Internet of Things multi-stage communication method and system for city management

Abstract

The invention discloses an Internet of Things multi-stage communication method and system for city management, and relates to the technical field of Internet of Things communication, and the method comprises the following steps: monitoring the state of Internet of Things equipment, collecting the state data of the equipment, analyzing the historical use data of the Internet of Things equipment, and determining the data transmission demands of the Internet of Things equipment. According to the Internet of Things multi-stage communication method and system for city management, through the energy consumption and performance analysis module, the operation state and performance of the Internet of Things equipment are monitored and evaluated in real time, the energy consumption bottleneck and the performance decline sign of the equipment are identified, early warning is given out in time, and corresponding optimization measures are suggested to be taken, so that the city management efficiency is improved. The service life of the equipment is effectively prolonged, downtime and maintenance cost caused by equipment faults are reduced, meanwhile, parameter settings such as a dormancy awakening strategy are intelligently adjusted according to the actual use condition of the equipment, and the energy consumption and operation cost of the equipment are further reduced.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things communication technology, and in particular to an Internet of Things multi-level communication method and system for city management. Background Art

[0002] With the acceleration of urbanization, urban management is facing increasingly complex challenges. As a close combination of new generation information technology and urban development, smart cities provide intelligent solutions for urban management by integrating advanced technologies such as the Internet of Things, big data, and cloud computing. The multi-level communication method of the Internet of Things, as one of the key technologies for building smart cities, is of great significance for realizing the refinement and intelligence of urban management.

[0003] In the multi-level communication of the Internet of Things, the Internet of Things devices usually need to run for a long time. Frequent data transmission will increase the energy consumption of the device and shorten the battery life. Therefore, how to implement the sleep wake-up mechanism according to the actual use of the device, put the device into sleep state when data transmission is not needed, reduce energy consumption, and achieve optimal use of resources is the problem we need to solve. To this end, a multi-level communication method and system of the Internet of Things for urban management is proposed. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: In the first aspect, a multi-level communication method of the Internet of Things for urban management comprises the following steps:

[0005] Step 1: Monitor the status of IoT devices and collect device status data, analyze the historical usage data of IoT devices, and clarify the data transmission requirements of each IoT device;

[0006] Step 2: According to the results of IoT device status monitoring and the analyzed data transmission requirements, IoT devices are classified into different categories, and corresponding sleep and wake-up conditions are set for each IoT device based on time, data transmission frequency, and power level. When the IoT device meets the sleep conditions, the sleep strategy is executed;

[0007] Step 3: Develop a corresponding sleep and wake-up strategy for each IoT device category, determine the wake-up conditions, and define the duration and wake-up frequency of the sleep state;

[0008] Step 4: After the IoT device is awakened, data transmission and status update are performed, and the energy consumption and battery life of the IoT device are monitored, and the energy consumption trend and battery life status of the device are analyzed;

[0009] Step 5: Based on the historical usage data of IoT devices, combined with the analysis results of device energy consumption trends and battery life status, evaluate the effectiveness of the sleep and wake-up strategy, preset the optimization level, determine the corresponding optimization level based on the evaluation results, and adjust the sleep and wake-up strategy to further optimize energy consumption and performance.

[0010] Preferably, in step 1, the process of analyzing data transmission requirements includes:

[0011] Connect IoT devices to the IoT platform through the network (such as Wi-Fi, Bluetooth, Zigbee, LoRaWAN, 4G / 5G, etc.), set the frequency of data collection according to application requirements, and use the built-in sensors of IoT devices (such as temperature sensors, humidity sensors, pressure sensors, etc.) to obtain various original status data of IoT devices;

[0012] After preprocessing (data cleaning, noise filtering, data fusion), the original status data is sent to the IoT platform, which receives the status data from IoT devices and stores it in the data warehouse;

[0013] Extract the historical usage data of IoT devices from the data warehouse and analyze the historical usage data, analyze the frequency of device data transmission, determine the data transmission pattern, determine which devices need to transmit data frequently and which devices can reduce the transmission frequency, analyze the amount of data transmitted each time, and evaluate the demand for data transmission.

[0014] Preferably, in step 2, the process of classifying IoT devices includes:

[0015] According to the results of equipment status monitoring and the analyzed data transmission requirements, analyze the frequency and amount of equipment data transmission, and determine which equipment data has high real-time requirements and which can be transmitted during non-peak hours;

[0016] Based on the working mode and data transmission requirements of IoT devices, IoT devices are divided into different categories, namely real-time monitoring devices, periodic reporting devices, and battery-powered devices;

[0017] Set different sleep and wake-up conditions for different categories of IoT devices. For example, set time-based sleep and wake-up conditions for periodic reporting devices, so that they enter sleep mode during non-working hours; set sleep and wake-up conditions based on data transmission frequency for real-time monitoring devices, so that they enter sleep mode when data changes little; set sleep and wake-up conditions based on power level for battery-powered devices, so that when the power level is lower than the preset threshold, the sleep mechanism is triggered to save power;

[0018] Develop a sleep strategy for IoT devices, including the duration of the sleep state and the frequency of wake-up, and determine the operations to be performed after wake-up, and execute the sleep strategy. When the device meets the sleep conditions, the IoT platform sends a sleep command to the IoT device. After receiving the command, the IoT device executes the necessary operations before sleep, such as saving the current state and shutting down non-essential functions, and enters sleep. During the device's sleep period, the IoT platform continuously monitors the state changes of the IoT device. If the IoT device experiences a sudden drop in power during sleep or receives an emergency wake-up signal, the wake-up mechanism is triggered.

[0019] Preferably, in step 3, the process of defining the duration of the sleep state and the wake-up frequency includes:

[0020] For real-time monitoring equipment, analyze its data change frequency and real-time requirements, determine the conditions for sleep and wake-up, set the conditions for entering the sleep state when the data change frequency is lower than the preset threshold, and set the wake-up conditions based on data changes. Wake up from the sleep state when abnormal data changes are detected and specific instructions are received. After receiving the wake-up instruction, the IoT device immediately resumes data monitoring and transmission;

[0021] For periodic reporting devices, analyze their reporting cycle and data collection frequency, determine the data collection frequency of IoT devices in non-reporting periods, determine the time points for sleep and wake-up, and set time-based wake-up conditions to automatically wake up before the scheduled reporting time to prepare data reports;

[0022] For battery-powered devices, analyze the power consumption pattern of IoT devices, determine the peak and trough of power consumption, evaluate the data transmission needs of IoT devices, determine the time nodes when data transmission can be reduced to save power, determine the sleep and wake-up strategy to extend battery life, set the conditions for entering the sleep state when the power is lower than the preset threshold, and set the wake-up conditions based on the power, set the conditions for waking up when the power returns to the preset level or receives the data transmission wake-up command, and the device resumes data transmission after the power is sufficient or the wake-up command is received;

[0023] When the IoT device meets the wake-up conditions, the IoT platform sends a wake-up instruction to the IoT device. After receiving the instruction, the IoT device executes the wake-up operation and resumes normal working state. The wake-up conditions are reaching the preset wake-up time, receiving the wake-up signal, or the power is restored to the preset level.

[0024] Preferably, in step 4, the process of analyzing the device energy consumption trend and battery life status includes:

[0025] After the IoT device is awakened, it establishes a stable communication connection with the IoT platform to ensure the reliability and real-time performance of data transmission, and starts collecting and transmitting data. The collected data is packaged and sent to the IoT platform through the communication network. During the data transmission process, the device should ensure the integrity and security of the data to avoid data loss or leakage;

[0026] The IoT device sends its current status information to the IoT platform, including operating status, power level, and fault status. The IoT platform updates the status record of the IoT device based on the received status information and provides a basis for subsequent management and maintenance;

[0027] Monitor the energy consumption of IoT devices in the awake state, and use the built-in sensors of IoT devices to collect energy consumption data of IoT devices, including CPU usage, network transmission power consumption, and sensor power consumption. Based on the collected energy consumption data, calculate the device energy consumption evaluation index and evaluate the energy efficiency of the device.

[0028] For battery-powered IoT devices, the built-in battery management system monitors the battery status, including battery voltage, current, temperature, and power parameters, and records the battery's charge and discharge times, capacity decay rate, and power consumption rate information. Based on the battery status monitoring data and combined with the battery aging model, the battery life assessment index is calculated to analyze the battery life status.

[0029] Preferably, the calculation expression of the equipment energy consumption evaluation index is:

[0030]

[0031] Among them, EI is the equipment energy consumption evaluation index, P i is the power consumption of the i-th sensor, n is the total number of sensors, E base is the baseline energy consumption value of the device, C is the CPU usage, and C base is the baseline value of CPU usage, λ is the sensitivity coefficient of CPU usage change, T is the network transmission power consumption of the device, P t is the network transmission power consumption of the sensor, P s is the average network transmission power consumption of all sensors. The value range of EI is [0, +∞), where 0 represents the lowest energy efficiency. The larger the value of EI, the higher the energy efficiency.

[0032] The calculation expression of the battery life evaluation index is:

[0033]

[0034] Among them, BI is the battery life assessment index, R j is the battery capacity measured for the jth time, m is the number of battery measurements, Era is the rated energy of the battery, E cu is the current energy of the battery, ∈ is a very small constant to prevent division by zero, N cy is the actual charge and discharge times of the battery, N cybase is the benchmark charge and discharge times determined based on the battery type and usage conditions, δ is the influence coefficient of battery temperature on battery life, which is used to adjust the influence of temperature on battery life assessment, and W avg is the average operating temperature of the battery. The value range of BI is (0, +∞). A value close to 0 indicates that the battery life is about to end. The larger the value of BI, the better the battery life status.

[0035] Preferably, in step 5, the evaluation process of the sleep-wake-up strategy effect includes:

[0036] Collect historical usage data of IoT devices, including sleep time, wake-up times, wake-up duration, data transmission volume after each wake-up, device energy consumption, and collect current energy consumption data and battery status information of IoT devices;

[0037] Analyze the energy consumption trend of the equipment, including the change of energy consumption over time, peak and valley, determine the energy consumption pattern of the equipment in different time periods, and analyze the life status of the battery, including the battery capacity attenuation, charge and discharge times and average operating temperature, and predict the remaining life and performance of the battery;

[0038] Combine historical usage data and energy consumption trend analysis results, integrate the device energy consumption evaluation index and battery life evaluation index, calculate the sleep evaluation coefficient, compare the sleep evaluation coefficient under the current sleep and wake-up strategy with historical data, compare the performance differences of the devices under the sleep and wake-up strategy, and evaluate the actual effect of the sleep and wake-up strategy based on the changes in the sleep evaluation coefficient;

[0039] According to the evaluation results, different optimization levels are preset, namely low optimization level, medium optimization level and high optimization level, and the corresponding optimization threshold is matched for each optimization level in combination with the dormancy evaluation coefficient. Each optimization level corresponds to different optimization goals and strategy adjustment directions;

[0040] According to the evaluation results and optimization level, adjust the sleep and wake-up strategies of IoT devices, including adjusting the sleep time interval, optimizing the wake-up process, improving the data transmission strategy, and replacing energy-efficient hardware components. After the strategy is adjusted, implement a new sleep and wake-up strategy, continuously monitor the energy consumption and performance of the device, collect feedback data, evaluate the actual effect of the new strategy, and continuously iterate and optimize the sleep and wake-up strategy based on the test results and continuously monitored data.

[0041] Preferably, the calculation expression of the sleep evaluation coefficient is:

[0042]

[0043] Among them, SAI is the dormancy assessment coefficient, EI k is the equipment energy consumption evaluation index measured for the kth time, reflecting the efficiency of equipment energy consumption, BI k is the battery life evaluation index of the kth measurement, reflecting the battery health status and expected life, N is the number of measurements, is an adjustment factor used to measure the relative importance of battery life to energy consumption assessment, E base is the benchmark energy consumption value, used for normalized energy consumption assessment, L cu is the current estimated battery life, L in The SAI is the initial life evaluation value of the battery. The value range of SAI is (0, +∞). A value close to 0 indicates that the sleep evaluation coefficient is poor, and the current sleep wake-up strategy is not effective and needs to be optimized. The larger the SAI value, the more effective the sleep wake-up strategy.

[0044] Preferably, the plurality of optimization levels correspond to the plurality of optimization thresholds, the optimization thresholds include an upper threshold and a lower threshold, and the correspondence between the plurality of optimization levels and the plurality of optimization thresholds is:

[0045] Low optimization level 0 <SAI≤SAI A ;

[0046] Medium optimization level SAI A <SAI≤SAI B ;

[0047] High optimization level SAI>SAI B ;

[0048] Among them, MC is the dormancy assessment coefficient, MC MP is the lower threshold corresponding to the high matching level and the upper threshold corresponding to the medium matching level, MC LP The lower threshold corresponding to the medium matching level and the upper threshold corresponding to the low matching level.

[0049] In a second aspect, an Internet of Things multi-level communication system for city management is used to implement an Internet of Things multi-level communication method for city management, including an Internet of Things platform, wherein the Internet of Things platform is communicatively connected with a data acquisition module, a data transmission module, a data processing module, a sleep and wake-up management module, an energy consumption and performance analysis module, a strategy optimization module, and a monitoring module, wherein electrical signals are connected between the modules;

[0050] The data collection module is used to collect raw data from various IoT devices in the city, including device status, environmental parameters, and usage, to ensure the real-time and accuracy of the data and provide a basis for subsequent analysis and decision-making;

[0051] The data transmission module transmits the collected data to the IoT platform wirelessly, supports a multi-level communication architecture, ensures efficient data transmission between different levels, improves the reliability and speed of data transmission, reduces latency, and supports real-time processing of large-scale data;

[0052] The data processing module is used to process, analyze and store the collected raw data, including data cleaning, fusion, analysis, extracting useful information, providing support for decision-making, and reducing data storage costs;

[0053] The sleep and wake-up management module controls the sleep and wake-up of the device according to the working mode and data transmission requirements of the device, so as to optimize energy consumption, reduce the energy consumption of the device, extend the battery life, and improve the sustainable operation capability of the system;

[0054] The energy consumption and performance analysis module uses historical data and real-time data to analyze the energy consumption trend, battery life, and performance of IoT devices, calculate the sleep evaluation coefficient, identify energy consumption bottlenecks and performance optimization points, and provide a basis for adjusting the sleep and wake-up strategy to achieve the optimal balance between energy consumption and performance.

[0055] The strategy optimization module presets different optimization levels and thresholds based on the analysis results, formulates and adjusts the sleep and wake-up strategies of IoT devices, improves the intelligent level of urban management, reduces operating costs, extends the service life of equipment, and improves user experience;

[0056] The monitoring module deploys the optimized strategy to the IoT devices and continuously monitors the operating status and performance of the devices to ensure the effective implementation of the strategy, timely discover and solve problems, and ensure the continuity and stability of urban management.

[0057] The present invention provides an Internet of Things multi-level communication method and system for urban management.

[0058] Beneficial effects:

[0059] 1. The multi-level communication method and system of the Internet of Things for urban management, through the energy consumption and performance analysis module, monitors and evaluates the operating status and performance of the Internet of Things equipment in real time, identifies the energy consumption bottleneck and performance degradation signs of the equipment, issues early warnings in time and recommends taking corresponding optimization measures, effectively extending the service life of the equipment, reducing the downtime and maintenance costs caused by equipment failure, and at the same time, intelligently adjusts parameter settings such as the sleep and wake-up strategy according to the actual use of the equipment, further reducing the energy consumption and operating costs of the equipment.

[0060] 2. The multi-level communication method and system of the Internet of Things for urban management optimizes energy distribution, improves the efficiency of energy use, and predicts equipment energy consumption trends and performance degradation, so as to carry out maintenance and replacement in advance, reduce unexpected downtime, and ensure the continuity and reliability of urban services. Through refined management, the Internet of Things technology not only improves the efficiency of resource use, but also reduces long-term operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A method flow chart of a multi-level communication method and system of the Internet of Things for city management according to the present invention;

[0062] Figure 2 It is a flow chart for analyzing the energy consumption trend and battery life status of the device of the present invention;

[0063] Figure 3 This is a flow chart for evaluating the effect of the sleep-wake-up strategy of the present invention;

[0064] Figure 4 This is a diagram of the module structure of the present invention. DETAILED DESCRIPTION

[0065] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0066] The first embodiment, as Figure 1 , Figure 2 As shown, the present invention provides a technical solution: a multi-level communication method of the Internet of Things for urban management, comprising the following steps:

[0067] Step 1: Monitor the status of IoT devices and collect device status data, analyze the historical usage data of IoT devices, clarify the data transmission requirements of each IoT device, connect IoT devices to the IoT platform through the network (such as Wi-Fi, Bluetooth, Zigbee, LoRaWAN, 4G / 5G, etc.), set the frequency of data collection according to application requirements, and use the built-in sensors of IoT devices (such as temperature sensors, humidity sensors, pressure sensors, etc.) to obtain various original status data of IoT devices. After preprocessing (data cleaning, noise filtering, data fusion), the original status data is sent to the IoT platform. The IoT platform receives the status data from IoT devices and stores it in the data warehouse. The historical usage data of IoT devices is extracted from the data warehouse and analyzed. The frequency of device data transmission is analyzed to determine the mode of data transmission, determine which devices need to transmit data frequently and which devices can reduce the transmission frequency, analyze the amount of data transmitted each time, and evaluate the demand for data transmission;

[0068] Step 2. According to the results of IoT device status monitoring and the analyzed data transmission requirements, IoT devices are divided into different categories, and corresponding sleep and wake-up conditions are set for each IoT device based on time, data transmission frequency, and power level. When the IoT device meets the sleep conditions, the sleep strategy is executed. According to the results of device status monitoring and the analyzed data transmission requirements, the frequency and data volume of device data transmission are analyzed to determine which devices have high real-time data requirements and which can be transmitted during non-peak hours. Based on the working mode and data transmission requirements of IoT devices, IoT devices are divided into different categories, namely real-time monitoring devices, periodic reporting devices, and battery-powered devices. Different sleep and wake-up conditions are set for different categories of IoT devices. Among them, time-based sleep and wake-up conditions are set for periodic reporting devices, and they enter the sleep mode during non-working hours. Sleep state: set sleep and wake-up conditions based on data transmission frequency for real-time monitoring devices, and enter sleep state when data changes little. Set sleep and wake-up conditions based on power level for battery-powered devices. When the power is lower than the preset threshold, trigger the sleep mechanism to save power. Formulate sleep strategies for IoT devices, including the duration of sleep state and wake-up frequency, and determine the operations to be performed after wake-up. Execute the sleep strategy. When the device meets the sleep conditions, the IoT platform sends a sleep command to the IoT device. After receiving the command, the IoT device executes the necessary operations before sleep, such as saving the current state and shutting down non-essential functions, and enters sleep state. During the device sleep period, the IoT platform continuously monitors the state changes of the IoT device. If the IoT device suddenly drops in power during sleep or receives an emergency wake-up signal, the wake-up mechanism is triggered.

[0069] Step 3. Develop a corresponding sleep and wake-up strategy for each IoT device category, determine the wake-up conditions, define the duration of the sleep state and the wake-up frequency. For real-time monitoring devices, analyze their data change frequency and real-time requirements, determine the sleep and wake-up conditions, set the conditions for entering the sleep state when the data change frequency is lower than the preset threshold, and set the wake-up conditions based on data changes. Wake up from the sleep state when abnormal data changes are detected and specific instructions are received. After receiving the wake-up command, the IoT device immediately resumes data monitoring and transmission. For periodic reporting devices, analyze their reporting cycle and data collection frequency, determine the data collection frequency of IoT devices in non-reporting cycles, so as to determine the time points of sleep and wake-up, and set time-based wake-up conditions. Automatically wake up before the scheduled reporting time and prepare data reports. For battery-powered devices, analyze the power consumption pattern of IoT devices, determine the peak and trough of power consumption, evaluate the data transmission needs of IoT devices, determine the time nodes where data transmission can be reduced to save power, determine the sleep and wake-up strategy to extend battery life, set the conditions for entering the sleep state when the power is below a preset threshold, and set the wake-up conditions based on the power level, set the conditions for waking up when the power is restored to a preset level or a data transmission wake-up instruction is received, and the device resumes data transmission after the power is sufficient or the wake-up instruction is received. When the IoT device meets the wake-up conditions, the IoT platform sends a wake-up instruction to the IoT device. After receiving the instruction, the IoT device executes the wake-up operation and resumes normal working state, where the wake-up conditions are reaching the preset wake-up time, receiving the wake-up signal, or the power is restored to the preset level;

[0070] Step 4: After the IoT device is awakened, data transmission and status update are performed, and the energy consumption and battery life of the IoT device are monitored, and the energy consumption trend and battery life status of the device are analyzed. After the IoT device is awakened, a stable communication connection is established with the IoT platform to ensure the reliability and real-time performance of data transmission, and data collection and transmission are started. The collected data is packaged and sent to the IoT platform through the communication network. During the data transmission process, the device should ensure the integrity and security of the data to avoid data loss or leakage. The IoT device sends its current status information to the IoT platform, including operating status, power level, and fault status. The IoT platform updates the status record of the IoT device based on the received status information. Record and provide a basis for subsequent management and maintenance. Monitor the energy consumption of IoT devices in the wake-up state, and use the built-in sensors of IoT devices to collect energy consumption data of IoT devices, including CPU usage, network transmission power consumption, and sensor power consumption. According to the collected energy consumption data, calculate the device energy consumption evaluation index and evaluate the energy efficiency of the device. For battery-powered IoT devices, monitor the battery status through the built-in battery management system, including battery voltage, current, temperature, and power parameters, and record the number of battery charge and discharge, capacity decay rate, and power consumption speed information. According to the battery status monitoring data, combined with the battery aging model, calculate the battery life evaluation index to analyze the battery life status;

[0071] Furthermore, the calculation expression of the equipment energy consumption evaluation index is:

[0072]

[0073] Among them, EI is the equipment energy consumption evaluation index, P i is the power consumption of the i-th sensor, n is the total number of sensors, E base is the baseline energy consumption value of the device, C is the CPU usage, and C base is the baseline value of CPU usage, λ is the sensitivity coefficient of CPU usage change, T is the network transmission power consumption of the device, P t is the network transmission power consumption of the sensor, P s is the average network transmission power consumption of all sensors. The value range of EI is [0, +∞), where 0 represents the lowest energy efficiency. The larger the value of EI, the higher the energy efficiency. i When the sensor power consumption increases, EI decreases, indicating that the energy efficiency decreases. When C approaches C base When the exponential part is close to E base , has little effect on EI. When C is far away from C base When T increases, the value of the logarithmic function will also increase, so that EI decreases, indicating that the energy efficiency is reduced. When Pt Relative P s When smaller, The smaller the value of is, the larger the EI is, indicating that the energy efficiency is improved;

[0074] The calculation expression of the battery life evaluation index is:

[0075]

[0076] Among them, BI is the battery life assessment index, R j is the battery capacity measured for the jth time, m is the number of battery measurements, E ra is the rated energy of the battery, E cu is the current energy of the battery, ∈ is a very small constant to prevent division by zero, N cy is the actual charge and discharge times of the battery, N cybase is the benchmark charge and discharge times determined based on the battery type and usage conditions, δ is the influence coefficient of battery temperature on battery life, which is used to adjust the influence of temperature on battery life assessment, and W avg is the average operating temperature of the battery. The value range of BI is (0, +∞). A value close to 0 indicates that the battery life is about to end. The larger the value of BI is, the better the battery life is. j During attenuation, the square root term decreases, resulting in a decrease in BI, indicating a decrease in battery life. cy Increase, approach or exceed the benchmark charge and discharge times N cybase When the logarithmic function value increases, BI decreases, indicating battery aging. When the average operating temperature of the battery W avg As the exponential increases, Decreased, indicating shorter battery life;

[0077] Step 5: Based on the historical usage data of IoT devices, combined with the analysis results of device energy consumption trends and battery life status, evaluate the effectiveness of the sleep and wake-up strategy, preset the optimization level, determine the corresponding optimization level based on the evaluation results, and adjust the sleep and wake-up strategy to further optimize energy consumption and performance.

[0078] The second embodiment is based on the first embodiment. Figure 3 As shown, in step 5, the evaluation process of the sleep-wake-up strategy effect includes:

[0079] Collect historical usage data of IoT devices, including sleep time, wake-up times, wake-up duration, data transmission volume after each wake-up, and device energy consumption. Collect current energy consumption data and battery status information of IoT devices, analyze energy consumption trends of devices, including changes in energy consumption over time, peaks and valleys, determine energy consumption patterns of devices in different time periods, and analyze battery life status, including battery capacity attenuation, charge and discharge times, and average operating temperature, predict remaining battery life and performance, combine historical usage data and energy consumption trend analysis results, integrate device energy consumption evaluation index and battery life evaluation index, calculate sleep evaluation coefficient, compare sleep evaluation coefficient under current sleep and wake-up strategy with historical data, compare performance differences of devices under sleep and wake-up strategies, and According to the change of the sleep evaluation coefficient, the actual effect of the sleep wake-up strategy is evaluated. According to the evaluation results, different optimization levels are preset, namely low optimization level, medium optimization level and high optimization level, and the corresponding optimization threshold is matched for each optimization level in combination with the sleep evaluation coefficient. Each optimization level corresponds to different optimization goals and strategy adjustment directions. According to the evaluation results and optimization level, the sleep wake-up strategy of the IoT device is adjusted, including adjusting the sleep time interval, optimizing the wake-up process, improving the data transmission strategy, and replacing high-efficiency hardware components. After the strategy is adjusted, a new sleep wake-up strategy is implemented, the energy consumption and performance of the device are continuously monitored, feedback data is collected, the actual effect of the new strategy is evaluated, and the sleep wake-up strategy is continuously optimized iteratively based on the test results and continuously monitored data;

[0080] Furthermore, the calculation expression of the dormancy evaluation coefficient is:

[0081]

[0082] Among them, SAI is the dormancy assessment coefficient, EI k is the equipment energy consumption evaluation index measured for the kth time, reflecting the efficiency of equipment energy consumption, BI k is the battery life evaluation index of the kth measurement, reflecting the battery health status and expected life, N is the number of measurements, is an adjustment factor used to measure the relative importance of battery life to energy consumption assessment, E base is the benchmark energy consumption value, used for normalized energy consumption assessment, L cu is the current estimated battery life, L in The SAI value is the initial battery life evaluation value. The SAI value range is (0, +∞). A value close to 0 indicates that the sleep evaluation coefficient is poor. The current sleep wake-up strategy is not effective and needs to be optimized. The larger the SAI value, the more effective the sleep wake-up strategy is. The device consumes less energy while maintaining performance. When EI k When the power consumption increases, the SAI decreases, which means that the sleep and wake-up strategy needs to be adjusted to reduce power consumption. cuWith L in When the ratio decreases, that is, the battery life decreases, the value in the square root decreases, and SAI decreases, which means that the battery performance is degraded. You may need to consider replacing the battery or optimizing the strategy to extend the battery life. When increases, the exponential function decreases faster, indicating that the battery life evaluation has a greater impact on the sleep evaluation coefficient;

[0083] Furthermore, multiple optimization levels correspond to multiple optimization thresholds, and the optimization thresholds include an upper threshold and a lower threshold. The corresponding relationship between the multiple optimization levels and the multiple optimization thresholds is:

[0084] Low optimization level 0 <SAI≤SAI A Maintain the basic performance of the device, moderately reduce energy consumption, fine-tune the sleep time, and optimize the transmission frequency of non-critical data;

[0085] Medium optimization level SAI A <SAI≤SAI B ; Balance device performance and energy consumption, achieve moderate energy consumption reduction, adjust wake-up cycle, optimize data transmission strategy, and implement dynamic sleep strategy;

[0086] High optimization level SAI>SAI B ; Maximize energy consumption reduction, which may sacrifice some performance, significantly extend sleep time, optimize data processing flow, and reduce unnecessary data transmission;

[0087] Among them, MC is the dormancy assessment coefficient, MC MP is the lower threshold corresponding to the high matching level and the upper threshold corresponding to the medium matching level, MC LP The lower threshold corresponding to the medium matching level and the upper threshold corresponding to the low matching level.

[0088] The third embodiment is based on the first and second embodiments. Figure 4 As shown, the present invention also provides a technical solution: an Internet of Things multi-level communication system for city management, used to implement an Internet of Things multi-level communication method for city management, including an Internet of Things platform, the Internet of Things platform is communicatively connected with a data acquisition module, a data transmission module, a data processing module, a sleep and wake-up management module, an energy consumption and performance analysis module, a strategy optimization module and a monitoring module, wherein the modules are connected by electrical signals;

[0089] The data collection module is used to collect raw data from various IoT devices in the city, including device status, environmental parameters, and usage, to ensure the real-time and accuracy of the data and provide a basis for subsequent analysis and decision-making;

[0090] The data transmission module transmits the collected data to the IoT platform wirelessly, supports a multi-level communication architecture, ensures efficient data transmission between different levels, improves the reliability and speed of data transmission, reduces latency, and supports real-time processing of large-scale data;

[0091] Data processing module, used to process, analyze and store the collected raw data, including data cleaning, fusion, analysis, extracting useful information, providing support for decision-making, and reducing data storage costs;

[0092] The sleep and wake-up management module controls the sleep and wake-up of the device according to the device's working mode and data transmission requirements to optimize energy consumption, reduce the device's energy consumption, extend battery life, and improve the system's sustainable operation capability;

[0093] The energy consumption and performance analysis module uses historical data and real-time data to analyze the energy consumption trend, battery life, and performance of IoT devices, calculate the sleep evaluation coefficient, identify energy consumption bottlenecks and performance optimization points, and provide a basis for adjusting the sleep and wake-up strategy to achieve the optimal balance between energy consumption and performance;

[0094] The strategy optimization module presets different optimization levels and thresholds based on the analysis results, formulates and adjusts the sleep and wake-up strategies of IoT devices, improves the intelligent level of urban management, reduces operating costs, extends the service life of equipment, and improves user experience;

[0095] The monitoring module deploys the optimized strategies to IoT devices and continuously monitors the operating status and performance of the devices to ensure the effective implementation of the strategies, timely discover and solve problems, and ensure the continuity and stability of urban management.

[0096] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A multi-level communication method of the Internet of Things for urban management, characterized in that: The following steps are involved: Step 1: Monitor the status of IoT devices and collect device status data, analyze the historical usage data of IoT devices, and clarify the data transmission requirements of each IoT device; Step 2: According to the results of IoT device status monitoring and the analyzed data transmission requirements, IoT devices are classified into different categories, and corresponding sleep and wake-up conditions are set for each IoT device based on time, data transmission frequency, and power level. When the IoT device meets the sleep conditions, the sleep strategy is executed; Step 3: Develop a corresponding sleep and wake-up strategy for each IoT device category, determine the wake-up conditions, and define the duration and wake-up frequency of the sleep state; Step 4: After the IoT device is awakened, data transmission and status update are performed, and the energy consumption and battery life of the IoT device are monitored, and the energy consumption trend and battery life status of the device are analyzed; Step 5: Based on the historical usage data of IoT devices, combined with the analysis results of device energy consumption trends and battery life status, evaluate the effectiveness of the sleep and wake-up strategy, preset the optimization level, determine the corresponding optimization level based on the evaluation results, and adjust the sleep and wake-up strategy to further optimize energy consumption and performance.

2. The multi-level communication method of the Internet of Things for urban management according to claim 1, characterized in that: In step 1, the process of analyzing data transmission requirements includes: Connect IoT devices to the IoT platform through the network, set the frequency of data collection according to application requirements, and use the built-in sensors of IoT devices to obtain various original status data of IoT devices; After preprocessing, the raw status data is sent to the IoT platform, which receives the status data from IoT devices and stores it in the data warehouse; Extract the historical usage data of IoT devices from the data warehouse and analyze the historical usage data, analyze the frequency of device data transmission, determine the data transmission mode, analyze the amount of data transmitted each time, and evaluate the demand for data transmission.

3. The multi-level communication method of the Internet of Things for urban management according to claim 2, characterized in that: In the step 2, the process of classifying IoT devices includes: Analyze the frequency and amount of equipment data transmission based on the results of equipment status monitoring and analyzed data transmission requirements; Based on the working mode and data transmission requirements of IoT devices, IoT devices are divided into different categories, namely real-time monitoring devices, periodic reporting devices, and battery-powered devices; Set different sleep and wake-up conditions for different categories of IoT devices. For example, set time-based sleep and wake-up conditions for periodic reporting devices, which enter sleep mode during non-working hours; set sleep and wake-up conditions based on data transmission frequency for real-time monitoring devices; set sleep and wake-up conditions based on power level for battery-powered devices. When the power level is lower than the preset threshold, the sleep mechanism is triggered to save power. Develop a sleep strategy for IoT devices, including the duration of the sleep state and the frequency of wake-up, and determine the operations to be performed after wake-up, and execute the sleep strategy. When the device meets the sleep conditions, the IoT platform sends a sleep command to the IoT device. After receiving the command, the IoT device executes the operations of saving the current state and shutting down non-essential functions before sleep, and enters the sleep state. During the device's sleep period, the IoT platform continuously monitors the state changes of the IoT device. If the IoT device experiences a sudden drop in power during sleep or receives an emergency wake-up signal, the wake-up mechanism is triggered.

4. The multi-level communication method of the Internet of Things for city management according to claim 3 is characterized in that: In step 3, the process of defining the duration of the sleep state and the wake-up frequency includes: For real-time monitoring equipment, analyze its data change frequency and real-time requirements, determine the conditions for sleep and wake-up, set the conditions for entering the sleep state when the data change frequency is lower than the preset threshold, and set the wake-up conditions based on data changes. Wake up from the sleep state when abnormal data changes are detected and specific instructions are received. After receiving the wake-up instruction, the IoT device immediately resumes data monitoring and transmission; For periodic reporting devices, analyze their reporting cycle and data collection frequency, determine the data collection frequency of IoT devices in non-reporting periods, determine the time points for sleep and wake-up, and set time-based wake-up conditions to automatically wake up before the scheduled reporting time to prepare data reports; For battery-powered devices, analyze the power consumption pattern of IoT devices, determine the peak and valley of power consumption, evaluate the data transmission needs of IoT devices, set conditions for entering a dormant state when the power is below a preset threshold, and set wake-up conditions based on power. Set wake-up conditions when the power returns to a preset level or a data transmission wake-up command is received. When the device is fully charged or receives a wake-up command, it resumes data transmission; When the IoT device meets the wake-up conditions, the IoT platform sends a wake-up instruction to the IoT device. After receiving the instruction, the IoT device executes the wake-up operation and resumes normal working state. The wake-up conditions are reaching the preset wake-up time, receiving the wake-up signal, or the power is restored to the preset level.

5. The multi-level communication method of the Internet of Things for city management according to claim 4, characterized in that: In step 4, the process of analyzing the device energy consumption trend and battery life status includes: After the IoT device is awakened, it establishes a communication connection with the IoT platform and starts collecting and transmitting data. The collected data is packaged and sent to the IoT platform through the communication network. The IoT device sends its current status information to the IoT platform, including operating status, power level, and fault status. The IoT platform updates the status record of the IoT device based on the received status information. Monitor the energy consumption of IoT devices in the awake state, and use the built-in sensors of IoT devices to collect energy consumption data of IoT devices, including CPU usage, network transmission power consumption, and sensor power consumption. Based on the collected energy consumption data, calculate the device energy consumption evaluation index and evaluate the energy efficiency of the device. For battery-powered IoT devices, the built-in battery management system monitors the battery status, including battery voltage, current, temperature, and power parameters, and records the battery's charge and discharge times, capacity decay rate, and power consumption rate information. Based on the battery status monitoring data and combined with the battery aging model, the battery life assessment index is calculated to analyze the battery life status.

6. The multi-level communication method of the Internet of Things for city management according to claim 5, characterized in that: The calculation expression of the equipment energy consumption evaluation index is: Among them, EI is the equipment energy consumption evaluation index, P i is the power consumption of the i-th sensor, n is the total number of sensors, E base is the baseline energy consumption value of the device, C is the CPU usage, and C base is the baseline value of CPU usage, λ is the sensitivity coefficient of CPU usage change, T is the network transmission power consumption of the device, P t is the network transmission power consumption of the sensor, P s is the average network transmission power consumption of all sensors. The value range of EI is [0, +∞), where 0 represents the lowest energy efficiency. The larger the value of EI, the higher the energy efficiency. The calculation expression of the battery life evaluation index is: Among them, BI is the battery life assessment index, R j is the battery capacity measured for the jth time, m is the number of battery measurements, E ra is the rated energy of the battery, E cu is the current energy of the battery, ∈ is a constant, N cy is the actual charge and discharge times of the battery, N cybase is the benchmark charge and discharge times determined based on the battery type and usage conditions, δ is the influence coefficient of battery temperature on life, W avg is the average operating temperature of the battery. The value range of BI is (0, +∞). A value close to 0 indicates that the battery life is about to end. The larger the value of BI, the better the battery life status.

7. The multi-level communication method of the Internet of Things for city management according to claim 6, characterized in that: In step 5, the evaluation process of the sleep-wake-up strategy effect includes: Collect historical usage data of IoT devices, including sleep time, wake-up times, wake-up duration, data transmission volume after each wake-up, device energy consumption, and collect current energy consumption data and battery status information of IoT devices; Analyze the energy consumption trend of the equipment, including the change of energy consumption over time, peak and valley, determine the energy consumption pattern of the equipment in different time periods, and analyze the life status of the battery, including the battery capacity attenuation, charge and discharge times and average operating temperature, and predict the remaining life and performance of the battery; Combine historical usage data and energy consumption trend analysis results, integrate the device energy consumption evaluation index and battery life evaluation index, calculate the sleep evaluation coefficient, compare the sleep evaluation coefficient under the current sleep and wake-up strategy with historical data, compare the performance differences of the devices under the sleep and wake-up strategy, and evaluate the actual effect of the sleep and wake-up strategy based on the changes in the sleep evaluation coefficient; According to the evaluation results, different optimization levels are preset, namely low optimization level, medium optimization level and high optimization level, and the corresponding optimization threshold is matched for each optimization level in combination with the dormancy evaluation coefficient. Each optimization level corresponds to different optimization goals and strategy adjustment directions; Adjust the sleep and wake-up strategies of IoT devices according to the evaluation results and optimization levels. After the strategies are adjusted, implement new sleep and wake-up strategies, continuously monitor the energy consumption and performance of the devices, collect feedback data, evaluate the actual effects of the new strategies, and continuously iterate and optimize the sleep and wake-up strategies based on the test results and continuously monitored data.

8. The multi-level communication method of the Internet of Things for city management according to claim 7, characterized in that: The calculation expression of the dormancy evaluation coefficient is: Among them, SAI is the dormancy assessment coefficient, EI k is the energy consumption evaluation index of the equipment measured at the kth time, BI k is the battery life evaluation index of the kth measurement, N is the number of measurements, is the adjustment factor, E base is the benchmark energy consumption value, L cu is the current estimated battery life, L in The SAI is the initial life evaluation value of the battery. The value range of SAI is (0, +∞). A value close to 0 indicates that the sleep evaluation coefficient is poor and the current sleep wake-up strategy is not effective. The larger the SAI value, the more effective the sleep wake-up strategy is.

9. The multi-level communication method of the Internet of Things for city management according to claim 8, characterized in that: The plurality of optimization levels correspond to the plurality of optimization thresholds, the optimization thresholds include an upper threshold and a lower threshold, and the correspondence between the plurality of optimization levels and the plurality of optimization thresholds is: Low optimization level 0 <SAI≤SAI A ; Medium optimization level SAI A <SAI≤SAI B ; High optimization level SAI>SAI B ; Among them, MC is the dormancy assessment coefficient, MC MP is the lower threshold corresponding to the high matching level and the upper threshold corresponding to the medium matching level, MC LP The lower threshold corresponding to the medium matching level and the upper threshold corresponding to the low matching level.

10. An Internet of Things multi-level communication system for city management, used to implement the Internet of Things multi-level communication method for city management as described in any one of claims 1 to 9, comprising an Internet of Things platform, characterized in that: The Internet of Things platform is connected in communication with a data acquisition module, a data transmission module, a data processing module, a sleep and wake-up management module, an energy consumption and performance analysis module, a strategy optimization module and a monitoring module, wherein the electrical signals between the modules are connected; The data collection module is used to collect raw data from various IoT devices in the city, including device status, environmental parameters, and usage; The data transmission module transmits the collected data to the Internet of Things platform wirelessly; The data processing module is used to process, analyze and store the collected raw data, including data cleaning, fusion and analysis; The sleep and wake-up management module controls the sleep and wake-up of the device according to the working mode and data transmission requirements of the device; The energy consumption and performance analysis module uses historical data and real-time data to analyze the energy consumption trend, battery life, and performance of IoT devices, calculate the sleep evaluation coefficient, and identify energy consumption bottlenecks and performance optimization points; The strategy optimization module presets different optimization levels and thresholds based on the analysis results, and formulates and adjusts the sleep and wake-up strategies of the IoT devices; The monitoring module deploys the optimized strategy to the IoT device and continuously monitors the operating status and performance of the device.

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