Intelligent Supervision System Research Articles

Research on Intelligent Supervision System and Terminal for Small Sluice Group

As a conventional water conservancy project, small water gates play a crucial role in flood prevention and drainage, water storage and irrigation. In response to the problems of a large number, wide distribution, and difficult management of small water gates, this article proposes an intelligent supervision system for small water gate groups based on the three-level architecture of provinces, cities, and counties. Then, according to the requirements of small water gate supervision, the hardware circuit and software program of the monitoring terminal were specially designed. The main content of this article includes three aspects: the provincial, city, and county level design of regulatory platforms, the modular and hierarchical structure design of terminal hardware, and the standardization and standardization design of terminal software. It provides a solution for the intelligent, efficient, and standardized management of small water gate groups, as well as a low-cost, reliable, and versatile monitoring terminal for the implementation of the solution. It has positive significance in solving the management difficulties of small water gates.

Retracted: Application of Moving Target Information Perception Technology in Intelligent Supervision System.

[This retracts the article DOI: 10.1155/2022/5192601.].

Research on Intelligent Supervision System of Ore Pass

To prevent safety accidents caused by mining vehicles and personnel entering the operation area by mistakes, it is necessary to reduce the risk of the ore pass. However, the underground space of the mine is narrow, and factors such as dust and noise during the unloading process endanger the health of the personnel on duty in the ore pass. As such, the target detection technology based on deep learning is introduced into the underground monitoring system. The underground surveillance video samples are collected to establish a dataset for Yolov3 algorithm to identify minecarts. Through optimizing the Yolov3 model training process and algorithm, and using the dual-camera collaborative discrimination method, the influence of brightness on the recognition results when the loaders or trucks lights are turned on can be overcome. Four types of minecarts can be accurately identified from the underground surveillance video. On the basis of mining car recognition, an intelligent access control system for mine shafts based on Jetson Nano’s embedded development is developed. The on-site operation results show that the average accuracy of target vehicle recognition is within the range of 95%-100%. The system continuously recognizes the mine car 5 times from the detection program and sends the opening and closing command to complete a 90 ° rotation, which takes only 3 seconds，effectively meeting the needs of the mine for ore pass control.

Construction of an Intelligent Supervision System for Internal Audit of State owned Enterprises in Beijing

Construction of an Intelligent Supervision System for Internal Audit of State owned Enterprises in Beijing

Application of Moving Target Information Perception Technology in Intelligent Supervision System.

In order to solve the problems of inaccurate information collection, incomplete information collection, and inconsistency of collected images in traditional sports injury collection methods, an application method of moving target information perception technology in intelligent supervision system is proposed. By judging and analyzing the potential motion damage posture of the motion posture intelligent tracking images, the collected motion intelligence tracking images are judged. The intelligent tracking image matrix can make up for the shortcomings of traditional images that are not connected, complete the identification, detect potential damage in time, and take targeted preventive measures and means. Finally, according to the target detection algorithm and target tracking algorithm, combined with OpenCV computer vision library and QT image library, an intelligent video surveillance target tracking simulation system is developed. The algorithm studied in this paper is to realize the target tracking function of the intelligent video surveillance system. Through the comparison of experimental results, the design method can accurately collect damage attitude information, without calculating continuous values, and the use of three-dimensional images in the positioning process can analyze the damage attitude from multiple angles.

Administrative Punishment Supervision System Based on Internet of Things Driven by Big Data

In order to study the administrative punishment supervision system based on the Internet of things driven by big data, firstly, based on the full collection of materials, this paper makes a detailed induction and analysis from the perspective of demonstration, and discusses the problems existing in the practice of administrative punishment. In terms of theory, first determine the concept of administrative punishment from the overall direction, and then locate it to administrative punishment. Then, it analyzes the specific contents of the construction of the supervision system based on the Internet of things driven by big data and the key technologies of the cloud platform system of the Internet of things. Finally, focusing on the judgment cases published by the municipal and county courts in a province from 2014 to 2017, the analysis results are displayed, discussed, and summarized. The results show that the construction of intelligent supervision system is realized, the intelligent response to supervision needs is completed, and the scientific and effective supervision is promoted.

Design of intelligent supervision system for metrology center based on UWB technology

With the comprehensive construction of the provincial metrology center, further digital management requirements are put forward for the daily operation and maintenance inspection work of the automated verification/testing area, the warehouse storage area, the material supporting turnover area and the temporary storage area, and the professional laboratory area. The article explains the UWB (ultra-wide band) technology and its principles and applies it to the smart supervision of the production area. It has developed functions such as basic information management, job attendance, positioning analysis, electronic fence, behavior monitoring, intelligent inspection and data analysis. The digital supervision plan has been verified in the actual production environment.

Study on the Deep Learning with Image Recognition to Plant Classification

Because of long cultivation period, the three main issues of the medicinal mushroom Cordyceps militaris need to be solved urgently including high manpower, unstable quantity and quality, high electric power consumption. This article proposes the intelligent technologies of (Artificial intelligence), and Big data analytics in the application to the cultivation of Cordyceps militaris, AI which cost-effectively solve the problems of labor storage, issues of quantity and quality, and energy consumption in the agriculture filed. In this study, the intelligent system for environmental monitoring and management is developed by optimizing light, temperature and humidity of the culture environment of C. militaris regarding of the bio-active ingredients. The new strains with the high bioactive ingredients will be developed with the enhancement of the elicitors and environmental stress in the augmented intelligent supervision system. Furthermore, the combined bio-active ingredients will be developed for new medicines.

Feature Selection and Evolutionary Rule Learning for Big Data in Smart Building Energy Management

Since buildings are one of the largest sources of energy consumption in most cities of the world, energy management is one of the major concerns in their design. To ameliorate this problem, buildings are becoming smarter by the incorporation of intelligent supervision and control systems. Data captured by the sensors can be interpreted and processed by rule-based computation methods of biological inspiration (such as genetic fuzzy systems, GFS) for predicting the future behavior of the building in a knowledge-based interpretable human-like manner. GFS are computational models inspired in human cognition which use evolutionary computation (inspired in the natural evolution) to automatically learn fuzzy rules which contain explicit imprecise knowledge about a system or process. This knowledge, represented using fuzzy rules that involve fuzzy linguistic variables and values, is used to perform approximate reasoning on the input values for obtaining inferred values for the output variables. In energy management of buildings, these rules allow a smart control of the system actuators to reduce the building average energy consumption. However, the large amount of data produced on a per second basis complicates the generation of accurate and interpretable models by means of traditional methods. In this paper, we present an evolutionary computation-based approach, namely a genetic fuzzy system, to build scalable and interpretable knowledge bases for predicting energy consumption in smart buildings. For accomplishing this task, we propose a cognitive computation system for multi-step prediction based on S-FRULER, a state-of-the-art scalable distributed GFS, coupled with a feature subset selection method to automatically select the most relevant features for different time steps. S-FRULER is able to learn a fuzzy rule-based system made up of Takagi-Sugeno-Kang (TSK) rules that are able to predict the output values using both linguistic imprecise knowledge (represented by fuzzy sets) and fuzzy inference. Experiments with real data on two different problems related with the energy management revealed an average improvement of 6% on accuracy with respect to S-FRULER without feature selection, and with knowledge bases with a lower number of variables.

Research on Intelligent Supervision Method and System Developing of Soil Remediation Project Based on 3D Mobile GIS

At present, some problems such as inconvenient manual supervision, lack of real-time online supervision and poor online interaction during the implementation of soil remediation project. In order to solve the problems, the supervision method and system development of soil remediation project are studied based on sensing online and 3D mobile GIS technologies. The remediation environment are monitored with fixed sensors online and the heavy metal content are sampled with the mobile sensors. The status of soil remediation site is supervised in real time with video online. All the real-time sensing data are integrated and stored in the comprehensive database. The information of soil pollution and remediation environment is visualized with maps and charts in 3D geographic scenes in the system. In addition, the pollution degree evaluation and remediation effect analysis functions are implemented in system. It is proved with the project practice that the method and system are convenient for managers to monitor the environment on-site and supervise the status of soil remediation site in real time. The informationization and intelligence level of soil remediation project can be effectively improved.

采砂智能监管系统研究与应用

采砂智能监管系统研究与应用

An intelligent supervision system for open loop controlled processes

On-line manufacturing systems for continuous production are traditionally checked by constant time-based inspection and statistical process control processes. In the monitoring operation of large scale process plants, it is important to detect and locate process variables as they can significantly modify the operation and quality of the products involved. The present paper explores an alternative for monitoring these systems that uses the open loop control paradigm. The proposed method is defined and presented as an application for one particular industrial process--rubber die extrusion. The advantages of this method for this particular application, including its implementation throughout a multi-agent system, compatible with the HoloMAS paradigm for managing, modeling and supporting complex systems, are also discussed.

Design of Intelligent Supervision System for Production Safety in Mine Areas

Based on investigation into available monitoring and control system technology at home and abroad, this paper presents extensive surveys and thorough analysis of the safety supervision system being employed in Chinese coal mines. Taking a mine area as example and according to years of working experience in technical management of coal mines, the author combines the status quo of the mine area and existing problems in the supervision system for production safety in Chinese coal mines, and provides a design proposal of supervision system for production safety in coal mines, where a digitalized supervision system for production safety in coal mines serving dual-function of supervising production safety and commanding accident rescue is designed.

Event-based process monitoring

This article presents an efficient Intelligent Supervision System (ISS) architecture for the monitoring of a plant. The ISS detects relevant events which are later used to identify the state of the plant. The ISS layered structure implements the sliding window paradigm to detect significative events from measured signals. This methodology allows for the design of flexible ISS interfaces, that can be easily configured to detect the desired events. The behavioral model of the plant is described by an automaton, which matches event sequences to the state of the plant. Expert knowledge is used in the design of the whole ISS architecture. The ISS has been implemented in Simulink, and applied to a biotechnological process.

Fuzzy Expert System for Supervision in Adaptive Control

As several problems arise at the application of adaptive controllers to real industrial processes, for a successful implementation the standard control algorithms have to be combined with heuristically derived safety jackets. These safety nets are often realized in expert systems. This paper presents such an intelligent supervision system, where the heuristic knowledge is represented by fuzzy rules. The fuzzy system designed for adaptive control of a simulated fermenter supervises the semi-continuous identification and the controller tuning procedure. Simulation results show that the application of the proposed algorithm results in a robust and good control performance.

Knowledge-based system for telecontrol of anaerobic wastewater treatment plants

This paper describes the design and implementation of an intelligent real-time supervision system for the monitoring and control of wastewater treatment plants. The system presents a hybrid structure which integrates knowledge engineering techniques and methodologies (an expert system based on production rules embodying non-mathematical or semiquantitative knowledge of unit operation) and algorithmic process-related methods (data acquisition, signal preprocessing, calculation of plant operation parameters etc.). The fundamental design aspects consist of temporal information treatment, artifact detection and a client- server structure which allows the telesupervision of various plants by a central system.

An intelligent supervisory system for ion implantation in IC fabrication processes

This paper presents a real-time intelligent supervision system for IC ion implantation processes. A hardware interface is developed, to extract the features directly from the 2-D analog image signals of a beam map. A qualitative model for the beam scanning is then obtained, and the symptoms of abnormal operations can be analyzed to achieve on-line diagnosis. Furthermore, a fuzzy expert system is developed to advise operators on making appropriate adjustments for the beam scanning. This supervisory system has been implemented on Eaton NV-6200 A/AV ion implanters at the Taiwan Semiconductor Manufacturing Company.

An Intelligent Supervision System for the Ion Implementation in IC Fabrication Processes

This paper presents a real-time intelligent supervision system for IC ion implantation processes. A hardware interface is developed to directly extract the features from the 2-D analog image signals of a beam map. A qualitative model for the beam scanning is then obtained and the symptoms of abnormal operations can be analyzed to achieve on-line diagnosis. Furthermore, a fuzzy expert system is developed to advise operators taking appropriate adjustment for the beam scanning. This supervisory system has been implemented on Eaton NV-6200 A/AV ion implanters at the Taiwan Semiconductor Manufacturing Company.