data support for sanitation decision-making.

[0034] In terms of ensuring data transmission security, this method determines the target encryption parameter for the first node at the current moment according to the encryption parameters of the first node and the second node at the specified historical moment and the weight relationship between them. This way of determining encryption parameters based on the association between nodes increases the complexity and dynamics of encryption. It is difficult for hackers to crack the key through the encryption information of a single node because the encryption parameters are dynamically generated based on the comprehensive information of multiple nodes. At the same time, the transmission parameters of the second node before the specified historical moment stored are deleted in a timely manner, effectively preventing historical data from being maliciously obtained and utilized, reducing the risk of data leakage, and comprehensively ensuring the security of sanitation data during transmission.

[0035] In addition, this method also has good adaptability. In the process of determining the actual delay and expected delay, various dynamic factors such as the transmission path state, network bandwidth threshold, and node transmission rate fluctuation are fully considered. When the network environment changes, such as the network bandwidth suddenly becoming narrower or the node transmission rate fluctuating, the method can correct and compensate the delay according to the preset delay correction coefficient, dynamic adjustment factor, etc., automatically adjust the data transmission protocol, enabling the drone to quickly adapt to the new network environment and continuously maintain an efficient and secure data transmission state. This feature enables the sanitation drone to stably complete the data transmission task in the complex and changeable urban environment, whether encountering signal interference or network congestion, greatly enhancing the stability and reliability of the sanitation drone data transmission system, and effectively promoting the intelligent and efficient development of the smart city sanitation service. Description of the Drawings

[0036] Figure 1This is the working principle diagram of the method for efficient and secure transmission of data of smart city environmental sanitation drones according to the present invention;

[0037] Figure 2 It is the flowchart for determining a specified historical moment;

[0038] Figure 3 It is the flowchart for determining the encryption parameters of the second node;

[0039] Figure 4 It is the flowchart for actual delay correction. Specific implementation manners

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0041] Please refer to Figures 1-4 , the present invention provides a method for efficient and secure transmission of data of smart city environmental sanitation drones, and the method includes:

[0042] First, determine the environmental sanitation drone with data to be transmitted as the first node, and at the same time find the environmental sanitation drone adjacent to the first node in the communication network as the second node. For example, in a certain area of a city, there are multiple drones performing environmental sanitation data collection tasks. One of them has collected a large amount of data such as garbage distribution and cleaning progress and needs to transmit it back to the control center. This drone is set as the first node. Another drone near it with good communication signals and capable of assisting in data transmission is determined as the second node.

[0043] Obtain the transmission parameters of the first node and the transmission parameters of the second node. The transmission parameters cover link state parameters and security parameters. The link state parameters include the signal strength between adjacent nodes in the communication network, the stability of the data transmission path, and the position information of the nodes; the security parameters include the type of encryption algorithm and the key length used in the data transmission process. Through the monitoring module deployed on the first node, collect the link state parameters during the data transmission process between the first node and the second node and store them; through the security module deployed on the first node, obtain the security parameters sent by the second node to protect its own data.

[0044] Based on the obtained transmission parameters, determine the actual delay between the transmission path of the first node at the current moment and the transmission path of the second node at the specified historical moment. This process needs to comprehensively consider various factors in the node transmission path, such as the number of relay nodes in the path, signal interference conditions, etc. At the same time, determine the expected delay between the first node at the current moment and the second node at the specified historical moment. The specific way to determine the expected delay is to determine the actual delay between the transmission link of the first node at the current moment and the receiving link of the second node at the specified historical moment according to the transmission path state of the first node at the current moment, the transmission path state of the second node at the specified historical moment, and the preset network bandwidth threshold; then, according to the transmission volume reached by the first node within the preset buffer period at the data transmission rate at the current moment, and the preset minimum delay threshold, determine the basic delay between the first node at the current moment and the second node at the specified historical moment.

[0045] Determine the correction amount according to the transmission volume completed by the second node from the specified historical moment to the current moment at the data transmission rate at the specified historical moment. The determination of this correction amount helps to more accurately adjust the expected delay.

[0046] Determine the expected delay according to the basic delay and the correction amount. Through such a calculation method, it is possible to more accurately estimate the time required for data transmission.

[0047] According to the difference between the actual delay and the expected delay, and the encryption parameters of the second node at the specified historical moment determined, determine the encryption parameters for the first node at the current moment as the target encryption parameters. The specific steps to determine the encryption parameters of the second node at the specified historical moment are as follows: determine the encryption parameters of the first node at the specified historical moment, obtain the first encryption weight and the first verification weight corresponding to the first node, and obtain the second encryption weight and the second verification weight corresponding to the second node; determine the combined value obtained by weighting the encryption parameters of the second node at the specified historical moment with the first encryption weight and weighting the verification parameters of the second node at the specified historical moment with the first verification weight as the first combined value, and determine the combined value obtained by weighting the encryption parameters of the first node at the specified historical moment with the second encryption weight and weighting the verification parameters of the first node at the specified historical moment with the second verification weight as the second combined value; with the matching relationship between the first combined value and the second combined value as the constraint condition, determine the encryption parameters of the second node at the specified historical moment through the preset weighted calculation rule. Finally, adjust the data transmission protocol of the first node according to the target encryption parameters, thereby improving the security and efficiency of data transmission.

[0048] The present invention will be further described below in conjunction with Embodiments 1 to 5:

[0049] Example 1: In this example, the specific process of determining the expected delay between the first node at the current moment and the second node at a specified historical moment is elaborated in detail.

[0050] Clarify the method of obtaining the transmission path status. In the actual operation environment of smart city sanitation drones, each drone is equipped with a high-precision positioning system and a signal monitoring device. For the first node, its positioning system records its own position information in real time, and obtains data such as signal strength and signal quality through communication with surrounding base stations, so as to determine the current transmission path status. For example, when the first node is flying near a tall building, its signal may be weakened by the building obstruction, and the positioning system and signal monitoring device will integrate this information into the current transmission path status data.

[0051] For the transmission path status of the second node at the specified historical moment, it is obtained through the flight data recording module inside the drone. This module will record various data during the flight of the drone, including flight trajectory, signal change situation, etc. Assuming that the specified historical moment is 10 minutes ago, by reading the flight data record 10 minutes ago, the transmission path status of the second node at that moment can be obtained, such as the area passed at that time, the communication situation with other nodes, etc.

[0052] Consider the preset network bandwidth threshold. In the communication network of city sanitation drones, network bandwidth resources are limited. In order to ensure the efficiency of data transmission, a network bandwidth threshold will be set according to the actual situation. For example, in a busy urban area where the network bandwidth is relatively tight, the set network bandwidth threshold may be 5Mbps. When the data transmission demand between the first node and the second node exceeds this threshold, a more accurate assessment of the transmission delay is required.

[0053] According to the transmission path status of the first node at the current moment, the transmission path status of the second node at the specified historical moment, and the preset network bandwidth threshold, determine the actual delay between the transmission link of the first node at the current moment and the receiving link of the second node at the specified historical moment. This process will comprehensively consider various factors, such as the distance of signal transmission, the attenuation of the signal during transmission, etc. For example, if the straight-line distance between the first node and the second node is relatively long and there are many signal interference sources in the middle, the actual delay will increase accordingly.

[0054] Determine the transmission volume reached by the first node within the preset buffer period at the current data transmission rate. The preset buffer period is set according to the hardware performance of the drone and the data transmission requirements. Assuming that the current data transmission rate of the first node is 3Mbps and the preset buffer period is 5 seconds, then within these 5 seconds, the transmission volume reached by the first node is 3Mbps × 5 seconds = 15Mbit.

[0055] Finally, in combination with a preset minimum delay threshold, the basic delay between the first node at the current moment and the second node at a specified historical moment is determined. The preset minimum delay threshold is set considering the basic characteristics of network transmission and the minimum requirements of UAV communication. For example, if the set minimum delay threshold is 1 second, and the delay calculated according to the previous calculation is less than 1 second, the basic delay is set to 1 second; if it is greater than 1 second, the actual calculation result is taken as the basis. In this way, the expected delay can be determined more accurately, providing an important basis for subsequent data transmission optimization.

[0056] Embodiment 2: This embodiment focuses on explaining the specific operations for obtaining the transmission parameters between the first node and the second node.

[0057] For the acquisition of link state parameters, the monitoring module deployed on the first node plays a key role. The monitoring module includes various sensors and communication devices. Among them, the signal strength sensor is responsible for real-time monitoring of the signal strength between the first node and the second node. For example, during the flight of the UAV, the signal strength sensor continuously measures the signal strength value when communicating with the second node and feeds back this data to the processor of the monitoring module in real time.

[0058] The monitoring of the stability of the data transmission path is achieved by analyzing the signal fluctuation situation and the packet loss rate. The monitoring module continuously records the signal fluctuation amplitude and the number of lost packets within a period of time. If the signal fluctuates frequently and the packet loss rate is high, it indicates that the stability of the data transmission path is poor. For example, when the UAV passes through an area with strong electromagnetic interference, the signal fluctuation amplitude may increase and the packet loss rate may also rise, and the monitoring module can capture this information in a timely manner.

[0059] The position information of the node is obtained through the positioning system of the UAV itself. Currently, most UAVs are equipped with a Global Positioning System (GPS) or other high-precision positioning devices. The positioning system regularly updates the position coordinates of the first node, and the monitoring module integrates and stores these coordinate information.

[0060] In terms of obtaining security parameters, the security module deployed on the first node plays a role. During the data transmission process, the second node sends the security parameters used to protect its own data to the first node. After receiving these parameters, the security module verifies and analyzes them. For example, the security parameters sent by the second node include information such as the encryption algorithm type and the key length. The security module first verifies the integrity and legality of these parameters to ensure that they have not been tampered with. Then, the legal security parameters are stored in the security database of the first node for subsequent use when determining encryption parameters and adjusting the data transmission protocol.

[0061] In addition, to ensure the accuracy and timeliness of the obtained transmission parameters, the monitoring module and the security module also need to be maintained and updated regularly. For example, the signal strength sensor is calibrated regularly to ensure the accuracy of its measurement; the encryption algorithm library of the security module is updated in a timely manner to adapt to the ever-changing network security environment. Through these specific operations, the transmission parameters between the first node and the second node can be obtained comprehensively and accurately, providing strong support for subsequent data transmission optimization and security guarantee.

[0062] Embodiment 3: During the data transmission of the sanitation drone, the duration from a specified historical moment to the current moment needs to be set reasonably. First, consider the communication delay of the second node sending security parameters through the security module. The transmission of security parameters involves complex operations such as encryption and decryption, which will cause a certain communication delay. For example, the second node uses a relatively complex encryption algorithm to encrypt the security parameters. During the sending process, due to the time consumption of encryption calculation and network transmission, a certain delay may occur. Assume that this delay averages seconds in different network environments.

[0063] At the same time, there is also a response delay when the first node collects link state parameters through the monitoring module. When the monitoring module collects data, it needs to read, process, and integrate the data of various sensors, which also takes a certain amount of time. For example, when reading the data of the signal strength sensor and the positioning system, due to the priority of data processing and the limitation of hardware performance, a second response delay may occur.

[0064] To ensure the timeliness and reliability of the obtained transmission parameters, the duration from the specified historical moment to the current moment should not be less than the maximum value of the above communication delay and response delay, that is:

[0065]

[0066] where, represents the duration from the specified historical moment to the current moment, represents the communication delay of the second node sending security parameters through the security module, represents the response delay of the first node collecting link state parameters through the monitoring module.

[0067] If the set duration is too short, it may cause the security parameters of the second node obtained by the first node to be incomplete or inaccurate, and at the same time, the collected link state parameters may not reflect the current actual situation. For example, if the duration is set to 0.2 seconds, it is possible that the first node starts subsequent calculations and operations while the security parameters are still being transmitted, which will seriously affect the security and efficiency of data transmission.

[0068] Conversely, if the set duration is too long, although the obtained parameters can be ensured to be complete and accurate, it will increase the time cost of data processing and reduce the real-time performance of data transmission. For example, if the duration is set to 5 seconds, in some sanitation tasks with high real-time requirements, such as the scheduling data transmission for emergency garbage cleaning, the execution effect of the task may be affected due to excessive delay. Therefore, reasonably setting the duration between the specified historical moment and the current moment is crucial for ensuring the efficient and secure transmission of sanitation drone data.

[0069] Example 4: The specific steps for determining the encryption parameters of the second node at the specified historical moment include:

[0070] Determine the encryption parameters of the first node at the specified historical moment. In the encryption system of the sanitation drone, each node uses specific encryption parameters at different times to ensure data security. By querying the encryption parameter record database of the first node, the encryption parameters at the specified historical moment can be obtained, including information such as the encryption algorithm and key used at that time.

[0071] Obtain the first encryption weight and the first verification weight corresponding to the first node, and obtain the second encryption weight and the second verification weight corresponding to the second node. These weights are preset according to factors such as the status of the node in the network and the importance of the data. For example, for a drone responsible for collecting sanitation data in the core area, its encryption weight and verification weight may be relatively high to ensure data security. Assume that the first node is responsible for collecting data in an important area, its first encryption weight is set to 0.6, and its first verification weight is set to 0.4; the second node is responsible for collecting data in a general area, its second encryption weight is set to 0.4, and its second verification weight is set to 0.6.

[0072] Determine the combined value obtained by weighting the encryption parameters of the second node at the specified historical moment with the first encryption weight and weighting the verification parameters of the second node at the specified historical moment with the first verification weight as the first combined value. At the same time, determine the combined value obtained by weighting the encryption parameters of the first node at the specified historical moment with the second encryption weight and weighting the verification parameters of the first node at the specified historical moment with the second verification weight as the second combined value. This process requires careful calculation and integration of the encryption parameters and verification parameters. For example, if the encryption parameters of the second node at the specified historical moment are [Algorithm A, Key 1], the verification parameters are [Verification Code 1], the first encryption weight is 0.6, and the first verification weight is 0.4, then the calculation of the first combined value involves calculating and fusing these parameters according to the weights.

[0073] Taking the matching relationship between the first combined value and the second combined value as a constraint condition, the encryption parameter of the second node at a specified historical moment is determined through a preset weighted calculation rule. The preset weighted calculation rule is obtained through a large number of experiments and theoretical analyses, aiming to ensure the rationality and security of the encryption parameter. For example, if the matching degree between the first combined value and the second combined value reaches a certain standard, such as more than 80%, it is considered that the currently calculated encryption parameter of the second node is reasonable; if the matching degree is insufficient, the weight or encryption parameter needs to be readjusted until the matching requirement is met. Through such rigorous steps, the encryption parameter of the second node at a specified historical moment can be accurately determined, providing a reliable basis for the determination of the target encryption parameter of the first node in the subsequent process.

[0074] Embodiment 5: This embodiment details the correction process of the actual delay between the transmission path of the first node and the transmission path of the second node and the dynamic compensation process of the expected delay.

[0075] In the process of correcting the actual delay between the transmission path of the first node and the transmission path of the second node, first, the method of obtaining the number of hops of multiple relay nodes in the current transmission path of the first node and the number of hops of multiple relay nodes in the historical transmission path of the second node needs to be clarified. Each UAV will record the information of relay nodes in its own transmission path during the data transmission process. For example, when the first node transmits data to the second node, it passes through 3 relay nodes, and the internal path recording module will record this information; similarly, the second node passes through 2 relay nodes in its transmission path at a specified historical moment, and this information will also be stored.

[0076] Calculate the path complexity difference. The path complexity difference can be reflected by the difference in the number of hops of relay nodes in the two paths. In the above example, the path complexity difference is 3 - 2 = 1.

[0077] Next, multiply the path complexity difference by a preset delay correction coefficient to correct the actual delay. The preset delay correction coefficient is obtained based on a large number of experiments and actual data statistics. Assuming that the preset delay correction coefficient is 0.2, then the increased amount of the corrected actual delay is 1×0.2 = 0.2 seconds. This correction process takes into account the influence of the number of relay nodes in the transmission path on the delay, making the calculation of the actual delay more accurate.

[0078] In the process of dynamic compensation of the expected delay, first, the fluctuation range between the current transmission rate of the first node and the historical transmission rate of the second node needs to be obtained. Through the monitoring module and historical data recording, the transmission rates of the two nodes at different times can be obtained. For example, the current transmission rate of the first node is 4Mbps, and the transmission rate of the second node at a specified historical moment is 3Mbps. After a period of monitoring, it is found that the fluctuation range of the transmission rate is between ±1Mbps.

[0079] Perform dynamic compensation on the base delay according to a preset dynamic adjustment factor. The preset dynamic adjustment factor is set according to the changing characteristics of the network environment and the real-time requirements of data transmission. Suppose the preset dynamic adjustment factor is 0.1. If the current transmission rate is higher than the historical transmission rate and the fluctuation range is within the allowable range, and the base delay is 2 seconds, then the expected delay after compensation is 2 + 2×0.1 = 2.2 seconds; if the current transmission rate is lower than the historical transmission rate, corresponding subtraction compensation is performed according to the specific situation. Through such a dynamic compensation process, the expected delay can be adjusted in real time according to the change of the transmission rate, improving the efficiency and stability of data transmission.

[0080] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0081] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An efficient and secure data transmission method for sanitation drones in a smart city, characterized in that, Including: Determine the sanitation UAV for the data to be transmitted as the first node, and the sanitation UAV adjacent to the first node in the communication network as the second node; According to the obtained transmission parameters of the first node and the transmission parameters of the second node, determine the actual delay between the transmission path of the first node at the current moment and the transmission path of the second node at the specified historical moment; at the same time, according to the transmission path state of the first node at the current moment, the transmission path state of the second node at the specified historical moment and the preset network bandwidth threshold, determine the actual delay between the transmission link of the first node at the current moment and the receiving link of the second node at the specified historical moment, determine the basic delay between the first node at the current moment and the second node at the specified historical moment according to the transmission volume reached by the first node at the current moment's data transmission rate within the preset buffer period and the preset minimum delay threshold; determine the correction amount according to the transmission volume completed by the second node from the specified historical moment to the current moment at the data transmission rate of the specified historical moment; determine the expected delay between the first node at the current moment and the second node at the specified historical moment according to the basic delay and the correction amount; According to the difference between the actual delay and the expected delay, and the encryption parameters of the second node determined at the specified historical moment, determine the encryption parameters for the first node at the current moment as the target encryption parameters, and adjust the data transmission protocol of the first node according to the target encryption parameters.

2. The method for efficiently and securely transmitting data of a smart city sanitation drone according to claim 1, wherein, The transmission parameters include: link state parameters and security parameters; the link state parameters include: signal strength between adjacent nodes in the communication network, stability of the data transmission path, and location information of the nodes; the security parameters include: encryption algorithm type and key length used in the data transmission process; Obtaining the transmission parameters of the first node and the second node specifically includes: Collect and store the link state parameters of the first node and the second node during data transmission through the monitoring module deployed on the first node; Obtain the security parameters sent by the second node for protecting its own data through the security module deployed on the first node.

3. The method for efficiently and securely transmitting data of a smart city sanitation drone according to claim 2, characterized in that, The duration between the specified historical moment and the current moment is not less than the maximum value of the communication delay for the second node to send the security parameters through the security module and the response delay for the first node to collect the link state parameters through the monitoring module.

4. The method according to claim 1 or 3, characterized in that, Determining the encryption parameters of the second node at the specified historical moment specifically includes: Determine the encryption parameters of the first node at the specified historical moment, obtain the first encryption weight and the first verification weight corresponding to the first node, and obtain the second encryption weight and the second verification weight corresponding to the second node; Determine the combined value obtained by weighting the encryption parameters of the second node at the specified historical moment by the first encryption weight and weighting the verification parameters of the second node at the specified historical moment by the first verification weight as the first combined value, and determine the combined value obtained by weighting the encryption parameters of the first node at the specified historical moment by the second encryption weight and weighting the verification parameters of the first node at the specified historical moment by the second verification weight as the second combined value; Taking the matching relationship between the first combined value and the second combined value as a constraint condition, determine the encryption parameters of the second node at the specified historical moment through a preset weighted calculation rule.

5. The method for efficient and secure transmission of data of a smart city sanitation drone according to claim 1, characterized in that, The method further includes: After determining the target encryption parameters, delete the stored transmission parameters of the second node before the specified historical moment.

6. The method for efficiently and securely transmitting data of a smart city sanitation drone according to claim 1, wherein, When determining the actual delay between the transmission path of the first node and the transmission path of the second node, it further includes: Calculate the path complexity difference according to the number of hops of multiple relay nodes in the current transmission path of the first node and the number of hops of multiple relay nodes in the historical transmission path of the second node, and multiply the path complexity difference by a preset delay correction coefficient to correct the actual delay.

7. The method for efficiently and securely transmitting data of a smart city sanitation drone according to claim 1, wherein When determining the expected delay, it further includes: Dynamically compensate the basic delay according to the fluctuation range between the current transmission rate of the first node and the historical transmission rate of the second node and a preset dynamic adjustment factor to obtain the compensated expected delay.

8. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the method for efficient and secure transmission of smart city sanitation drone data according to any one of claims 1 to 7.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for efficient and secure transmission of smart city sanitation drone data according to any one of claims 1 to 7.

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