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Design of Temperature monitoring System Using distributed intelligent CAN Bus Networks 8th

Design of Temperature Monitoring System Using Distributed In...

引用

8th international conference on Artificial Intelligence and Security (ICAIS)

作者： Su, Yu Hou, Lingjuan Li, Sinan Jiang, Zhaochang China Elect Technol Grp Corp Res Inst 54 Shijiazhuang 050081 Hebei Peoples R China Tianjin Normal Univ Sch Management Tianjin 300387 Peoples R China Sehan Univ Grad Sch Mokpo 58613 South Korea

ISBN: (纸本)9783031067945;9783031067938

Temperature sensing and control remain challenges since temperature is a critical index of the increasingly growing in agriculture and smart planting. CAN (controller Area Network) bus, due to its high stability, anti-interference ability, timeliness, adaptability to complex industrial environment, good performance, it has been widely used industrial communication among networked instrument. In this project a STC89C52 microcontroller is selected as the master chip, using as an independent CAN controller SJA1000, PCA82C250 as the CAN bus driver to achieve CAN bus communication, designed and implemented based on CAN bus network multi-node temperature monitoring system, including the master node controller, from the node controller and PC server-side procedures. The system in real time from a node can collect temperature sensor DS18B20 temperature signal transmitted via the CAN controller SJA1000 CAN controller to the receiver, and then before sending the master node, the master node receives the signal can be displayed on the LCD screen, you can also via RS-232 bus serial transmission to the host computer program computer display, the other computer can also send commands through the host computer to control the master/slave node, enabling on-line monitoring distributed CAN bus network in site-specific farming.

关键词： controller Area Network bus (CAN-bus) Temperature sensor Temperature measurement and conditioning Fieldbus Embedded systems (ES)

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Low power consumption agricultural greenhouse environmental monitoring system design and Implementation 7

Low power consumption agricultural greenhouse environmental ...

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2022 7th international conference on Information Science, computer Technology and Transportation, ISCTT 2022

作者： Zhou, Juncheng Liu, Yu Bian, Hanlin Sun, Jinkai School of Computer Engineering Jinling Institute of Technology Nanjing211169 China

ISBN: (纸本)9783800760565

To ensure the quality of agricultural products, it is essential to monitor crops during planting and growth. In this paper, we develop a Low power consumption agricultural greenhouse environment monitoring system to obtain accurate, real-time, and efficient information on crop growth. With STM32F407, ARM Cortex-M as the core of the acquisition and control unit, the system collects and monitors the temperature, humidity, atmospheric pressure, light intensity and harmful gas index in the growing environment of crops in real-time. The sensor data is transmitted to the server by Narrowband-Internet of Things (NB-IoT) communication technology. We also built a website on the server side to display the corresponding data and control the thresholds remotely. In summary, A real-time crop information monitoring system with long-distance, low power consumption, intellectualization, multi-dimension, and multi-scale is implemented. Users can monitor and control the environment of crops more intuitively by viewing the web interface's text, curve, and picture information. The results show that the system can significantly reduce maintenance costs and simplify operations. The use of this system can effectively improve the economic benefits. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Crops

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Vehicle Classification in intelligent Transportation Systems Using Deep Learning and Seismic Data 20

Vehicle Classification in Intelligent Transportation Systems...

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20th IEEE international conference on Intelligence and Security Informatics, ISI 2023

作者： Hashima, Sherief Saad, Mohamed H. Hatano, Kohei Rizk, Hamada Computational Learning Theory Team RIKEN-AIP Fukuoka819-0395 Japan Egyptian Atomic Energy Authority Engineering Dept Cairo13759 Egypt Egyptian Atomic Energy Authority Ncrrt Radiation Engineering Dept Cairo Egypt Kyushu University Department of Informatics Fukuoka819-0395 Japan Graduate School of Information Science and Technology Osaka University Suita565-0871 Japan Tanta University Computer and Control Engineering Department Tanta31733 Egypt

ISBN: (纸本)9798350337730

intelligent transportation systems have become increasingly important for efficient traffic management and road safety. Vehicle classification is a fundamental task in these systems, enabling various applications such as traffic monitoring, congestion management, and accident prevention. Traditional methods for vehicle classification heavily rely on visual or sensor-based data, such as images or radar signals. However, these methods may encounter limitations in adverse weather conditions, poor lighting, or occlusion scenarios. To address these limitations, this paper introduces a novel approach for vehicle classification using seismic data, which captures the vibrations generated by vehicles and is less susceptible to environmental factors. The proposed approach leverages the fractional wavelet domain to extract both time and frequency signatures of vehicles from the seismic data effectively. These signatures are then used to train a recurrent neural network that captures the temporal features of the input, thereby facilitating vehicle classification. Additionally, the proposed approach incorporates various modules to improve the generalization and robustness of the deep model against noise. The implementation of the proposed approach on realistic data demonstrated its ability to classify vehicles with an accuracy of 98%, improving upon the state-of-the-art techniques. © 2023 IEEE.

关键词： Vehicles

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Greenhouse monitoring system based on PLC and wireless sensors

Greenhouse monitoring system based on PLC and wireless senso...

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international conference on control Systems and computer Science (CSCS)

作者： Alexandru Dumitrascu Department of Automatic Control and System Engineering University Politehnica of Bucharest Bucharest Romania

The modern monitoring and control systems that are currently used in most fields are based on intelligent algorithms, distributed management systems, and a new generation of communication buses. For the monitoring and control of the processes inside a greenhouse, the use of sophisticated algorithms or complex devices is not required. However, in order to make the activity more efficient and increase the production of a greenhouse, a proposed solution is to use data management and control devices such as PLCs, and the data acquired from the greenhouse to be retrieved by means of sensors connected to nodes with wireless transmission. The wireless communication variant proved to be the most efficient, in the greenhouse environment being an increased humidity due to the irrigation process of the plants. Also, the need for space for the plants requires giving up the wires drawn through the greenhouse.

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Application Research of computer Artificial Intelligence Technology in intelligent Home System

Application Research of Computer Artificial Intelligence Tec...

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Data Science and computer Application (ICDSCA), IEEE international conference on

作者： Shuiying He Shanghai Institute of Commerce & Foreign Languages Shanghai China

This paper constructs an intelligent home monitoring system based on NI wireless sensor network. The system consists of multiple sensors to collect temperature and humidity, smoke, theft and other environmental data. The NI wireless sensor network node sends the data to the upper PC in the way of wireless network. LabVIEW software is used to judge and control the data on PC. The system has obtained a good man-machine interface. Among them, the software design process of the system is introduced in detail. The intelligent home monitoring system has the characteristics of NI wireless sensor network -- low power consumption, good real-time performance, easy to expand, remote monitoring and so on.

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Research on Multi-Parameter computer intelligent monitoring System for Insulation Performance of Key Probe in Nuclear Power Plant

Research on Multi-Parameter Computer Intelligent Monitoring ...

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international conference on Information Systems and computer Aided Education (ICISCAE)

作者： Yu Wang Haiyan He CGN Digital Technology Co. Ltd. CGNPC Beijing China CGNPC Uranium Resources Co. Ltd. Beijing China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

In this paper, an intelligent insulation monitoring system for power equipment of nuclear power plant is proposed. The PC terminal instrument communication and data acquisition program is mainly responsible for receiving and saving the data at the instrument end during the system detection process under the command of the control system and cooperating with the instrument, and generating or exporting the data format for later reading and analysis. After the overall detection process is completed, the program is responsible for output a statistical information, which is used to give the detection date and time. The device improves the leakage current method and the bridge method. The insulation resistance of DC system is detected by the testing principle of ping-pong transformer bridge, which is not affected by the large distributed capacitance of nuclear power plant. The system adopts advanced detection principle and computer technology to realize effective on-line monitoring of DC system and improve the reliability and stability of DC system. Measuring instruments need to provide communication protocols such as current, voltage and other relevant information for software development.

关键词： Resistance Insulation Voltage measurement Bridge circuits Stability analysis Leakage currents Power generation monitoring Testing Power transformer insulation

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international conference on Autonomous Unmanned Systems, ICAUS 2022

International Conference on Autonomous Unmanned Systems, ICA...

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international conference on Autonomous Unmanned Systems, ICAUS 2022

ISBN: (纸本)9789819904785

The proceedings contain 362 papers. The special focus in this conference is on Autonomous Unmanned Systems. The topics include: Integrated Virtual Simulation and Test System for Vision-Based Applications of UAVs;UAV Integrated Internet-of-Vehicle (IoV) System for Flooding monitoring and Rescue;pursuit-Evasion Games for Multi-agent Based on Reinforcement Learning with Obstacles;air Exhaust Environment Simulation of Altitude Test Facility control Based on Model-Assisted Active Disturbance Rejection control;underwater Vortex and Aggregation Behaviors Based on Monocular Vision;Visual Active Tracking Algorithm for UAV Cluster Based on Deep Reinforcement Learning;a Camera-Based Real-Time Parking Positioning Method for Air-Ground Vehicles;Evaluation of Autonomous Capability of Ground Attack UAV Based on Hierarchical Analysis Method;intelligent Air Combat Maneuvering Decision Based on TD3 Algorithm;research on Transmitting Beamforming of Uniform Circular Frequency Diversity Array Sonar;preface;Online Compensation Method for Inertial Device Error of Airborne UAV;enhanced Reinforcement Learning Method Based on AlphaGo-Zero;a Self-organizing Dual-Layer Defense Algorithm for Multi-agent Systems;deep Reinforcement Learning Based on Curriculum Learning for Drone Swarm Area Defense;Reinforcement Learning-Based Cooperative Adversarial Algorithm for UAV Cluster;UAV Maneuvering Target Tracking with Position-Attitude Fusion;formation control of Multi-agent Based on Deep Reinforcement Learning;A HPEDF-Based Reinforcement Learning Radar Scheduling Method;environmental Target Recognition System for ROV Based on Forward Looking Sonar;fast Parking Slot Detection in the Bird's Eye View;Design of UAV 3D Visual Simulation System Based on X-Plane;Multi-agent Deep Reinforcement Learning for Dynamic Motion control Allocation in UAV Swarm Cooperative Jamming to Netted Radar;Research on distributed Task Decision-Making Method of UAV Swarm Based on Information Consistency.

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6th EAI international conference on 6GN for Future Wireless Networks, 6GN 2023

6th EAI International Conference on 6GN for Future Wireless ...

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6th EAI international conference on 6GN for Future Wireless Networks, 6GN 2023

ISBN: (纸本)9783031534003

The proceedings contain 60 papers. The special focus in this conference is on 6GN for Future Wireless Networks. The topics include: Application of MED-TET to Feature Extraction of Vibration Signals;a Novel Phase Congruency-Based Image Matching Method for Heterogenous Images;design of Image Based Optical Flow Tracking and Positioning System in intelligent Assembly;a Review of Image and Point Cloud Fusion in Autonomous Driving;deep Learning in Strawberry Growth monitoring Research: A Review;stepwise Change and Refine Network for Human Pose Transfer;performance Analysis of Web Server Side Reactive Programming;improved Sparrow Search Algorithm Optimized Neural Network Analysis of Traffic Congestion;industrial Noisy Speech Enhancement Using Joint Time-Frequency Loss Function Based on U-Net;Multiple Color Feature and Contextual Attention Mechanism Based on YOLOX;improved War Strategy Optimization Algorithm Based on Hybrid Strategy;quantitative Analysis on Coin Flipping Protocol;Research on Cost Optimization of UAV Network Routing Protocol Based on OLSR Protocol;a Lightweight Fault Diagnosis Model of Rolling Bearing Based on Gramian Angular Field and EfficientNet-B0;ISAC Device-Free Sensing Method for V2V System;fuzzy Sliding Mode Trajectory Tracking control for Omnidirectional Mobile Robots Based on Exponential Convergence Law;image Classification Method Base on Contrastive Learning;Research on RFID Indoor Localization Algorithm Based on Virtual Tags and Fusion of LANDMARC and Kalman Filter;Research on Information Literacy Teaching of Library MOOC Based on Constructivism;research on Smart Library System Based on Big Data;smoke Segmentation Method Based on Super Pixel Segmentation and Convolutional Neural Network;Research on distributed Routing Technology for LEO Satellite Network.

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Construction of intelligent Building Automation control System Based on Fuzzy Clustering Algorithm

Construction of Intelligent Building Automation Control Syst...

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Internet of Things, Robotics and distributed Computing (ICIRDC), international conference on

作者： Jing Liu Yu He Harbin Huade University Harbin China

With the vigorous development of the construction industry, the market demand for automatic control systems is increasing, and it has attracted domestic and foreign automation system manufacturers to continuously improve the software for computer control management, emphasizing the humanized use of interfaces, and ensuring the orderly use of building machinery and fire protection, security, and parking management. In this regard, this article constructs an intelligent building automation control system based on fuzzy clustering algorithm, which can effectively improve the intelligence and prevention level of buildings. The intelligent building equipment automation control system utilizes modern scientific technologies such as communication technology, computer network technology, and intelligent monitoring technology. It uses hierarchical clustering to obtain the initial number of clusters from offline data, and then performs fuzzy clustering on incremental data. However, there is a problem of needing to set parameters to identify outlier samples. Comparative experiments have been conducted to verify the time for receiving control instructions between the traditional system and the system in this paper. The average receiving time of the traditional system is 18.95 seconds, while the average receiving time of the system in this paper is 12.75 seconds, which shortens the receiving time of control instructions by 6.2 seconds compared to the traditional system. The above experimental results once again validate the effectiveness of the system in this paper.

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6th EAI international conference on 6GN for Future Wireless Networks, 6GN 2023

6th EAI International Conference on 6GN for Future Wireless ...

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6th EAI international conference on 6GN for Future Wireless Networks, 6GN 2023

ISBN: (纸本)9783031534034

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