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Exploration on computer Video intelligent monitoring and Tracking System Based on PSO Algorithm

Exploration on Computer Video Intelligent Monitoring and Tra...

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international conference on Computational Intelligence and Communication Networks (CICN)

作者： Chunrong Zhou Zhenghong Jiang School of Big Data Chongqing Vocational College of Transportation Jiangjin Chongqing China

In order to ensure the accuracy of the monitoring system, this paper experimentally designs and determines to set up sensor nodes in the distributed power supply branch points, collects the current, voltage, and high-frequency signals of these branch points, and forms a cluster of every 20–40 nodes. Using short-range communication Zig Bee technology, a tree-shaped wireless sensor network can be formed. Each network uses C language to program the improved PSO algorithm, and embedded in the ZigBee core chip CC2530, thus constructing a monitoring platform based on the PSO algorithm of the underlying data acquisition system. The bottom layer data of the monitoring system is input into the bottom layer embedded system through the convergence node of the wireless sensor network, and then uploaded to the central control center by the embedded system through the public transmission network to realize the remote centralized monitoring of the distributed power supply. The intelligent computer video monitoring system based on particle swarm optimization (PSO) algorithm explored in this paper is proved experimentally to be superior to other techniques in terms of MOTA index, MT, FP, etc., with the values of 99%, 120 times, and 99 times of the traditional techniques, respectively.

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Early detection of DDoS attack using integrated SDN-Blockchain architecture for IoT

Early detection of DDoS attack using integrated SDN-Blockcha...

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2022 international conference on Innovative Computing, intelligent Communication and Smart Electrical Systems, ICSES 2022

作者： Sumathi, A.C. Ahalawat, Anchal Rameshkumar, Abijoy KPR Institute of Engineering and Technology Computer Science and Engineering Coimbatore India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

The advancement in technology with the internet commences the new era of communication by allowing people to communicate through text, audio and video calling, images and video clips and various other applications. The applications of internet paved the way to a technology called Internet of Things (IoT). IoT is interpreted as communication between components, (e.g., sensors and actuators) through the internet designed for application-oriented assistance. IoT is simple and user friendly which attracted the people to adapt the technology. Despite the immense benefits of the IoT device, it is *** results in the devices to undergo various attacks. distributed Denial-of-Service (DDoS) attack challenges the security in IoT devices. Therefore, this paper proposes the integrated SDN-Blockchain architecture to provide the secure connection for IoT devices. Software Defined Networking (SDN) technology is used in optimizing the network management, enabling a dynamic and efficient network configuration programming thereby optimizing the performance and monitoring the network. SDN transforms computer network by segregating control plane and data plane. Blockchain is represented as collection of blocks which are linked together as a back traced *** previous block hash is used to connect the blocks together in the chain. The characteristics of Blockchain include decentralization, peer-to-peer connectivity, and immutable ledgers. © 2022 IEEE.

关键词： Internet of things

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Research on intelligent Big Data Information monitoring System Based on computer Machine Learning Technology

Research on Intelligent Big Data Information Monitoring Syst...

引用

computers, Information Processing and Advanced Education (CIPAE), 2020 international conference on

作者： Yitian Liu School of Earth Sciences Zhejiang University Hangzhou China

The communication information acquisition system has the problem of high packet loss rate. This paper designs an intelligent communication big data information monitoring system based on genetic algorithm. Through the built-in Transmission control protocol/Internet Protocol (TCP/IP) stack, additional pins are selected as the carrier of the register and connected to the circuit. Through the design of environmental information communication software architecture, coordination node program and terminal node program, the environmental communication software system is designed. The wireless communication network is selected as the network module of the communication information monitoring system, and combined with the transmission link balanced configuration method, the communication information monitoring data is sent and received and the communication route is designed. The simulation results show that the overall stability of the system is superior. The output results are accurate and reliable.

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Integration of smart Sensors and Machine Learning Algorithms for Automated Pest Management

Integration of smart Sensors and Machine Learning Algorithms...

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Sustainable Energy Technologies and Computational Intelligence (SETCOM), international conference on

作者： Krrish Yadav Sritama Roy School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

This paper presents a new IoT-based approach for agricultural pest control, incorporating machine learning techniques. Traditional pest monitoring methods are labor-intensive and often result in the overuse of pesticides. The proposed system solves this problem by predicting pest populations using environmental data collected via IoT sensors. We use random forest regression and random search cross-validation to predict pests and identify important factors. The system calculates the amount of pesticides based on forecasts, helping farmers optimize use and reduce environmental impact. The experimental results demonstrate the effectiveness of the system in terms of accurate prediction and optimal pesticide application, and thereby providing a scalable and cost-effective solution for sustainable agriculture.

关键词： Temperature sensors Temperature distribution Accuracy Pesticides Humidity Pest control Agriculture Data models Random forests intelligent sensors

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Regional Forest Fire Detection and control: An Integrated Approach Using distributed Sensing and Automated Suppression Systems

Regional Forest Fire Detection and Control: An Integrated Ap...

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IoT Based control Networks and intelligent Systems (ICICNIS), international conference on

作者： Abha Marathe Manas Kadam Shreya Narayanrao Mohite Prachi Lasurkar Riya Lanjewar Pranav Modhave Electronics and Communication Engineering Vishwakarma Institute of Technology Pune Computer Engineering Vishwakarma Institute of Technology Pune

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

Forest fires present a significant hazard to property, lives, and ecosystems globally, necessitating swift detection and containment measures. Historically, manual forest fire control systems relied on human observation and reporting, which often resulted in delayed responses and increased damage. The forest is divided into target areas, with each area equipped with intelligent software interfaces, automated response mechanisms, flame sensors, and sprinklers. The proposed system relies on advanced flame sensor technology for prompt and accurate fire outbreak detection. Upon detection, real-time fire data is transmitted to a cloud-based platform, ***, for comprehensive monitoring and analysis. This division allows for targeted intervention and efficient resource allocation based on the severity and location of the fire. The flame sensors used in this system have a range of up to 100 meters, allowing for extensive coverage of forest areas. Additionally, the system includes automated sprinklers that activate immediately upon fire detection, providing an immediate response to help contain and extinguish the fire. By leveraging *** for data transmission and analysis, stakeholders gain valuable insights into fire behavior, facilitating informed decision-making and long-term mitigation strategies. This integrated approach offers a comprehensive solution to combat forest fires, emphasizing early detection and efficient containment to minimize damage and protect both natural habitats and human communities.

关键词： Prevention and mitigation Fires Forestry Sensor systems Software Real-time systems Stakeholders Resource management monitoring intelligent sensors

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AI-Enabled Safe and Scalable Pet Care: An intelligent System for Real Time Health monitoring and Care

AI-Enabled Safe and Scalable Pet Care: An Intelligent System...

引用

international conference on ent Computing and control Systems (ICICCS)

作者： Aravind G Jeeva S Selvaganesh D S.P. Sasirekha Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore India

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

Modern pet health management requires advanced solutions because the world demonstrates rising demand for companion animals. The current pet care systems operate without real-time data monitoring because they do not adapt to shifting diagnostic criteria. An AI-powered pet management system based on Internet of Things (IoT) links a secure cloud-edge computing system to offer these capabilities. A proposed system depends on strong machine learning techniques to deliver persistent health tracking while simultaneously analyzing behavioral patterns and carrying out automatic care operations. Through its IoT-connected smart sensors the system obtains real-time data which enables it to identify anomalies as soon as possible while providing tailored medical solutions. A modular distributed architecture design offers better system adaptability thus making possible seamless operations between multiple operational domains. Security is of utmost importance in the system so a combination of encryption layers works together with authentication protocols and monitored data channels serve to secure both privacy and data integrity. The experimental findings reveal that predictions about behavioral outcomes together with optimized resource usage and system protection function at superior rates than traditional methods do. A thorough analysis of both ethical practices and data security measures exists for automated pet supervision to facilitate responsible program execution. This recommended system gives remote accessibility together with multi-functional pet care operations to provide safe services which benefit all pet owners along with veterinarians and additional stakeholders. The future research agenda includes developing hybrid federated learning systems to deliver individualised diagnoses as well as using diversified health data from various sources to conduct more thorough examinations while striving to enable this monitoring method in various animal care settings. Such resear

关键词： Ethics Animals Data security Scalability computer architecture control systems Real-time systems Internet of Things Stakeholders monitoring

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Human Violence Detection Using LHOGF Algorithm and Deep Learning Model 4

Human Violence Detection Using LHOGF Algorithm and Deep Lear...

引用

4th international conference on Advances in Computing, Communication control and Networking, ICAC3N 2022

作者： Chauhan, Akash Gupta, Ruchika Chandigarh University Computer Science and Engineering India

ISBN: (纸本)9781665474368

A minor action of human is performed with some purpose. Understanding the behavior and the way to interact of human with environment in automatic way has attained a lot of attention in research field over past few years due to its potential in diverse domains. Several applications such as intelligent video surveillance and for monitoring the environmental home, for storing and retrieving the video etc. are related to the domain of recognizing the human activity. The human violence is detected in several stages in which the data is pre-processed, features are extracted, and the data is classified. This research introduces a deep learning algorithm for predicting the human violence. Python is executed to simulate the introduced algorithm and diverse metrics such as precision, and recall are considered to analyze the outcomes. The proposed model shows significant high performance as compared to existing model. © 2022 IEEE.

关键词： Python

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Smart Transportation Revolution: Adaptive monitoring with Squeeze and Excitation Networks

Smart Transportation Revolution: Adaptive Monitoring with Sq...

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Advanced Computing Technologies (ICoACT), international conference on

作者： A P Naveen M C Monisha T Shanmugapriyan B G Geetha Department of Computer Science and Engineering K. S. Rangasamy College of Technology Tiruchengode India

ISBN: (数字)9798331509859

ISBN: (纸本)9798331509866

In the rapidly advancing field of smart cities, effective traffic management is essential for improving safety, alleviating congestion, and minimizing environmental damage. This paper rigorously examines the function of deep learning in adaptive traffic monitoring and presents an innovative method utilizing Squeeze and Excitation Networks (SENets). SENets enhance traffic monitoring systems by dynamically recalibrating feature maps, allowing for the prioritization of important features and hence boosting detection accuracy in intricate urban settings. The suggested system combines real-time data from IoT sensors, security cameras, and vehicular networks, offering a comprehensive framework for traffic monitoring and accident prevention. Experimental findings indicate that the SENets-based model attains a 94.5% accuracy in identifying traffic abnormalities and enhances signal control optimization by 30% relative to traditional methods. These findings highlight the capacity of SENets to transform urban traffic management, providing a scalable and economical solution for intelligent transportation systems.

关键词： Adaptive systems Accuracy Smart cities Transforms Feature extraction Sensor systems Smart transportation Safety Security monitoring

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Incentive Mechanism for Mobile Crowd Sensing Using Reverse Auction Dynamic Pricing and Recent History 3

Incentive Mechanism for Mobile Crowd Sensing Using Reverse A...

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3rd international conference on Advances in Computing, Communication, Embedded and Secure Systems, ACCESS 2023

作者： Yangchin, Jowa Marchang, Ningrinla North Eastern Regional Institute of Science and Technology Department of Computer Science and Engineering Nirjuli791109 India

ISBN: (纸本)9798350346169

Mobile crowd sensing is a technique that allows collection of real-time data from a large number of mobile users who carry a mobile device with sensing capabilities. It is widely used for data sensing applications, such as traffic monitoring, environmental monitoring, health and fitness, retail marketing, and emergency response. It requires individual users to perform the sensing task based on the location of the task and the user. Ensuring privacy and security of individuals and accuracy and reliability of the data collected are primary challenges in a mobile crowd sensing system. To motivate more users to collect data, it is required for the system to be built in a manner that each user is rewarded for the task done while maintaining the budget balance. As users are of heterogeneous nature, they must be rewarded for the task done based on their own true valuation of the task. The reverse auction method for mobile crowdsensing is becoming one of the widely used incentive mechanism for its choice to the mobile users, who act as the participating workers, for fixing the price for which they want to sell the sensed data. For a reverse auction system to work, it is required that there are enough users who are willing to bid in an auction round. Maintaining a participant pool with enough competition while keeping the bid values near to true values is a key challenge to be addressed. Failing to maintain enough participants can result in higher bid prices with each round and hence increasing total reward value to be distributed. This may lead to incentive explosion where the bid price is too high for the available budget. In this work, we propose a novel approach of retaining users by considering the frequency of winning and participation of users. This mechanism is built on top of RADP-VPC which is reverse auction mechanism based on reverse- auction with dynamic pricing with virtual participation credit. The experimental results show that the proposed approach using part

关键词： Budget control

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Research on Modeling Method of Digital Twin of Lithium Battery Based on Data-Model Hybrid Drive

Research on Modeling Method of Digital Twin of Lithium Batte...

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Power Electronics, computer Applications (ICPECA), IEEE international conference on

作者： Yuxin Zhang Jianhua Wu Shanxun Sun Tao Ye Energy and Electricity Research Center Jinan University Zhuhai China Guangdong Electrical and Intelligent Control Engineering Technology Research Center Institute of Rail Transportation Jinan University Zhuhai China

Lithium battery, as an important part of new energy storage, its scientific and safe use and management has become a key factor to achieve low-carbon technology. Lithium-ion battery is a highly nonlinear system, and its operating state is susceptible to environmental interference and other disturbances, resulting in errors. Aiming at the error caused by the disturbance of the running state of lithium battery, this paper proposes a method of digital twin modeling of lithium-ion battery which integrates the mechanism model and the data-driven model. The adaptive particle swarm optimization support vector machine regression (SVR) algorithm was used to conduct data-driven modeling for the errors between the mechanism model and the battery entity data, and the errors were corrected to obtain a real-time and high-precision battery model, which realized condition monitoring and offline simulation display. Moreover, the accuracy of the model was verified through experiments, proving that it can lay a foundation for the safe and intelligent management and control of the battery system.

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