Garbage classification monitoring method with low power consumption and wireless transmission

Abstract

The invention relates to the technical field of garbage classification monitoring, in particular to a low-power-consumption wireless transmission garbage classification monitoring method, which comprises a garbage throwing behavior sensing module, a garbage filling state detection module, a data compression and transmission module and an energy consumption management scheduling module. Garbage types are judged through a micro sensor array and a classification rule base, the filling state is obtained through ultrasonic ranging and a gas sensor, data are compressed through differential coding and Huffman coding, communication energy consumption is reduced through a self-adaptive modulation mechanism, and meanwhile power supply and task scheduling are optimized in combination with an energy recovery device. The data acquisition precision can be improved, the system energy consumption can be reduced, the transmission stability can be enhanced, and the efficient and energy-saving garbage classification monitoring requirement in smart city construction can be met.

Description

Technical Field

[0001] This invention belongs to the field of Internet of Things and environmental monitoring technology, specifically a low-power wireless transmission method for waste sorting monitoring. Background Technology

[0002] Waste sorting and intelligent monitoring technologies have developed rapidly in recent years. Low-power wireless transmission methods for waste sorting monitoring, due to their high efficiency, convenience, and environmental friendliness, have gradually become an important research direction in smart city construction and environmental governance. However, existing waste sorting monitoring technologies have shortcomings in data acquisition accuracy, transmission energy consumption, and system integration, which affect their practical application effectiveness.

[0003] A search revealed a patent, CN111994513B, which discloses a method and device for real-time monitoring of waste types in intelligent sorting trash cans, published on March 21, 2023. This patent identifies the identity information of the waste disposal personnel, the three-dimensional depth information of the waste in the trash can, and the three-dimensional capacity information of the trash can. Based on the labeled data, it establishes a training set and a test set for a deep learning model, thereby achieving real-time inference of waste types. However, this technical solution relies on a highly complex deep learning model, requiring significant hardware computing power and data storage. Furthermore, it does not explicitly mention the specific implementation method for low-power wireless transmission, which may result in high overall system energy consumption, posing a challenge for long-term operation.

[0004] A search revealed a patent for an intelligent sanitation management method for urban environments, publication number CN117522388B, published on April 12, 2024. This patent monitors the filling level and gas parameters of waste sorting bins using a sensor network and combines real-time data analysis to generate optimal waste collection routes and schedules. However, while this technical solution emphasizes intelligent data acquisition and analysis, it does not adequately consider energy consumption optimization during wireless transmission, potentially leading to high energy costs during large-scale deployment. Furthermore, the coverage and data transmission stability of its sensor network may be limited by wireless communication technology.

[0005] The aforementioned problems indicate that existing waste sorting monitoring technologies still have certain limitations in terms of low-power wireless transmission, system energy consumption optimization, and data transmission stability. Therefore, this invention proposes a low-power wireless transmission method for waste sorting monitoring, aiming to meet the demand for efficient and energy-saving waste sorting monitoring methods in smart city construction by optimizing the wireless transmission protocol, reducing system energy consumption, and improving the stability and efficiency of data transmission. Summary of the Invention

[0006] This invention provides a low-power wireless transmission method for waste sorting monitoring, which features optimized data acquisition accuracy, reduced system energy consumption, and improved data transmission stability.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a low-power wireless transmission method for monitoring waste sorting, comprising a waste disposal behavior sensing module, a waste filling status detection module, a data compression and transmission module, and an energy consumption management and scheduling module.

[0008] The waste disposal behavior sensing module includes a motion recognition unit and a category determination unit. The motion recognition unit captures the movement trajectory of waste during disposal using a micro-motion sensor array mounted on top of the waste bin, and converts the captured trajectory information into a time-series signal. The category determination unit makes a preliminary determination of the waste type based on the time-series signal and a pre-set classification rule library, while simultaneously recording the timestamp information of the waste disposal. The waste disposal behavior sensing module sends the generated waste type information and timestamp information to the data compression and transmission module.

[0009] The waste filling status detection module includes a volume measurement unit and a gas concentration detection unit. The volume measurement unit uses ultrasonic ranging technology to acquire the real-time height of waste accumulation inside the waste bin and converts this height into a filling percentage. The gas concentration detection unit collects volatile organic compound (VOC) concentration distribution data through a multi-point gas sensor array arranged on the inner wall of the waste bin. The waste filling status detection module sends the filling percentage and gas concentration distribution data to the data compression and transmission module.

[0010] The data compression and transmission module includes a data encoding unit and a wireless communication unit. The data encoding unit performs layered encoding on the received waste type information, timestamp information, fill rate percentage, and gas concentration distribution data. First, it uses a differential coding algorithm to compress the continuous time series data, and then uses Huffman coding to perform a second compression on the discontinuous data. The wireless communication unit designs an adaptive modulation mechanism based on a low-power wide-area network protocol, dynamically selecting the modulation method according to the current network load and channel quality, reducing wireless communication power consumption while ensuring data transmission stability. The data compression and transmission module sends the compressed data packets to the energy management and scheduling module.

[0011] The energy management and scheduling module includes a power management unit and a task scheduling unit. The power management unit supplies power to the entire system through a built-in energy storage module and an energy recovery device. The energy recovery device uses piezoelectric materials to convert the mechanical vibrations generated during waste disposal into electrical energy, which is then stored in the energy storage module. The task scheduling unit analyzes the current system operating status based on the content of received data packets and prioritizes the allocation of computing and communication resources to high-priority tasks. For example, when the filling rate reaches a preset threshold or the gas concentration abnormally increases, a waste collection request is triggered first, and relevant personnel are notified.

[0012] The action recognition unit of the waste disposal behavior perception module captures the movement trajectory of waste during disposal through a micro-motion sensor array. The category determination unit combines time-series signals and a classification rule base to determine the type of waste, generating waste type information and timestamp information before sending it to the data compression and transmission module. The capacity measurement unit of the waste filling status detection module uses ultrasonic ranging technology to obtain the waste accumulation height and convert it into a filling rate percentage. The gas concentration detection unit collects gas concentration distribution data through a multi-point gas sensor array and sends this data to the data compression and transmission module. The data encoding unit of the data compression and transmission module uses differential coding and Huffman coding to perform layered compression of the data. The wireless communication unit dynamically selects the modulation method based on an adaptive modulation mechanism to reduce wireless communication power consumption and sends the compressed data packets to the energy management and scheduling module. The power management unit of the energy management and scheduling module supplies power to the system through an energy storage module and an energy recovery device. The task scheduling unit analyzes the system operating status based on the data packet content and prioritizes resource allocation to high-priority tasks, such as triggering waste collection requests and notifying staff.

[0013] The waste disposal behavior sensing module captures the movement trajectory of waste during disposal and determines the waste type by combining it with a classification rule base. The waste filling status detection module uses ultrasonic ranging technology and a multi-point gas sensor array to acquire data on waste accumulation height and gas concentration distribution. The data compression and transmission module uses differential coding and Huffman coding to perform layered compression of data and reduces wireless communication energy consumption through an adaptive modulation mechanism. The energy management and scheduling module supplies power to the system through an energy storage module and an energy recovery device, and analyzes the system's operating status based on data packet content to prioritize resource allocation to high-priority tasks, forming a complete low-power wireless transmission waste classification monitoring method. This method addresses the shortcomings of existing technologies in data acquisition accuracy, transmission energy consumption, and system integration by optimizing specific technical means in data acquisition, transmission, and energy management, thus meeting the demand for efficient and energy-saving waste classification monitoring methods in smart city construction. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the system module structure of the present invention;

[0015] Figure 2 A flowchart of the waste disposal behavior sensing module;

[0016] Figure 3 This is a functional block diagram of the energy consumption management and scheduling module.

[0017] The attached figures are labeled as follows:

[0018] 1. Waste disposal behavior sensing module; 2. Waste filling status detection module; 3. Data compression and transmission module; 4. Energy consumption management and scheduling module; 5. Action recognition unit; 6. Category determination unit; 7. Capacity measurement unit; 8. Gas concentration detection unit; 9. Data encoding unit; 10. Wireless communication unit; 11. Power management unit; 12. Task scheduling unit. Detailed Implementation

[0019] This invention relates to a low-power wireless transmission method for monitoring waste sorting, the specific implementation of which is combined with... Figures 1 to 3 The accompanying diagrams and reference numerals provide detailed explanations. The waste disposal behavior sensing module 1, waste filling status detection module 2, data compression and transmission module 3, and energy consumption management and scheduling module 4 together constitute the core of the entire system. The modules interact with each other through data flow and control signals.

[0020] The waste disposal behavior sensing module 1 includes an action recognition unit 5 and a category determination unit 6. The action recognition unit 5 consists of a micro-motion sensor array mounted on the inner surface of the top of the waste bin. The sensors are positioned to ensure comprehensive coverage of the action range during waste disposal. The micro-motion sensor array is made of highly sensitive piezoelectric material. When waste is thrown into the bin, the sensor array captures the minute vibration signals generated during the waste's descent and converts these signals into time-series data. The category determination unit 6 receives the time-series signal generated by the action recognition unit 5 and, in conjunction with a pre-set classification rule library, makes a preliminary determination of the waste type. The classification rule library stores the time-series characteristics of various waste disposal patterns, such as the differences in movement trajectories generated by waste of different weights, shapes, or materials during disposal. The category determination unit 6 determines the waste type and records the disposal timestamp information by comparing the time-series signal with the feature patterns in the rule library. The waste type information and timestamp information are then sent to the data compression and transmission module 3 via a data interface.

[0021] The waste filling status detection module 2 includes a volume measurement unit 7 and a gas concentration detection unit 8. The volume measurement unit 7 uses ultrasonic ranging technology to obtain the real-time height of the waste pile inside the bin. An ultrasonic transmitter and receiver are respectively installed at the top center of the inner wall of the bin. The ultrasonic signal emitted by the transmitter is reflected off the waste surface and captured by the receiver. The waste pile height is calculated by calculating the round-trip time. The volume measurement unit 7 converts the pile height value into a filling percentage and sends this data to the data compression and transmission module 3. The gas concentration detection unit 8 consists of a multi-point gas sensor array. These sensors are evenly distributed at different heights on the inner wall of the bin to ensure comprehensive monitoring of the gas concentration distribution inside the bin. The gas sensor array collects volatile organic compound (VOC) concentration data and sends the concentration distribution information to the data compression and transmission module 3.

[0022] The data compression and transmission module 3 includes a data encoding unit 9 and a wireless communication unit 10. The data encoding unit 9 performs layered encoding processing on the received waste type information, timestamp information, fill rate percentage, and gas concentration distribution data. For continuous time series data, the data encoding unit 9 uses a differential coding algorithm for initial compression, which reduces redundant information by calculating the difference between adjacent data points. For non-continuous data, the data encoding unit 9 further utilizes Huffman coding for secondary compression, thereby minimizing the data volume. The wireless communication unit 10 designs an adaptive modulation mechanism based on a low-power wide-area network protocol, dynamically selecting the modulation method according to the current network load and channel quality. When the network load is low and the channel quality is good, the wireless communication unit 10 selects a higher-order modulation method to improve the data transmission rate; when the network load is high or the channel quality is poor, the wireless communication unit 10 switches to a lower-order modulation method to ensure data transmission stability. The compressed and modulated data packets are finally sent to the energy management and scheduling module 4.

[0023] The energy management and scheduling module 4 includes a power management unit 11 and a task scheduling unit 12. The power management unit 11 supplies power to the entire system through a built-in energy storage module and energy recovery device. The energy storage module uses a high-capacity lithium-ion battery, capable of meeting the system's long-term operating requirements. The energy recovery device, made of piezoelectric material, is installed on the bottom and inner side walls of the trash can. Mechanical vibrations generated during trash disposal are converted into electrical energy by the piezoelectric material and stored in the energy storage module. The task scheduling unit 12 receives data packets from the data compression and transmission module 3 and analyzes the current system operating status based on the packet content. When the filling rate reaches a preset threshold or the gas concentration abnormally increases, the task scheduling unit 12 prioritizes allocating computing and communication resources to high-priority tasks, such as triggering a trash collection request and notifying relevant personnel via the wireless communication unit 10.

[0024] The action recognition unit 5 of the waste disposal behavior perception module 1 captures the movement trajectory of waste during disposal through a micro-motion sensor array. The category determination unit 6 combines time series signals and a classification rule base to determine the type of waste, generating waste type information and timestamp information before sending it to the data compression and transmission module 3. The capacity measurement unit 7 of the waste filling status detection module 2 uses ultrasonic ranging technology to obtain the height of waste accumulation and convert it into a filling rate percentage. The gas concentration detection unit 8 collects gas concentration distribution data through a multi-point gas sensor array and sends this data to the data compression and transmission module 3. The data encoding unit 9 of the data compression and transmission module 3 uses differential coding and Huffman coding to perform layered compression of the data. The wireless communication unit 10 dynamically selects the modulation method based on an adaptive modulation mechanism to reduce wireless communication power consumption and sends the compressed data packet to the energy consumption management and scheduling module 4. The power management unit 11 of the energy consumption management and scheduling module 4 supplies power to the system through an energy storage module and an energy recovery device. The task scheduling unit 12 analyzes the system operating status based on the data packet content and prioritizes the allocation of resources to high-priority tasks, such as triggering waste collection requests and notifying staff.

[0025] The positional and connection relationships of the modules in the above embodiments are as follows: The waste disposal behavior sensing module 1 and the waste filling status detection module 2 are respectively installed on the top and inner wall of the waste bin, and their output ends are connected to the input end of the data compression and transmission module 3 via data cables. The output end of the data compression and transmission module 3 is connected to the input end of the energy management and scheduling module 4 via a wireless communication link. The power management unit 11 of the energy management and scheduling module 4 is connected to the energy storage module and the energy recovery device via wires, and the task scheduling unit 12 is connected to the wireless communication unit 10 via control signal lines to realize resource allocation and task scheduling functions.

[0026] In practical applications, this invention can be applied to waste sorting management systems in smart cities. For example, multiple smart trash cans equipped with this invention can be deployed in residential communities or public places. Each trash can uploads compressed data packets to a cloud server via a wireless communication unit 10. The cloud server further analyzes and processes the data, generating waste disposal statistics reports and collection suggestions. When the filling rate of a trash can reaches 80% or the gas concentration exceeds a safety threshold, the system automatically sends a collection request to the sanitation department and notifies relevant personnel to handle the situation promptly via mobile terminals. In this way, this invention not only achieves accurate monitoring of waste sorting but also significantly reduces system energy consumption, meeting the demand for efficient and energy-saving waste sorting monitoring methods in smart city construction.

[0027] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principle of this invention is further explained below in conjunction with a specific application scenario.

[0028] In the waste sorting management system of a smart city, multiple smart trash cans equipped with this invention are deployed. Each trash can uploads compressed data packets to a cloud server via a wireless communication unit 10. The cloud server analyzes and processes the data, generating waste disposal statistics reports and collection suggestions. The following are the specific application scenarios, steps, and implementation principles.

[0029] First, when a resident or user disposes of trash into the smart trash can, the motion recognition unit 5 of the trash disposal behavior sensing module 1 captures the vibration signals generated during the trash's descent using a micro-motion sensor array. These micro-motion sensor arrays, made of highly sensitive piezoelectric material, accurately record the trajectory of the trash during disposal and convert it into time-series data. Subsequently, the classification determination unit 6 receives these time-series signals and compares them with feature patterns in a classification rule base. The classification rule base stores time-series features of various trash disposal patterns, such as the trajectory differences generated by trash of different weights, shapes, or materials during disposal. By comparing the time-series signals with the feature patterns in the rule base, the classification determination unit 6 ultimately determines the type of trash and records the disposal timestamp information. This information is then sent to the data compression and transmission module 3 via a data interface.

[0030] Meanwhile, the capacity measurement unit 7 of the waste filling status detection module 2 uses ultrasonic ranging technology to obtain the real-time height of the waste pile inside the waste bin. An ultrasonic transmitter and receiver are respectively installed at the top center of the inner wall of the waste bin. The ultrasonic signal emitted by the transmitter is captured by the receiver after being reflected from the waste surface. By calculating the round-trip time, the capacity measurement unit 7 determines the waste pile height and converts it into a filling percentage. The gas concentration detection unit 8 collects volatile organic compound (VOC) concentration distribution data through a multi-point gas sensor array. These sensors are evenly distributed at different heights on the inner wall of the waste bin to ensure comprehensive monitoring of the gas concentration distribution inside the bin. The capacity measurement unit 7 and the gas concentration detection unit 8 send the filling percentage and gas concentration distribution data to the data compression and transmission module 3, respectively.

[0031] The data encoding unit 9 of the data compression and transmission module 3 performs layered encoding processing on the received waste type information, timestamp information, filling rate percentage, and gas concentration distribution data. For continuous time series data, the data encoding unit 9 uses a differential coding algorithm for initial compression, which reduces redundant information by calculating the difference between adjacent data points. For non-continuous data, the data encoding unit 9 further uses Huffman coding for secondary compression, thereby minimizing the data volume. The compressed data then enters the wireless communication unit 10. The wireless communication unit 10 designs an adaptive modulation mechanism based on a low-power wide-area network protocol, dynamically selecting the modulation method according to the current network load and channel quality. When the network load is low and the channel quality is good, the wireless communication unit 10 selects a high-order modulation method to improve the data transmission rate; when the network load is high or the channel quality is poor, the wireless communication unit 10 switches to a low-order modulation method to ensure data transmission stability. The compressed and modulated data packets are finally sent to the energy management and scheduling module 4.

[0032] The power management unit 11 of the energy management and scheduling module 4 supplies power to the entire system through a built-in energy storage module and energy recovery device. The energy storage module uses a high-capacity lithium-ion battery, which can meet the needs of the system for long-term operation. The energy recovery device is made of piezoelectric material and is installed on the bottom and inner side walls of the trash can. When trash is disposed of, the mechanical vibration generated is converted into electrical energy by the piezoelectric material and stored in the energy storage module. The task scheduling unit 12 receives data packets from the data compression and transmission module 3 and analyzes the current operating status of the system based on the content of the data packets. When the filling rate reaches 80% or the gas concentration exceeds the safety threshold, the task scheduling unit 12 prioritizes the allocation of computing and communication resources to high-priority tasks, such as triggering a trash collection request and notifying relevant personnel through the wireless communication unit 10.

[0033] Through the above steps, this invention achieves precise monitoring of waste sorting. For example, when the filling rate of a waste bin reaches 80%, the system automatically sends a collection request to the sanitation department and notifies relevant personnel via mobile terminal to handle the situation promptly. Furthermore, when the gas concentration abnormally increases, the system also triggers an alarm mechanism to remind staff to take appropriate measures. In this way, this invention not only improves the accuracy and efficiency of waste sorting monitoring but also significantly reduces system energy consumption, meeting the demand for efficient and energy-saving waste sorting monitoring methods in smart city construction.

[0034] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A low-power wireless transmission method for monitoring waste sorting, characterized in that: The system includes a waste disposal behavior perception module (1), a waste filling status detection module (2), a data compression and transmission module (3), and an energy management and scheduling module (4). The waste disposal behavior perception module (1) includes an action recognition unit (5) and a category determination unit (6). The action recognition unit (5) captures the movement trajectory of waste disposal through a micro-motion sensor array and converts the trajectory information into a time series signal. The category determination unit (6) generates waste type information and timestamp information based on the time series signal and a classification rule base, and sends the waste type information and timestamp information to the data compression and transmission module (3). The waste filling status detection module (2) includes a capacity measurement unit (7) and a gas concentration detection unit (8). The capacity measurement unit (7) uses ultrasonic ranging technology to obtain the height of waste accumulation inside the waste bin and converts it into a filling rate percentage. The gas concentration detection unit (8) collects volatile organic compound concentration distribution data through a multi-point gas sensor array and sends the filling rate percentage and gas concentration distribution data to the data compression and transmission module (3). The data compression and transmission module (3) includes a data encoding unit (9) and a wireless communication unit (10). The data encoding unit (9) performs layered encoding processing on the received garbage type information, timestamp information, filling rate percentage and gas concentration distribution data. It uses differential encoding algorithm to perform initial compression on continuous time series data and Huffman coding to perform secondary compression on non-continuous data. The wireless communication unit (10) designs an adaptive modulation mechanism based on low power wide area network protocol, dynamically selects the modulation mode according to network load and channel quality, and sends the compressed data packet to the energy consumption management and scheduling module (4). The energy consumption management and scheduling module (4) includes a power management unit (11) and a task scheduling unit (12). The power management unit (11) supplies power to the system through an energy storage module and an energy recovery device. The energy recovery device uses piezoelectric material to convert the mechanical vibration generated when garbage is disposed of into electrical energy and stores it in the energy storage module. The task scheduling unit (12) analyzes the system operating status according to the content of the received data packet and prioritizes the allocation of computing resources and communication resources to high-priority tasks.

2. The method according to claim 1, characterized in that: The micro-motion sensor array of the motion recognition unit (5) is made of high-sensitivity piezoelectric material and is installed on the inner surface of the top of the trash can to cover the range of motion when the trash is disposed of, and converts the vibration signal generated during the fall of the trash into time series data.

3. The method according to claim 1, characterized in that: The classification rule base of the category determination unit (6) stores the time series features of various waste disposal patterns. The category determination unit (6) determines the waste type by comparing the time series signal with the feature patterns in the rule base.

4. The method according to claim 1, characterized in that: The ultrasonic transmitter and receiver of the capacity measurement unit (7) are installed at the center of the top of the inner wall of the trash can. The height of the trash pile is obtained by calculating the round-trip time of the ultrasonic signal and converted into a percentage of the filling rate.

5. The method according to claim 1, characterized in that: The gas concentration detection unit (8) has a multi-point gas sensor array that is evenly distributed at different heights on the inner wall of the trash can to collect data on the concentration distribution of volatile organic compounds.

6. The method according to claim 1, characterized in that: The adaptive modulation mechanism of the wireless communication unit (10) selects a high-order modulation mode when the current network load is low and the channel quality is good, and switches to a low-order modulation mode when the current network load is high or the channel quality is poor.

7. The method according to claim 1, characterized in that: When the filling rate reaches a preset threshold or the gas concentration rises abnormally, the task scheduling unit (12) will trigger a garbage collection request and notify relevant staff through the wireless communication unit (10).

8. The method according to claim 1, characterized in that: The energy recovery device of the power management unit (11) is installed on the bottom and inner side wall of the trash can. It converts the mechanical vibration generated when the trash is disposed of into electrical energy through piezoelectric material and stores it in the electrical energy storage module.

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