Intelligent interconnection method and device for environmental sanitation equipment based on ad hoc network technology

Abstract

The invention relates to the technical field of environmental sanitation equipment intelligent connection, in particular to an environmental sanitation equipment intelligent interconnection method and device based on the ad-hoc network technology, and the method comprises the steps: a source node broadcasts probe request information to the surrounding, and receives response information fed back by a neighbor node at the same time; based on the response information, determining an optimal connection object according to a preset scoring function, and establishing a bidirectional communication link with the optimal connection object to form a network topology; each node in the network topology periodically broadcasts reachability information of the node itself, wherein the reachability information comprises a reachability node list and a corresponding metric value thereof; and obtaining destination node information, and calculating and determining an optimal path from the source node to the destination node as a data forwarding link. The method can get rid of dependence on a fixed base station, networking can be carried out in a complex area, and network adaptability and stability are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent connection of environmental sanitation equipment, and particularly to an intelligent interconnection method and device for environmental sanitation equipment based on self-organizing network technology. Background Art

[0002] Traditional environmental sanitation management systems mainly rely on a centralized network architecture in the urban environment. This architecture uses fixed base stations for data transmission to monitor and manage various environmental sanitation equipment (such as garbage collection trucks, street sweepers, trash cans, etc.). Although this method played a certain role in the early urban environmental sanitation work, with the continuous expansion of the urban scale and the increasing complexity of environmental sanitation requirements, its limitations have gradually emerged.

[0003] The design concept of the centralized network architecture is to simplify network deployment and management. It assumes that all nodes can stably connect to one or more fixed access points (APs), which are usually located at specific positions in the city, such as street lamp poles, building tops, etc. However, in actual applications, the urban environment is full of various complex factors, such as high-rise buildings standing in great numbers, underground tunnels crisscrossing, and a wide range of electromagnetic interference sources, etc. These all pose great challenges to wireless signal propagation. Specifically, high-rise buildings will block the straight-line propagation path of wireless signals, causing so-called "shadow areas"; while underground spaces may completely shield signals, making some areas communication blind spots. In addition, electromagnetic interference from other electronic devices will also reduce the quality of the wireless link, further affecting the reliability of data transmission. Due to relying on fixed base stations, when environmental sanitation equipment leaves the effective coverage area of the base station, it cannot maintain a stable communication connection. Especially in large cities, due to the complex and changeable geographical conditions, even increasing the number of base stations is difficult to ensure full coverage. In addition, some special occasions such as parks, squares, etc., where there are dense crowds but it is difficult to deploy base stations, often become dead corners of network services.

[0004] With the acceleration of the urbanization process, the urban population density is increasing continuously, and the corresponding environmental sanitation task volume is also growing. To cope with this change, the environmental sanitation department has to add more mobile devices to improve work efficiency. However, the traditional centralized network is difficult to adapt to such a large-scale and highly dynamic working scenario. On the one hand, the newly added devices require additional infrastructure support, such as expanding the base station coverage area or adding new base stations, which not only increases the construction cost but also prolongs the deployment time. On the other hand, since environmental sanitation vehicles and facilities are often in a mobile state, their relative positions with respect to the fixed base stations are constantly changing, resulting in frequent switching or even interruption of the communication link, thus reducing the overall system response speed and service quality.

[0005] Moreover, a fatal weakness of the centralized network architecture is that a single point of failure may lead to the paralysis of the entire system. If a critical base station fails, all devices relying on that base station will lose connection, thus affecting the normal operation of the entire sanitation work. Although this situation can be alleviated by setting up redundant base stations, this undoubtedly increases the complexity and maintenance difficulty of the system. More importantly, redundant design cannot completely eliminate all potential risks, because in the event of a large-scale power outage or other natural disasters, all backup measures may fail.

[0006] In addition, for sanitation equipment in motion, traditional networks are difficult to provide continuous and stable connections. Sanitation vehicles may pass through different signal strength areas during task execution, and sometimes even enter areas with extremely poor or no signal. At this time, the information exchange between devices will be severely affected, not only hindering real-time scheduling and command, but also possibly resulting in the loss of important data. In addition, when multiple sanitation vehicles work in the same area simultaneously, serious channel competition problems will occur, further deteriorating the communication performance.

[0007] In the long run, the centralized network architecture lacks sufficient flexibility to meet the needs of future smart city development. The concept of a smart city emphasizes the interconnection of all things, that is, different types of intelligent devices can cooperate seamlessly to jointly provide more efficient services for urban management. In this context, as an important part of urban operation, the sanitation system should have stronger self-organization capabilities and intelligent levels. Therefore, how to build a new type of networking solution that is both economical and efficient has become an urgent problem to be solved. Summary of the Invention

[0008] The object of the present invention is to provide an intelligent interconnection method and device for sanitation equipment based on self-organizing network technology, which can get rid of the dependence on fixed base stations, form a network in complex areas, and enhance the network adaptability and stability.

[0009] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0010] An intelligent interconnection method for sanitation equipment based on self-organizing network technology, which includes:

[0011] The source node broadcasts a probe request message to the surrounding area, and at the same time receives the response information fed back by neighbor nodes;

[0012] Based on the response information, determine the optimal connection object according to a preset scoring function, and establish a two-way communication link with it to form a network topology;

[0013] Each node in the network topology periodically broadcasts its own reachability information, and the reachability information includes a list of reachable nodes and their corresponding metric values;

[0014] Obtain the information of the destination node, calculate and determine the optimal path from the source node to the destination node as the data forwarding link.

[0015] Furthermore, the preset scoring function is: S i = α·RSSI i + β·energy_level i + γ·proximity i ;

[0016] Wherein, S i is the total score of the i-th neighbor node, RSSI i is the received signal strength indication value of the i-th neighbor node, energy_level i is the energy level of the i-th neighbor node, proximity i is the distance between the source node and the i-th neighbor node, α is the weight coefficient of the signal strength, β is the weight coefficient of the energy level, and γ is the weight coefficient of the geographical location.

[0017] Furthermore, each node in the network topology regularly reports its own operating status to the neighbor nodes with which it has established a two-way communication link, and at the same time listens to the status reports from other nodes in the network topology;

[0018] Evaluate the operating status of the nodes in the network topology according to the preset evaluation function. When the evaluation value exceeds the preset threshold, the node re-determines the connection object.

[0019] Furthermore, the preset evaluation function is: w = a·link_quality + b·node_mobility + c·energy_level + d·network_load;

[0020] Wherein, w is the evaluation value of the node's operating status;

[0021] link_quality is the link quality, indicating the stability of the communication link between nodes;

[0022] node_mobility is the node mobility, indicating the stability of the node's moving speed and moving direction;

[0023] energy_level represents the node energy level, indicating the current battery percentage of the node;

[0024] network_load is the network load, indicating the amount of data currently processed by the node and the busyness of communication tasks;

[0025] a is the weight coefficient of link quality, which is used to adjust the influence degree of link quality on the node operating condition in the evaluation function;

[0026] b is the weight coefficient of node mobility, which is used to adjust the influence degree of node mobility on the node operating condition in the evaluation function;

[0027] c is the weight coefficient of node energy level, which is used to adjust the influence degree of energy level on the node operating condition in the evaluation function;

[0028] d is the weight coefficient of network load, which is used to adjust the influence degree of network load on the node operating condition in the evaluation function.

[0029] Furthermore, several standby planned paths are also provided between the source node and the destination node. When the data forwarding link is not the optimal path, the standby planned path is enabled for data forwarding.

[0030] Furthermore, in response to the failure of a certain node in the network topology, the remaining nodes communicatively connected to the failed node adjust their respective routing tables, remove all records pointing to the failed node, and re-determine the connection objects.

[0031] Furthermore, the working states of each node are automatically adjusted according to the actual workload. When the time that a node is in the stationary state exceeds the preset time threshold, the node is controlled to enter deep sleep.

[0032] Furthermore, the data exchange between the nodes in the network topology adopts the AES-256-bit symmetric encryption algorithm.

[0033] In the second aspect, the present invention discloses an intelligent interconnection system for sanitation equipment based on ad-hoc network technology, which includes:

[0034] The first broadcast module is arranged in the source node and is used to broadcast probe request messages to the surroundings;

[0035] The recording module is used to receive the response information fed back by the neighbor nodes;

[0036] The connection module is used to determine the optimal connection object based on the response information according to the preset scoring function, and establish a two-way communication link with it to form a network topology;

[0037] The second broadcast module is used to periodically broadcast the reachability information of each node itself in the network topology, and the reachability information includes the reachable node list and its corresponding metric value;

[0038] The forwarding module is used to obtain the destination node information, calculate and determine the optimal path between the source node and the destination node as the data forwarding link.

[0039] The present invention has the following unexpected beneficial effects:

[0040] The intelligent interconnection method of sanitation equipment based on the ad-hoc network technology of the present invention has significant advantages. On the one hand, it improves the communication autonomy and convenience. Sanitation equipment can autonomously discover surrounding nodes and connect, getting rid of the dependence on fixed base stations and being able to form a network in complex areas. And it selects the optimal connection object through a preset scoring function, comprehensively considering various factors to ensure the initial connection quality. On the other hand, each node periodically broadcasts reachability information to maintain the update of the network topology, providing a basis for routing decisions. It calculates the optimal path as the data forwarding link, improving the data transmission efficiency. Overall, this series of steps enhances the network adaptability and stability. Facing the movement of sanitation equipment and environmental changes, it can dynamically adjust to maintain communication, reducing the impact on sanitation operations and improving the system reliability. Furthermore, it overcomes many limitations under the traditional centralized network architecture, has good scalability and compatibility, can be easily integrated with more types of intelligent devices, and promotes the development process of smart cities. Brief Description of the Drawings

[0041] Figure 1 It shows a schematic flowchart of the intelligent interconnection method of sanitation equipment based on the ad-hoc network technology described in the embodiments of the present invention.

[0042] Figure 2 It shows a schematic structural diagram of the intelligent interconnection system of sanitation equipment based on the ad-hoc network technology described in the embodiments of the present invention. Detailed Embodiments

[0043] The following will illustrate the embodiments of the present invention with reference to the drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention, rather than for limiting the protection scope of the present invention.

[0044] It should be noted that the drawings provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Therefore, only the components related to the present invention are shown in the drawings, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0045] In one embodiment, as shown in Figure 1 the present invention discloses an intelligent interconnection method of sanitation equipment based on the ad-hoc network technology, which includes the following steps:

[0046] S1. The source node broadcasts a probe request message to its surroundings and simultaneously receives response information feedback from neighbor nodes.

[0047] S2. Based on the response information, determine the optimal connection object according to a preset scoring function and establish a two-way communication link with it to form a network topology.

[0048] S3. Each node in the network topology periodically broadcasts its own reachability information, and the reachability information includes a list of reachable nodes and their corresponding metric values.

[0049] S4. Obtain the destination node information, calculate and determine the optimal path from the source node to the destination node as the data forwarding link.

[0050] The intelligent interconnection method for sanitation equipment based on the ad hoc network technology of the present invention has significant advantages. On the one hand, it improves the communication autonomy and convenience. Sanitation equipment can autonomously discover surrounding nodes and connect, getting rid of the dependence on fixed base stations and being able to form a network in complex areas. And the optimal connection object is selected through a preset scoring function, comprehensively considering various factors to ensure the initial connection quality. On the other hand, each node periodically broadcasts reachability information to maintain the update of the network topology and provide a basis for routing decisions. Calculating the optimal path as the data forwarding link improves the data transmission efficiency. Overall, this series of steps enhances the network adaptability and stability. Facing the movement of sanitation equipment and environmental changes, it can dynamically adjust to maintain communication, reducing the impact on sanitation operations and improving the system reliability. Furthermore, it overcomes many limitations under the traditional centralized network architecture, has good scalability and compatibility, can be easily integrated with more types of intelligent devices, and promotes the development process of smart cities.

[0051] Exemplarily, the intelligent interconnection method for sanitation equipment based on the ad hoc network technology of the present invention specifically includes the following steps:

[0052] S1. The source node broadcasts a probe request message to its surroundings and simultaneously receives response information feedback from neighbor nodes.

[0053] The node (source node and neighbor node) is integrated with an SOC module. The internal structure of this SOC module includes a microprocessor (MCU), a wireless communication unit (supporting at least one of Wi-Fi, Bluetooth, and Zigbee), a sensor interface (such as temperature, humidity, GPS, etc. information detection), a power management module, and a software component for executing the ad hoc network protocol stack. The design of this SOC module aims to minimize power consumption while maximizing processing power and communication efficiency.

[0054] When the garbage collection truck starts, the built-in SOC module first loads the preset configuration file and activates the wireless communication unit. The SOC module sends a probe request message with a unique identifier (ID) to the surrounding environment through the Zigbee protocol to detect potential neighboring nodes. Assuming that the garbage collection truck is located in a certain community, it will try to connect to nearby garbage bins, sweepers and other equipment.

[0055] Other devices that receive the probe request, i.e., neighbor nodes, respond with response information including information related to the neighbor phase, including RSSI value (signal strength indicator), current status (active / sleeping), remaining battery percentage, etc. For example, a nearby trash can reports an RSSI of -60dBm, a battery level of 85%, and a location coordinate of (40.7128, -74.0060).

[0056] The source node broadcasts the probe request message and receives the response from the neighboring nodes. This method enables the sanitation equipment to autonomously discover the surrounding connectable nodes without complicated pre-configuration, greatly improving the autonomy and convenience of network establishment. Compared with the traditional centralized network architecture that relies on fixed base stations, this method is free from the constraints of specific infrastructure and can quickly establish communication connections in complex urban environments. For example, in parks, squares and other areas with poor base station coverage, sanitation equipment can also successfully network and communicate.

[0057] S2, based on the response information, determines the optimal connection object according to the preset scoring function, and establishes a two-way communication link with it to form a network topology.

[0058] The preset scoring function is: i =α·RSSI i +β·energy_level i +γ·proximity i Where S i is the total score of the i-th neighbor node, RSSI i is the received signal strength indicator value of the i-th neighbor node, energy_level i is the energy level of the i-th neighbor node, proximity i is the distance between the source node and the i-th neighbor node, α is the weight coefficient of signal strength, β is the weight coefficient of energy level, and γ is the weight coefficient of geographical location.

[0059] This preset scoring function provides an accurate basis for the source node to select the optimal connection object by comprehensively considering multiple important factors. Among them, the signal strength (RSSI) directly affects the stability of data transmission. The stronger the signal, the more conducive it is to communication, and the weight coefficient α reflects its importance. The energy level is related to the continuous working ability of the node. A node with sufficient energy can ensure the persistence of the connection, and the weight coefficient β reflects its proportion in the scoring. The distance (proximity) between the source node and its neighbor nodes affects the transmission delay. A shorter distance can reduce the delay, and the weight coefficient γ highlights its influence. With the help of this scoring function, sanitation equipment can select the most favorable connection object during network formation, optimize the initial state of the network, and then improve the performance and reliability of the entire self-organizing network of sanitation equipment, ensuring the efficient progress of sanitation operations.

[0060] When the sanitation equipment starts or enters the working state, the source node broadcasts a probe request message and receives responses from neighbor nodes. The preset scoring function is used to calculate the scores of each neighbor node, and the optimal connection object is selected based on the scores to establish a two-way communication link. For example, a garbage collection vehicle will preferentially connect to trash cans or street sweepers with strong signals, sufficient power, and short distances, which can reduce signal interference and transmission delay, improve the initial connection quality, and ensure the stability and efficiency of data transmission.

[0061] Adapt to node dynamic changes: Sanitation equipment moves continuously during operation, and the network topology changes accordingly. The preset scoring function can be used to evaluate potential connection nodes in real time. When the signal of an existing connection node becomes weak, the energy level drops, or the distance becomes farther due to movement, the scores are recalculated, and a new node with a higher score is selected to establish a connection. For example, when a garbage collection vehicle moves to a new area, it can quickly find a better connection object according to the scoring function to maintain network stability and smooth data transmission.

[0062] By adjusting the weight coefficients of various factors in the scoring function, the utilization of network resources can be balanced. In areas with high requirements for signal stability, the weight coefficient of signal strength (RSSI) is appropriately increased; in scenarios with limited energy, the weight coefficient of the energy level is increased, and nodes with sufficient power are preferentially selected for connection to extend the overall operation time of the network; in cases sensitive to transmission delay, the weight coefficient of geographical proximity is increased to ensure fast data transmission. Exemplarily, α = 0.5, β = 0.3, γ = 0.2, that is, a garbage collection vehicle will preferentially connect to trash cans or street sweepers with strong signals, sufficient power, and short distances, which can reduce signal interference and transmission delay, improve the initial connection quality, and ensure the stability and efficiency of data transmission.

[0063] For the trash can described in S1, the calculated score according to the preset scoring function is S = 0.5×(-60) + 0.3×85 + 0.2×10 = -2.5.

[0064] After calculating the scores of all neighbor nodes around the garbage collection vehicle through a preset scoring function, the node with the highest score is finally selected as the initial connection object, and a two-way communication link is established with it through a handshake protocol to form a preliminary network topology.

[0065] Determining the optimal connection object through a preset scoring function comprehensively considers various factors such as signal strength, node energy level, and geographical proximity. This method can select the most suitable neighbor nodes for connection, ensuring the quality of the initial network connection. Taking the garbage collection vehicle as an example, it can connect to trash cans or street sweepers with strong signals, sufficient power, and short distances, effectively reducing signal interference and transmission delay, and improving the stability and efficiency of data transmission.

[0066] S3, each node in the network topology periodically broadcasts its own reachability information, and the reachability information includes a list of reachable nodes and their corresponding metric values. Exemplarily, the AODV algorithm is used to maintain the latest routing table, and the routing information is updated every 5 seconds.

[0067] Each node periodically broadcasts reachability information, enabling each node in the network to timely grasp the status and connection conditions of other nodes. This not only helps to maintain the real-time update of the network topology but also provides an accurate basis for subsequent routing decisions. For example, in sanitation operations, the positions of vehicles and equipment are constantly changing. By periodically broadcasting reachability information, the network can be ensured to adapt to these changes in a timely manner, guaranteeing the smoothness of data transmission.

[0068] S4, obtain the destination node information, calculate and determine the optimal path between the source node and the destination node as the data forwarding link.

[0069] Using the Dijkstra algorithm, based on the latest obtained routing information, calculate the optimal path between the source node and the destination node. Define an adjacency matrix A, where A ij represents the direct connection cost from node i to node j. If there is no direct connection, then A ij = ∞. For example, if the garbage collection vehicle wants to go to another trash can B and there are two paths: one passes through the street sweeper C and the other reaches directly, then the calculated path costs are c1 = 2 and c2 = 3 respectively, and the path c1 with the lower cost is selected as the default data forwarding route.

[0070] Calculating the optimal path from the source node to the destination node as the data forwarding link can effectively reduce the number of hops and delay in the data transmission process, improving the data transmission efficiency. In actual sanitation operations, a large amount of data such as vehicle position information and garbage collection volume data needs to be transmitted in a timely and accurate manner. The optimal path algorithm can ensure that this data quickly reaches the target node, enhancing the response speed and overall operation efficiency of the sanitation management system.

[0071] As a preferred embodiment of the present invention, each node in the network topology regularly reports its own operating status to neighbor nodes with which it has established a two-way communication link, and at the same time listens for status reports from other nodes in the network topology. This enables each node in the network to grasp the dynamic situation of the entire network in real time. Taking a garbage collection vehicle as an example, its position changes continuously during operation. Through regular reports, peripheral devices can timely know its position information, which is convenient for adjusting their own communication strategies with the garbage collection vehicle. This real-time update of information provides an accurate basis for the dynamic adjustment of the network.

[0072] The operating status of nodes in the network topology is evaluated according to a preset evaluation function. When the evaluation value exceeds the preset threshold, it means that the current network state is not good. At this time, the node re-determines the connection object. For example, when a garbage collection vehicle is driving, if it moves to an area with weak signals, resulting in a decline in link quality and the evaluation value exceeding the threshold, it will re-look for nodes with better signals and more stable connections to establish connections, ensuring the stability of data transmission, avoiding affecting the sanitation operation scheduling and data transmission due to network problems, and maintaining the efficient and stable operation of the network.

[0073] Further, the preset evaluation function is: w = a·link_quality + b·node_mobility + c·energy_level + d·network_load;

[0074] In the formula, w is the evaluation value of the operating status of the node;

[0075] link_quality is the link quality, which represents the stability of the communication link between nodes. It is specifically measured by indicators such as signal strength (RSSI), packet loss rate, and bit error rate. A higher link quality means higher reliability and efficiency of data transmission.

[0076] node_mobility is the node mobility, which represents the stability of the moving speed and moving direction of the node. In sanitation equipment, for example, equipment such as garbage collection vehicles and road sweepers may move during operation. This parameter is used to evaluate the impact of the dynamic changes of the node on the network topology.

[0077] energy_level represents the node energy level, which represents the current battery percentage of the node. The energy level affects the continuous working ability and communication ability of the node. The higher the energy level, the more stable the node can participate in network communication.

[0078] network_load is the network load, which represents the amount of data currently processed by the node and the busyness of communication tasks.

[0079] a is the weight coefficient of link quality, which is used to adjust the influence degree of link quality on the node operating condition in the evaluation function.

[0080] b is the weight coefficient of node mobility, which is used to adjust the influence degree of node mobility on the node operating condition in the evaluation function.

[0081] c is the weight coefficient of node energy level, which is used to adjust the influence degree of energy level on the node operating condition in the evaluation function.

[0082] d is the weight coefficient of network load, which is used to adjust the influence degree of network load on the node operating condition in the evaluation function.

[0083] As a preferred embodiment of the present invention, several standby planned paths are also provided between the source node and the destination node. When the data forwarding link is not the optimal path, the standby planned path is enabled for data forwarding.

[0084] The sanitation operation scenario is complex and changeable, and the equipment moves frequently. The data forwarding link is very likely to no longer be the optimal path due to factors such as node position changes and signal interference. At this time, the existence of the standby planned path is crucial. For example, when the garbage collection vehicle is on the way to the destination, if the original path is blocked due to road construction ahead, or the signal becomes poor due to building occlusion, and the performance of the main data forwarding link decreases, the system can immediately enable the standby planned path to ensure uninterrupted data transmission, avoid data loss or delay caused by path problems, and ensure the real-time performance and accuracy of the sanitation management system.

[0085] Moreover, setting the standby planned path can also make the network have stronger adaptability and fault tolerance, reduce the impact on sanitation operations due to path problems, and reduce the risk of single-point failures. Even if a certain link has problems, the network can quickly switch and maintain normal operation. At the same time, this method also improves the flexibility of the network, can better adapt to the complex urban environment and diverse sanitation operation requirements, and lays a solid foundation for the further expansion and upgrade of the sanitation system in the future smart city.

[0086] Meanwhile, the standby paths should cover different nodes and links as much as possible to reduce the possibility of multiple standby paths failing simultaneously due to the failure of a certain node or link. For example, in the self-organizing network of sanitation equipment, if the signal interference is serious in some areas, different standby paths can bypass these interference areas. Priority is given to selecting links with high signal strength, good node stability, and sufficient energy to build the standby paths to ensure that when the main path fails, the standby paths can transmit data stably and reliably. When setting the standby paths, it is necessary to comprehensively consider the construction cost and expected benefits of the paths, avoid setting overly complex or costly standby paths, and ensure that the standby paths can play a role when needed to improve the success rate of data transmission.

[0087] Exemplarily, the method for setting the backup planning path specifically includes:

[0088] Step 1, data collection, including node information, link information, and network topology information.

[0089] Node information: Collect the basic information of each node in the network, including the location, energy level, signal strength, processing capacity, etc. of the node. This information will help evaluate the reliability and availability of the node and provide basic data for the planning of the backup path.

[0090] Link information: Understand the link quality between nodes, such as signal strength, transmission delay, packet loss rate, etc. Through regular link detection and monitoring, obtain accurate link status information so that better-quality links can be selected when planning the backup path.

[0091] Network topology information: Keep track of the network topology structure in real time, including the connection relationship between nodes and the overall layout of the network. The dynamic update of the network topology information can help discover new potential paths and improve the diversity and reliability of the backup path.

[0092] Step 2, use a multi-path routing algorithm to generate multiple paths from the source node to the destination node. For example, based on an extended version of the Dijkstra algorithm or A* algorithm, by adjusting the parameters or constraints of the algorithm, different paths are generated. These algorithms can consider factors such as link quality and node energy and select the optimal backup path.

[0093] And use historical data and machine learning algorithms to predict the movement trajectory and link status of the nodes. According to the prediction results, plan the backup path in advance to cope with possible network changes. For example, by analyzing the driving rules of sanitation vehicles, predict their future positions and possible network conditions, and thus generate corresponding backup paths.

[0094] Step 3, evaluation and optimization.

[0095] Path evaluation metrics: Define evaluation metrics to measure the quality of the backup path, such as path length, transmission delay, bandwidth utilization, reliability, etc. Through the comprehensive evaluation of these metrics, select the optimal set of backup paths.

[0096] Dynamic optimization: As the network state changes, regularly evaluate and optimize the backup path. When the location, energy level, or link quality of the node changes, adjust the backup path in a timely manner to ensure that the backup path always remains in an optimal state.

[0097] Step 4, storage and management of the backup path.

[0098] Path storage: Store the generated alternative path information in a network node or a central server so that it can be quickly queried and called when needed. A database or a data structure can be used to manage the alternative path information to improve the query efficiency.

[0099] Path update: Establish an update mechanism for alternative paths. When the network topology changes or node information is updated, update the alternative path information in a timely manner. At the same time, ensure that the alternative path information among all nodes is consistent to avoid path conflicts or inconsistencies.

[0100] As a preferred embodiment of the present invention, in response to the failure of a certain node in the network topology, the remaining nodes communicatively connected to the failed node adjust their respective routing tables, remove all records pointing to the failed node, and re-determine the connection objects.

[0101] In the self-organizing network of sanitation equipment, node failure is an inevitable situation, such as the battery of a trash can running out or a hardware failure of the equipment. When a certain node fails, the nodes communicatively connected to it quickly adjust the routing table and remove the records pointing to the failed node, which can timely block the data transmission to the failed node and avoid data loss and transmission delay. The operation of re-determining the connection objects enables the network to quickly find a new communication path. For example, if a street sweeper node fails, the nearby garbage collection trucks connected to it will immediately adjust the routing table and find other trash cans or street sweepers to establish new connections, ensuring that the data transmission is not interrupted and maintaining the normal operation of the sanitation operation scheduling system. At the same time, the garbage collection truck will check whether there is an alternative planned path P ik that can reach the original target node k. If so, immediately switch to the alternative planned path P ik ; if not, start a global path search until a new valid path is found. Suppose the garbage collection truck originally reached the destination through trash can A, and now trash can A fails, it will switch to a new path through street sweeper B to reach the same destination.

[0102] This preferred embodiment greatly enhances the reliability and fault tolerance of the network, effectively preventing a large-scale network paralysis caused by a single point of failure. Even if some nodes are offline, the network can still maintain its basic functions. In the actual sanitation operation scenario, the equipment is widely distributed and often moves, and node failures occur frequently. This mechanism enables the network to quickly adapt to changes, continuously provide stable support for sanitation management, ensure the efficient and orderly progress of urban sanitation work, and also lay a solid foundation for the stable operation of the smart city sanitation system.

[0103] As a preferred embodiment of the present invention, automatically adjust the working state of each node according to the actual workload. When the time that a node is in a stationary state exceeds a preset time threshold, control the node to enter a deep sleep state.

[0104] In actual operation, sanitation equipment may be in a stationary state for a long time. For example, trash cans are waiting to be emptied when full, and street sweepers are on break. When the stationary time of a node exceeds a preset time threshold, the node is controlled to enter a deep sleep state, which can significantly reduce the energy consumption of the equipment. Taking the battery power supply system of sanitation equipment as an example, the power consumption of the equipment in the deep sleep state is significantly reduced, reducing battery wear, extending the equipment's service life, and lowering the equipment's maintenance cost and replacement frequency.

[0105] Automatically adjusting the working state of nodes according to the actual workload can enable more reasonable allocation of network resources. When the workload is low, some stationary nodes are allowed to enter the deep sleep state, which can allocate more network bandwidth and computing resources to the working nodes, improving the overall operating efficiency of the network. For example, when the sanitation workload is low at night and most sanitation equipment is in a stationary state, allowing these equipment nodes to enter the deep sleep state can ensure that the equipment still in operation, such as street lamp monitoring nodes and emergency equipment nodes, can obtain more stable and efficient network support, improving the response speed and processing capacity of the entire sanitation management system. For example, measures such as reducing the working frequency of the MCU in the SOC module, closing unused wireless communication channels, and reducing the sensor sampling frequency during low load periods can reduce energy consumption during non-essential times.

[0106] As a preferred embodiment of the present invention, the data exchange between nodes in the network topology uses the AES-256 bit symmetric encryption algorithm.

[0107] The data transmitted by the self-organizing network of sanitation equipment contains important information, such as equipment location and garbage collection volume. The AES-256 bit symmetric encryption algorithm has high-strength encryption capabilities. The 256-bit key length makes it extremely difficult to crack and can effectively resist various forms of attacks, such as brute force cracking and cryptographic analysis attacks. Even if the data is intercepted during transmission, it is difficult for attackers to obtain the sensitive information therein, thus ensuring the confidentiality, integrity, and availability of the data and maintaining the normal order of sanitation operations.

[0108] The design of this algorithm enables its encryption and decryption processes to be efficient, capable of processing a large amount of data in a short time. In the case of limited resources of sanitation equipment, such as some equipment with low computing power and storage capacity, the AES-256 bit algorithm occupies less resources and can quickly complete data encryption and decryption operations without affecting the normal operation of the equipment, ensuring the real-time nature of data transmission.

[0109] The AES-256 bit symmetric encryption algorithm is a widely used standard encryption algorithm, which is supported by many hardware and software platforms and has good compatibility. This means that in the self-organizing network of sanitation equipment, devices of different types and manufacturers can easily use this algorithm for data encryption, facilitating the integration and expansion of the system and reducing the development and maintenance costs.

[0110] In another embodiment, the present invention discloses a sanitation equipment intelligent interconnection system based on self-organizing network technology. Refer to Figure 2 As shown, the intelligent interconnection system 10 includes a first broadcast module 11, a recording module 12, a connection module 13, a second broadcast module 14 and a forwarding module 15. The first broadcast module 11 is arranged in the source node and is used to broadcast a probe request message to the surroundings; the recording module 12 is used to receive the response information fed back by the neighbor nodes; the connection module 13 is used to determine the optimal connection object based on the response information according to a preset scoring function and establish a two-way communication link with it to form a network topology; the second broadcast module 14 is used to periodically broadcast the reachability information of each node in the network topology, and the reachability information includes a reachable node list and its corresponding metric value; the forwarding module 15 is used to obtain the destination node information, calculate and determine the optimal path between the source node and the destination node as the data forwarding link.

[0111] On the one hand, the sanitation equipment intelligent interconnection system based on self-organizing network technology of the present invention can achieve autonomous and efficient networking. The first broadcast module 11 enables the source node to actively broadcast a probe request message to quickly discover potential neighbor nodes around. The recording module 12 receives the response information and provides data support for the connection module 13. The connection module 13 selects the optimal connection object according to a preset scoring function, comprehensively considering factors such as signal strength and node energy, and establishes a two-way communication link to achieve autonomous and efficient networking between devices, getting rid of the dependence on a fixed base station and being able to quickly build a stable network in a complex urban environment, such as in areas with high-rise building blockage or underground spaces, to ensure smooth communication between sanitation equipment.

[0112] On the other hand, the sanitation equipment intelligent interconnection system based on self-organizing network technology of the present invention can achieve dynamic network maintenance. The second broadcast module 14 periodically broadcasts the reachability information to enable each node to keep abreast of the network dynamics in real time. When the node position or status changes, the network topology can be updated in a timely manner. The forwarding module 15 calculates the optimal data forwarding link accordingly, such as using the AODV or Dijkstra algorithm, to ensure efficient data transmission. In the face of situations such as the movement of sanitation vehicles and equipment failures, the system can quickly adjust the path to maintain stable data transmission and improve the network adaptability and reliability.

[0113] The intelligent interconnection system for environmental sanitation equipment based on ad hoc network technology according to the present invention ensures accurate and timely data transmission, enabling the environmental sanitation management department to real-time master information such as the location and working status of the equipment, and reasonably allocate resources. For example, according to the data of garbage collection trucks and trash cans, the collection route is optimized, improving the operation efficiency, reducing the waste of human and material resources, promoting the intelligent upgrade of environmental sanitation management, and contributing to the construction of a smart city.

[0114] The above embodiments are only preferred embodiments given to fully illustrate the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or transformations made by those skilled in the art on the basis of the present invention are within the protection scope of the present invention.

Claims

1. An intelligent interconnection method for environmental sanitation equipment based on ad-hoc network technology, characterized in that, including: The source node broadcasts a probe request message to the surroundings while receiving response information fed back by neighbor nodes; Based on the response information, determine the optimal connection object according to a preset scoring function, and establish a two-way communication link with it to form a network topology; Each node in the network topology periodically broadcasts its own reachability information, and the reachability information includes a list of reachable nodes and their corresponding metric values; Obtain the destination node information, calculate and determine the optimal path between the source node and the destination node as the data forwarding link.

2. The intelligent interconnection method for environmental sanitation equipment based on ad hoc network technology according to claim 1, wherein, The preset scoring function is: S i = α·RSSI i + β·energy_level i + γ·proximity i ; Where S i is the total score of the i-th neighbor node, RSSI i is the received signal strength indication value of the i-th neighbor node, energy_level i is the energy level of the i-th neighbor node, proximity i is the distance between the source node and the i-th neighbor node, α is the weight coefficient of the signal strength, β is the weight coefficient of the energy level, and γ is the weight coefficient of the geographical location.

3. The intelligent interconnection method of sanitation equipment based on ad hoc network technology according to claim 1, characterized in that: Each node in the network topology regularly reports its own operating status to neighbor nodes with which a two-way communication link is established, and at the same time listens for status reports from other nodes in the network topology; Evaluate the operating status of the nodes in the network topology according to a preset evaluation function. When the evaluation value exceeds the preset threshold, the node re-determines the connection object.

4. The intelligent interconnection method for environmental sanitation equipment based on the ad hoc network technology according to claim 3, characterized in that The preset evaluation function is: w = a·link_quality + b·node_mobility + c·energy_level + d·network_load; In the formula, w is the evaluation value of the node's operating status; link_quality is the link quality, indicating the stability of the communication link between nodes; node_mobility is the node mobility, indicating the stability of the node's moving speed and moving direction; energy_level represents the node energy level, indicating the current battery percentage of the node; network_load is the network load, indicating the amount of data currently processed by the node and the busyness of communication tasks; a is the weight coefficient of the link quality, used to adjust the influence degree of the link quality on the node's operating status in the evaluation function; b is the weight coefficient of the node mobility, used to adjust the influence degree of the node mobility on the node's operating status in the evaluation function; c is the weight coefficient of the node energy level, used to adjust the influence degree of the energy level on the node's operating status in the evaluation function; d is the weight coefficient of the network load, used to adjust the influence degree of the network load on the node's operating status in the evaluation function.

5. The intelligent interconnection method for environmental sanitation equipment based on ad-hoc network technology according to claim 1, characterized in that: There are also several standby planned paths between the source node and the destination node. When the data forwarding link is not the optimal path, the standby planned path is enabled for data forwarding.

6. The intelligent interconnection method for environmental sanitation equipment based on the ad-hoc network technology according to claim 1, characterized in that: In response to the failure of a certain node in the network topology, the remaining nodes communicating with the failed node adjust their respective routing tables, remove all records pointing to the failed node, and re-determine the connection object.

7. The intelligent interconnection method for environmental sanitation equipment based on ad hoc network technology according to claim 1, characterized in that: Automatically adjust the working status of each node according to the actual workload. When the time for a node to be in a stationary state exceeds the preset time threshold, control the node to enter deep sleep.

8. The intelligent interconnection method for environmental sanitation equipment based on ad hoc network technology according to claim 1, characterized in that: The data exchange between each node in the network topology adopts the AES-256-bit symmetric encryption algorithm.

9. An intelligent interconnection system for environmental sanitation equipment based on ad hoc network technology, characterized in that, including: The first broadcast module, arranged in the source node, is used to broadcast a probe request message to the surroundings; The recording module is used to receive response information fed back by neighbor nodes; The connection module is used to determine the optimal connection object according to a preset scoring function based on the response information, and establish a two-way communication link with it to form a network topology; The second broadcast module is used to periodically broadcast the reachability information of each node in the network topology, and the reachability information includes a list of reachable nodes and their corresponding metric values; The forwarding module is used to obtain destination node information, calculate and determine the optimal path between the source node and the destination node as the data forwarding link.

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