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检索条件"任意字段=International Conference on Computer Distributed Control and Intelligent Environmental Monitoring"

共 1800 条记录，以下是1-10 订阅

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Research on an intelligent Atmospheric Environment monitoring System Based on Modular Structure 24

Research on an Intelligent Atmospheric Environment Monitorin...

引用

2nd international conference on Frontiers of intelligent Manufacturing and Automation, CFIMA 2024

作者： Shi, Ting Wang, Peihao Qiao, Junfei Ao, Yunpeng Wang, Kai Zhang, Yuling Beijing Laboratory for Intelligent Environmental Protection Beijing University of Technology Beijing China

ISBN: (纸本)9798400710681

The quality of the atmospheric environment is closely related to human health and has received widespread attention in recent years. Atmospheric environment monitors are used in both production and daily life. However, current atmospheric environment monitoring systems suffer from poor compatibility, expandability, and intelligence. To address these issues, a modular monitoring system was designed. On the main control board, only the microcontroller and essential components for its operation are retained. At the same time, several general-purpose module interfaces are equipped for connecting various modules. The main control board can automatically identify the type of *** replacing sensor modules and data transmission modules, this system can be easily adapted to various usage scenarios. Through multi-point transmission modules, distributed monitoring can be achieved. By incorporating edge computing modules, the monitoring system gains edge computing capabilities, allowing it to run neural network algorithms for predicting and tracing the sources of atmospheric pollutants, thus achieving intelligent monitoring. The results verified the effectiveness of the proposed modular monitoring system, demonstrating its ability to achieve full-scenario, distributed, and intelligent monitoring with strong expandability and high intelligence. © 2024 Copyright held by the owner/author(s).

关键词： environmental monitoring

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Research on intelligent monitoring and optimization control system model of greenhouse environment based on deep learning 4

Research on intelligent monitoring and optimization control ...

引用

4th international conference on Electronic Information Engineering and computer Communication, EIECC 2024

作者： Shao, Xue Chen, Yangfeiyi Chen, Xiwei Zhu, Fengzhe JiLin Agricultural Science and Technology University Electrical and Information Engineering College Jilin Jilin China

ISBN: (纸本)9798331534622

This paper presents an improved intelligent control model for greenhouse environments, integrating environmental monitoring data with a deep learning approach combining multilayer CNN and LSTM networks with model predictive control (MPC). By optimizing model parameters and utilizing data fusion techniques, the system's prediction accuracy and response speed are enhanced. Experimental results from a real greenhouse monitoring system show that the improved model significantly outperforms traditional models and other machine learning algorithms, with a mean absolute error (MAE) of 2.342, mean square error (MSE) of 6.749, and a coefficient of determination (R2) of 0.931, demonstrating its efficiency and reliability in controlling key environmental indicators like temperature, humidity, and CO2 concentration. © 2024 IEEE.

关键词： environmental monitoring

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Decision Tree Based Incident Detection for distributed Progressive Signal System in an Organic Traffic control System 12th

Decision Tree Based Incident Detection for Distributed Progr...

引用

2023 international conference on Smart Cities and Green ICT Systems and international conference on Vehicle Technology and intelligent Transport Systems

作者： Thomsen, Ingo Tomforde, Sven Christian Albrechts Univ Kiel Intelligent Syst D-24118 Kiel Germany

ISBN: (纸本)9783031709654;9783031709661

Today's world-wide traffic congestion significantly contributes to wastage of time and fuel in addition to environmental stress, such as air pollution due to CO2 emissions. To address these concerns, traffic management systems are continually developed and improved to become intelligent and adaptable. For instance, self-organizing strategies like the Organic Traffic control (OTC) system present benefits such as enhanced efficiency, resilience, and scalability. Beyond the de-centralised and traffic-responsive manipulation of traffic signals, synchronised adjustment of traffic lights through Progressive Signal Systems ("Green Waves") plays an important role. As previous work we presented an approach for creating decentralised PSS, taking recognised incidents into account to steer the traffic flows. In this paper we further propose a decision-tree based incident detection mechanism.

关键词： Traffic management Organic traffic control Progressive signal systems Green waves Incident detection Supervised learning

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Construction of Green environmental Protection intelligent control and monitoring System Based on Neural Network Algorithm 2

Construction of Green Environmental Protection Intelligent C...

引用

2nd international conference on distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Cheng, Hao'en Wang, Ziqian Qiu, Jiayi Zhao, Jiahao North China University of Science and Technology Hebei Tangshan China Hebei University of Science & Technology Hebei Shijiazhuang China

ISBN: (纸本)9798350382952

environmental automatic monitoring system has been widely used in iron and steel enterprises, and has achieved certain results, Traditional techniques' imprecise monitoring of environmental contamination and resource use are caused by characteristics such sensor performance, data collecting frequency, and number of monitoring stations, which restrict their accuracy. The accuracy of environmental monitoring data may be increased to more precisely represent environmental conditions by incorporating neural network algorithms and continually learning and optimizing. To lower noise in the data, a significant amount of environmental monitoring data was gathered and preprocessed. While ambient spatiotemporal and temporal data were being recorded, the Inception-Long Short-Term Memory (LSTM) model was built. The outputs of the LSTM and Inception modules were combined via the fusion layer. According to the test set findings, the Inception-LSTM model had an average accuracy of 97.9% in predicting environmental conditions. Therefore, the application of the Inception-LSTM model can accurately predict environmental conditions, It can not only be applied to the environmental monitoring of the existing factory, but also to the monitoring of a certain area. © 2024 IEEE.

关键词： Long short-term memory

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Design of an intelligent computer Room Equipment Safety monitoring System Based on computer Vision 13

Design of an Intelligent Computer Room Equipment Safety Moni...

引用

13th IEEE international conference on Communication Systems and Network Technologies, CSNT 2024

作者： Qiao, Yuya Fujian Normal University Fuqing Branch Fuqing Fujian350300 China

ISBN: (纸本)9798350305463

This article used OpenCV (Open Source computer Vision Library) to preprocess images, and then used positioning methods and horizontal and vertical projection methods to accurately locate the key information to be recognized. Then, convolutional neural networks were utilized to recognize and analyze the segmented images. Based on the characteristics of the layout and dynamic environmental monitoring of the computer room, the computer room equipment safety monitoring system designed in this article includes an environmental monitoring module, a power monitoring module, a security access control monitoring module, and an abnormal alarm module. The average current intensity in the sleep state was 2μA, 10 mA in the wake state, 110 mA in the send state, and 15 mA in the receive state. The computer room equipment safety monitoring system has increased the efficiency and quality of computer room operation and maintenance, improved the intelligence level of power communication room monitoring, and provided a reference for technical solutions for real-time monitoring of other power communication rooms. © 2024 IEEE.

关键词： Access control

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IoT-Enabled Systems for Automated Cat Care: A Comprehensive Literature Review 6

IoT-Enabled Systems for Automated Cat Care: A Comprehensive ...

引用

6th international conference on Cybernetics and intelligent System, ICORIS 2024

作者： Angela, Stephanie Tiomar, Jolin Sudijanto, Justin Anthony Widianto, Mochammad Haldi School of Computer Science Bina Nusantara University Bandung Campus Bandung11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Bandung Campus Jakarta11480 Indonesia

ISBN: (纸本)9798331539603

In its connection, these abstract aims to introduce the paper by explaining how the innovation of IoT has changed pet care by performing feeding, health monitoring, and environmental control features that were proven problematic with conventional techniques. Thus, this literature review seeks to assess the existing literature and track the innovations on the subject of IoT applications in cat care. In the present investigation, by using a PubMed database search of recent articles, the study proves that IoT devices immeasurably improve cat care through telemetry and a distance interface. However, issues like privacy, security, and costs are still among some of the difficulties that organizations face. The results highlight the future possibilities of IoT in cat care and urge for the studies into avenues for the creation of improved secure and inexpensive solutions for the welfare of cats. © 2024 IEEE.

关键词： Automated Feeding environmental control Health monitoring IoT in Cat Care Smart Pet Devices

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international conference on distributed Computing and Optimization Techniques, ICDCOT 2024

International Conference on Distributed Computing and Optimi...

引用

2nd international conference on distributed Computing and Optimization Techniques, ICDCOT 2024

ISBN: (纸本)9798350382952

The proceedings contain 295 papers. The topics discussed include: forecasting online shoppers purchase intentions with cat boost classifier;brain tumor detection and classification using deep learning techniques;advances in thermal imaging: a convolutional neural network approach for improved breast cancer diagnosis;financial fraudulent detection using vortex search algorithm based efficient 1DCNN classification;energy-efficient approach for node selection in routing protocols of wireless sensor networks;data of stable structure of Ag-Au-Pd nanoparticles based on fish swarm algorithm;on the enhancement of energy efficiency of wireless rechargeable sensor networks through mobile charger scheduling;computer information extraction algorithm based on English corpus;construction of green environmental protection intelligent control and monitoring system based on neural network algorithm;and English text spelling error detection and correction based on multi-feature data fusion algorithm.

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IoT-based environmental monitoring System 3

IoT-based Environmental Monitoring System

引用

3rd international conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Abhiram, D. Dhanush Reddy, K. Koushik Reddy, P. Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This project meets the current important demand for the constant monitoring of environmental conditions because climate change and human activities affect ecosystems. Temperature and humidity are measured using the DHT11/DHT22 sensor connected to the ESP8266 microcontroller and the GPS module is used to obtaining the location information. In contrast to current approaches targeting the communication data or energy consumption only, the contaminants of this system are unified, location-based, and central. It provides immediate data transfer to the cloud through a comfortable low power interface for usage in farming, transportation, and more for environmental monitoring. The findings show that all the environmental conditions and location change can be monitored by the IoT-based system which use ESP32/Arduino microcontroller for sensing data by a Bluetooth or Wi-Fi through cloud platform or server and it gives alert message to web interface or mobile application when temperature increases or decreases more than threshold values. This practical system is especially valuable for those areas of interest that require a constant check, such as environmental control or the logistics and health safety of the transported goods or passengers. © 2025 IEEE.

关键词： environmental monitoring

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intelligent monitoring System for Farms Based on Human-computer Interaction and Automatic control Algorithms 1

引用

13th international conference on Frontier Computing, FC 2023

作者： Qin, Gong Zou, Li School of Mechanical and Electrical Engineering Hubei Three Gorges Polytechnic Hubei Yichang443000 China College of General Education Hubei Three Gorges Polytechnic Hubei Yichang443000 China

ISBN: (数字)9789819992997

ISBN: (纸本)9789819992980

With the continuous development of livestock and poultry industry, monitoring of livestock and poultry farms has become more and more important. The monitoring of livestock and poultry farms mainly includes instrument monitoring and environmental parameter monitoring. The purpose of this paper is to study the farm intelligent monitoring system based on human-computer interaction and automatic control algorithm. In view of the real situation and problems encountered in the industrial development of China’s livestock and poultry farming industry, the current situation of environmental monitoring of livestock and poultry farms at home and abroad is analysed. Based on the research of wireless sensor network and human-computer interaction technology, a livestock and poultry environmental monitoring system based on automatic control algorithm technology was designed and developed. The automatic control algorithm was tested and the experiment showed that the overall error of the system was small. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Wireless sensor networks

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Research on computer Artificial Intelligence Technology in Complex Marine Environment Water Detection System 3

Research on Computer Artificial Intelligence Technology in C...

引用

3rd IEEE international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Yubai, Zhang Shuliang, Tan Daohuan, Xu Shandong Marine Forecast and Hazard Mitigation Service Qingdao China

ISBN: (纸本)9798350380989

This paper proposes a real-time monitoring system for offshore water environmental quality. This project combines LoRa wireless communication technology, sensor technology, Web technology and WeChat application technology to achieve long distance and high anti-interference ability. The system can collect, process, transmit, store, share, display, manage and control the environmental quality of offshore waters in real time. The system can be used for coastal water quality monitoring, fishery aquaculture monitoring and aquaculture monitoring. The experimental research proves that the system can realize the real-time, intelligent and long-term monitoring of offshore water environmental quality. This method can solve the problems of short observation distance, high cost, flexible deployment and weak anti-interference ability in Marine real-time monitoring. © 2024 IEEE.

关键词： artificial intelligence computer marine environment water detection system

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