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CN-122022643-A - Dangerous waste supervision system based on Internet of things

CN122022643ACN 122022643 ACN122022643 ACN 122022643ACN-122022643-A

Abstract

The invention relates to the technical field of hazardous waste supervision, in particular to a hazardous waste supervision system based on the Internet of things, which comprises a perception layer, a network layer, a platform layer and an application layer, wherein the perception layer collects full-flow data of hazardous waste products, storages, transportation and places through a multi-dimensional sensing group, the accuracy of the data is improved by combining a dynamic threshold calibration algorithm, the network layer adopts a mixed networking of edge calculation and 5G/NB-IoT plus satellite communication, the data is transmitted in real time and stored in a non-tamperable mode by matching with block chain nodes, the platform layer integrates a digital twin engine, an intelligent path planning module and a multi-department collaborative early warning system, a full life cycle virtual simulation and risk prediction model of the hazardous waste is constructed, and the application layer provides differentiated functions for supervision departments, waste production enterprises, transportation units and disposal institutions. The invention realizes real-time, accurate, closed cyclization and intelligent monitoring of dangerous wastes, greatly improves monitoring efficiency and reduces environmental risks.

Inventors

  • MA TINGTING
  • LIU QUANZHENG
  • GAO LEI

Assignees

  • 甘肃省生态环境科学设计研究院(甘肃省生态环境规划院)

Dates

Publication Date
20260512
Application Date
20251230

Claims (10)

  1. 1. The hazardous waste supervision system based on the Internet of things is characterized by comprising a perception layer, a network layer, a platform layer and an application layer; The sensing layer comprises a multi-dimensional sensing group which is deployed at a dangerous waste production point, a storage warehouse, a transport vehicle and a disposal terminal, wherein the multi-dimensional sensing group comprises a gas sensor, a temperature and humidity sensor, a liquid level/weight sensor, a GPS/Beidou positioning module, a triaxial acceleration sensor and a sealing state sensor and is used for acquiring physical and chemical parameters, position information and state data of the full life cycle of dangerous waste, and a dynamic threshold calibration unit is arranged in the sensing layer and used for calibrating the sensing data in real time based on an LSTM algorithm; The network layer comprises edge computing nodes, a mixed communication module and a blockchain consensus node, wherein the edge computing nodes preprocess and abnormally judge the sensing data, the mixed communication module adopts a 5G, NB-IoT and satellite communication redundancy design, and the blockchain consensus node comprises a supervision department node, an enterprise node and a third party detection node to realize data uplink certification; The platform layer comprises a digital twin engine, a blockchain tracing module, an intelligent path planning module and a multi-department collaborative early warning system, wherein the digital twin engine builds a digital twin model of the full life cycle of dangerous waste, the blockchain tracing module realizes data non-tamperable tracing based on a alliance chain architecture, the intelligent path planning module is combined with a GIS map and real-time road conditions to generate an optimal transportation path, and the multi-department collaborative early warning system automatically matches with a responsibility main body and triggers hierarchical early warning; the application layer comprises a monitoring end, an enterprise end, a transportation end and an emergency end, and each terminal realizes data interaction and function call through the platform layer to form a full-flow closed-loop monitoring.
  2. 2. The hazardous waste monitoring system based on the Internet of things, which is characterized in that the calibration flow of the dynamic threshold calibration unit is that sensing data and environment interference parameters are collected, a sensing data-interference parameter mapping model is established through an LSTM algorithm, a sensor threshold interval is adjusted in real time, and abnormal interference data are removed.
  3. 3. The hazardous waste monitoring system based on the Internet of things, which is characterized in that the block chain consensus node adopts PBFT consensus mechanism, the block data comprises hazardous waste classification information, sensing acquisition data, transportation track data, disposal result data and signature information of each link responsibility main body, and the block generation interval is not more than 30 seconds.
  4. 4. The hazardous waste monitoring system based on the Internet of things, which is characterized in that the digital twin engine acquires entity scene data through three-dimensional laser scanning, a static model is built by combining a BIM technology, and the real-time access perception layer data update dynamic model is realized to realize hazardous waste stock prediction, risk point simulation and treatment process optimization.
  5. 5. The hazardous waste monitoring system based on the Internet of things of claim 1, wherein the intelligent path planning module is based on an A-algorithm, integrates hazardous waste transportation limit area, road bearing capacity and real-time traffic congestion data, dynamically adjusts a transportation path, and has a path deviation early warning response time of not more than 10 seconds.
  6. 6. The hazardous waste supervision system based on the Internet of things, which is characterized in that the multi-department collaborative early warning system is provided with a three-level early warning mechanism, the first-level early warning triggers linkage of environmental protection, emergency and public security departments, the second-level early warning is pushed to the supervision departments in jurisdictions and enterprise responsible persons, the three-level early warning only sends correction reminding to the enterprise, and early warning information contains risk positions, types and treatment suggestions.
  7. 7. The hazardous waste monitoring system based on the Internet of things of claim 1, wherein the multi-dimensional sensing group on the transport vehicle further comprises a video monitoring module and an electronic seal sensor, wherein the electronic seal sensor is linked with a transport carriage door lock, and positioning tracking and video recording are automatically triggered when the seal is abnormal.
  8. 8. The hazardous waste monitoring system based on the Internet of things, which is characterized in that the platform layer further comprises a data encryption module, the transmission data is encrypted by adopting an SM4 symmetric encryption algorithm, and node identity authentication is realized by adopting an SM2 asymmetric encryption algorithm.
  9. 9. The hazardous waste supervision system based on the Internet of things, which is characterized in that an enterprise side of the application layer supports the functions of on-line reporting, automatic generation of standing accounts and compliance self-checking of hazardous waste, and automatically associates national hazardous waste directory update classification standards.
  10. 10. The hazardous waste monitoring system based on the Internet of things, which is characterized in that the sensor of the sensing layer adopts waterproof, anti-corrosion and anti-explosion design, the protection level is not lower than IP67, and the hazardous waste monitoring system is suitable for severe environments of hazardous waste storage and transportation.

Description

Dangerous waste supervision system based on Internet of things Technical Field The invention relates to the technical field of hazardous waste supervision, in particular to a hazardous waste supervision system based on the Internet of things. Background Hazardous waste is solid waste which is listed in the national hazardous waste directory or has hazardous characteristics according to the hazardous waste identification standard and identification method specified by the country, has the characteristics of corrosiveness, toxicity, flammability, reactivity or infectivity, and can cause serious harm to the ecological environment and human health if improperly regulated. With the increasing frequency of industrial production and social activities, the production of hazardous waste continues to grow, and the complexity and urgency of the supervision work thereof are increasingly highlighted. The existing hazardous waste supervision mode mainly relies on manual declaration, periodic checking and paper account management, and has a plurality of problems which are difficult to solve. Firstly, the data acquisition and supervision have serious hysteresis, under the manual reporting mode, the information such as the generation amount, the storage state, the transportation path and the like of dangerous wastes are required to be actively reported by enterprises, and the supervision department is difficult to acquire real data in real time, so that the phenomena of ' report hiding, report missing ' and false report ' are frequently generated, and part of enterprises have the actions of reducing the cost, even illegally dumping and transferring the dangerous wastes, thereby bringing great hidden trouble to the environmental safety. Secondly, the existing internet of things supervision system mostly adopts a single sensor to collect data, and influences of factors such as temperature and humidity, electromagnetic interference, chemical corrosion and the like in dangerous waste storage and transportation environments on accuracy of the sensing data are not considered, so that the data false alarm rate is high, and supervision departments are difficult to make accurate judgment according to the data. Meanwhile, a centralized server is adopted for data storage, the risks of data tampering and loss exist, once an environmental accident occurs, responsibility tracing is difficult to realize, and responsibility main bodies of links of waste enterprises, transportation units, disposal institutions and the like cannot be clearly defined. In the aspect of transportation supervision, in the prior art, transportation track recording is realized only through GPS positioning, but intelligent path planning is not performed by combining factors such as real-time road conditions, dangerous waste transportation limiting areas (such as water source protection areas and residential areas), road bearing capacity and the like, so that transportation efficiency is low, and abnormal conditions such as path deviation, illegal stay and the like cannot be found in time. In addition, the dangerous waste transportation process lacks effective real-time monitoring means, can not early warn in time on the carriage sealing state of the transportation vehicle, the dangerous waste leakage condition and the like, and once leakage accidents occur, environmental pollution diffusion is easy to cause. In the aspect of full life cycle supervision, the existing system focuses on supervision of a single link, lacks data communication of all links of dangerous waste generation, storage, transportation and disposal, forms an 'information island', cannot comprehensively master the circulation condition of dangerous waste by a supervision department, and is difficult to realize full-flow closed-loop supervision. Meanwhile, the existing system lacks predictive supervision capability, can only perform passive processing after an accident occurs, and cannot predict risk points in advance through data analysis, such as problems of over-storage of dangerous wastes, insufficient disposal capability and the like, so that supervision work is trapped in the passive state. In the aspect of emergency response, the existing supervision system does not establish a multi-department cooperative mechanism, when emergency such as dangerous waste leakage and fire disaster occurs, a plurality of departments such as environmental protection, emergency, public security and medical treatment are manually coordinated, the response time is long, the treatment flow is complicated, the optimal treatment opportunity is easily delayed, and the accident influence range is enlarged. In addition, most of emergency treatment schemes are universal templates, personalized treatment suggestions are formulated by not combining with factors such as specific types of dangerous wastes, accident site environments and the like, so that treatment measures lack pertinence, and the treatment effect is poor.