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

共 1799 条记录，以下是41-50 订阅

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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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Step-Wise Working Status for Next-Generation Smart Cities: Integrating Fog and Edge Computing Solutions

Step-Wise Working Status for Next-Generation Smart Cities: I...

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2025 international conference on Visual Analytics and Data Visualization, ICVADV 2025

作者： Beevi, L Sherin Nehru, V. Joe Prathap, P.M. Dani, W. Vinil R.M.D. Engineering College Department of Computer Science and Engineering Kavaraipettai India Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Computer Science and Engineering Avadi Chennai India St. Peter's College of Engineering and Technology Department of Eee Avadi India

ISBN: (纸本)9798331521394

In the fast changing environment of smart cities, combining fog and edge computing with powerful IoT devices like Hikvision cameras is revolutionising urban administration and public safety. Hikvision, a video surveillance systems pioneer, offers a variety of IP and analogue cameras, thermal imaging, and intelligent software platforms used for traffic management, public safety, environmental monitoring, and infrastructure security. These technologies, which combine high-definition video quality, advanced image processing, and cognitive analytics, enable real-time monitoring, event detection, and quick responses. Traffic cameras collect real-time data for vehicle counts and congestion management, while environmental sensors monitor air, water, and noise levels to aid in health warnings and pollution control. Smart meters and wearable health gadgets monitor energy, water, and health indicators to optimise resource management. Parking sensors and waste management sensors boost parking and rubbish collection efficiency. The integration of fog and edge computing processes data locally, lowering latency and bandwidth utilisation, while fog nodes aggregate data for thorough analysis. Cloud storage enables long-term data analytics, which improves decision-making for city planners and emergency responders. Hikvision's software, which includes HikCentral and iVMS-4200, combines video surveillance, access control, and intelligent traffic management to create a comprehensive urban security framework. These systems are crucial to public safety because they provide real-time monitoring, facial recognition, and motion detection. For city planners, such innovations provide essential insights for urban growth and sustainability programs. The integration of Hikvision video surveillance with fog and edge computing is a game-changing approach to smart city management, improving urban safety and efficiency while improving inhabitants' quality of life. © 2025 IEEE.

关键词： Water pollution control

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Peer-to-Peer Integrated Smart Gardening Automation Using Cloud Technology with Real-Time environmental monitoring and Logging via Blynk Cloud Dashboard

Peer-to-Peer Integrated Smart Gardening Automation Using Clo...

引用

intelligent control, Computing and Communications (IC3), international conference on

作者： Praveen Kumar Malik Veena Bharti Neeti Misra Nagendar Yamsani Anshul Mahajan Parulpreet Singh School of Electronics and Electrical Engineering Lovely Professional University Phagwara Punjab India Raj Kumar Goel Institute of Technology Ghaziabad India Department of Management Uttaranchal Institute of Management Uttaranchal University Dehradun Uttarakhand India School of Computer Science and Artificial Intelligence SR University Warangal India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

The authors of this article discuss the holistic method of automation of gardening operations based on IoT technology that allows real time environmental factors to be monitored, decisions to be made based on data, and those decisions to be executed at a distance. The objective of the system is to minimize the amount of water used, to improve the state of the plants, and ultimately to allow the users of the system to control their gardens from anywhere in the world with as little effort as possible. The concept makes use of the continuously monitored network of sensors to observe important parameters like soil moisture, temperature, humidity, light intensity and rainfall among others. After being received, this information is up to date and the system will use this data to manage irrigation and lighting systems for the plants efficiently. Also, the support of this cloudbased platform is essential today as it allows the users to look up the parameters in their garden remotely and go for manual intervention when required. All the advantages of cloud technology provide remote control of the system but also all the historical data sets which are important trends in future decision making.

关键词： Temperature sensors Temperature measurement Irrigation Automation Clouds Lighting Crops Real-time systems Water pollution Water resources

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On Developing Smart IoT-Based distributed System for Remote Detection of Slope Movements

On Developing Smart IoT-Based Distributed System for Remote ...

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international conference on Computing, Networking and Communications (ICNC)

作者： Rahul Debnath Ahmed Abdelmoamen Ahmed Md Jobair Bin Alam Department of Computer Science Prairie View A&M University Prairie View TX USA Department of Civil Engineering Prairie View A&M University Prairie View TX USA

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

Landslides or slope failures cause significant damage to the transportation infrastructure worldwide, resulting in billions of dollars of property damage. The initial slope movement of highway slopes, caused by environmental factors and man-made activities, must be detected early to prevent significant losses in infrastructure damages and human lives. However, traditional monitoring approaches for slope movement, such as periodic human inspection and surveying, are labor-intensive and time-consuming. With the advent of the Internet of Things (IoT) and high-speed internet, the potential to use such technologies for monitoring remote earth movement of highway embankments is becoming increasingly important. This paper presents an IoT-based distributed system for the early detection of slope movements to assist transportation authorities in immediately repairing the slope before a major failure occurs. We built a laboratory prototype embankment, equipped with various IoT sensors (e.g., tilt, moisture, and tensiometer sensors), that simulate a failure-prone slope to evaluate the effectiveness of our system. A user-friendly GUI is developed to enable users to utilize the system remotely. The collected sensory data for four months allowed us to analyze the soil hydrologic dynamics and the slope performance by detecting changes in the slope tilting both parallel (pitch) and perpendicular (roll). The experimental results showed that our system could detect negligible movement (1mm) and rotation (0.02°) of slopes.

关键词： Road transportation Working environment noise Transportation Artificial neural networks Sensor systems Vectors Internet of Things Remote monitoring intelligent sensors Graphical user interfaces

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Target Identification and Detection Using Hyperpectral Signature Transformation

Target Identification and Detection Using Hyperpectral Signa...

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international conference on intelligent control and Information Processing (ICICIP)

作者： Nian Zhang Oshin Wilson Lara A. Thompson Department of Electrical and Computer Engineering University of the District of Columbia Washington D.C. USA Department of Mechanical Engineering BME University of the District of Columbia Washington D.C. USA

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

Hyperspectral imaging has emerged as a powerful technique for target detection and material identification across various fields, from remote sensing to environmental monitoring. This paper proposes a spectral signature matching method for detecting a known target (i.e., sea water) in hyperspectral images. By analyzing pixel-by-pixel spectral characteristics, spectral matching algorithm computes the similarity between the spectral signature of each pixel and that of known target *** proposed method employs the Jasper Ridge hyperspectral data from an urban landscape to demonstrate the algorithm’s effectiveness, with results revealing high accuracy in target detection even in heterogeneous environments where various land cover types (like water, vegetation, urban structures, soil, and rocks) are intermixed within the same area. This highlights the algorithm’s robustness in discerning similar spectral features. The experimental results demonstrate that the Jeffries-Matusita Spectral Angle Mapper (JMSAM) outperformed the Spectral Angle Mapper (SAM) and the Normalized Spectral Similarity Score (NS3) algorithms, by achieving the lowest MSE of 0.056933.

关键词： Water Accuracy Land surface Vegetation mapping Object detection Soil Rocks Robustness Hyperspectral imaging intelligent control

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Step-Wise Working Status for Next-Generation Smart Cities: Integrating Fog and Edge Computing Solutions

Step-Wise Working Status for Next-Generation Smart Cities: I...

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Visual Analytics and Data Visualization (ICVADV), international conference on

作者： L Sherin Beevi V. Nehru P. M. Joe Prathap W. Vinil Dani Department of Computer Science and Engineering R.M.D. Engineering College Kavaraipettai INDIA Department of Computer Science and Engineering Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Avadi Chennai Department of EEE St. Peter's College of Engineering and Technology Avadi INDIA

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

关键词： Cloud computing Smart cities Video surveillance Cameras Real-time systems Public security Internet of Things intelligent sensors Water resources Edge computing

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Prediction of Quality and Lifetime of Fruit using Deep Learning

Prediction of Quality and Lifetime of Fruit using Deep Learn...

引用

international conference on ent Computing and control Systems (ICICCS)

作者： Gurram Sai Harshit Guntupalli Jothish L.Sujihelen Department of CSE Sathyabama Institute of Science & Technology Chennai India

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

This proposed system focuses on developing a predictive model "Prediction of Quality and Lifetime of Fruits Using Deep Learning" is to create a reliable system for predicting fruit shelf life and evaluating fruit quality in real time. The system examines fruit photos to determine surface flaws, maturity levels, and general quality using Deep Learning-based object detection. It predicts how long fruits will last on the shelf by taking into account environmental factors like temperature and humidity. A Deep Learning model is trained using the preprocessed dataset, which comes from Roboflow, to ensure precise detection and classification. By decreasing fruit waste and empowering farmers, distributors, and retailers to make well-informed decisions, this technology aims to maximize supply chain management. In order to improve food quality monitoring and guarantee efficiency, sustainability in the agricultural industry. The suggested solution integrates computer vision and Deep Learning algorithms. The proposed work performs better when compared with the existing algorithms.

关键词： Deep learning computer vision Visualization Supply chain management Temperature Computational modeling Object detection Prediction algorithms Real-time systems Tuning

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A Bayesian Belief Network Framework for Protecting Generative AI-driven Attack in Smart Grid Communication

A Bayesian Belief Network Framework for Protecting Generativ...

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international conference on Computing, Networking and Communications (ICNC)

作者： Md Shirajum Munir Sravanthi Proddatoori Manjushree Muralidhara Sachin Shetty School of Computing Analytics and Modeling Univesity of West Georgia Carrollton GA USA Dept. of Computer Science Old Dominion University Norfolk VA USA Dept. of ECE Old Dominion University Norfolk VA USA

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

In the era of artificial intelligence (AI), native generative AI (GenAI) has become prominent in generating intelligent cyber-attacks in a smart grid environment by imitating operational parameters and metrics. As a result, it is imperative to understand the attack generation capabilities of native GenAI models, such as Generative Adversarial Networks (GANs) and Autoencoders in a smart grid environment. This research aims to explore the potential of GenAI models to accurately imitate and analyze the behavior of cyberattacks within a smart grid environment. The goal is to understand the risks posed by these intelligent attacks while developing strategies to protect against disruptive distributed Energy Resources (DER) events, such as incorrect load shifting, imbalanced demand supply, and unstable price forecasting. First, this work leverages two customized native GenAI models, namely GAN and Autoencoder, to synthesize DERs control message parameters such as nominal power consumption, price elasticity coefficients, and communication data packets, among others, to introduce highly unpredictable new intelligent attack vectors. Second, this research proposes and develops a new Bayesian Belief Networks (BBNs) framework by creating correlation dependency nodes among DER control message parameters to understand the risks of intelligent attack vectors better while monitoring and mitigating their impact on smart grid operations. In particular, by leveraging the customized BBN, the system can observe and analyze the uncertain behaviors in DER operations that GenAI introduces, and the proposed framework can help mitigate grid vulnerabilities by understanding the poisonous parameters through mutual information. Finally, the experiment results show that the Autoencoder outperformed GAN in reproducing intelligent attacks with an MSE about 98.984% lower than that of GANs. Additionally, BBN can explain prominent parameters of the intelligent attacks’ by quantifying dependencies thro

关键词： Generative AI Autoencoders Generative adversarial networks Vectors Data models Smart grids distributed power generation Bayes methods Mutual information Load modeling

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An Integrated IoT and Wireless System for Energy Optimization and Real-Time monitoring Towards Sustainable and Efficient Building Management in Smart Buildings

An Integrated IoT and Wireless System for Energy Optimizatio...

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intelligent control, Computing and Communications (IC3), international conference on

作者： Someet Singh Praveen Kumar Malik Ashish Singh Chauhan Manoj Kumar Nagendar Yamsani Parulpreet Singh School of Electronics and Electrical Engineering Lovely Professional University Phagwara Punjab India Uttaranchal University Dehradun Uttarakhand India Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad India School of Computer Science and Artificial Intelligence SR University Warangal India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

At a time when urbanization is increasing, and the world's energy need is growing, energy efficiency in building elements has become a key factor in the environment impact mitigation and operational cost reduction strategies. Building management is governed by traditional operational features that are often inadequate to contemporary occupation patterns, infrastructural demands, and environmental changes. Consequently, there is a growing tendency towards the implementation of integrated systems such as autonomous management systems which can oversee energy use and other resources without sacrificing comfort and safety. Cloud storage and wireless technologies have now made it possible to improve energy management like never before. By making use of such technologies, smart building systems are able to receive, transmit and monitor data from many networks in real time. This capability further enhances the control of energy-demanding devices and processes such as heating, ventilation, and lighting, which are controlled and manipulated by preset schedules and manual settings. In addition to this, predictive maintenance and detection of inefficiencies is possible due to real time data analysis trends, usage history and anticipation of external consumption forces.

关键词： Wireless communication Renewable energy sources Smart buildings Buildings Urban areas Real-time systems Energy efficiency Sustainable development Optimization monitoring

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IoT-Driven Smart Car Parking System: Optimizing Urban Mobility and Reducing environmental Impact

IoT-Driven Smart Car Parking System: Optimizing Urban Mobili...

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intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Y. Tanvi B. Lakshmi Sowmya Prashanth B N Shinu M Rajagopal Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India Dept. of Electronics and Communication Engineering Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India Dept. of Mechanical Engineering Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

The rapid increase in urban vehicle numbers has significantly worsened traffic congestion, particularly in public parking spaces, where conventional parking systems often prove inefficient, leading to wasted time, excessive fuel consumption, and increased environmental pollution. A Smart Car Parking System is proposed to address these challenges by integrating advanced technologies, including the Internet of Things (IoT), to optimize parking operations. The system employs sensors embedded in parking spaces to detect vehicle presence and provide real-time data on availability. This enables drivers to locate free parking spaces efficiently, improving traffic flow. Additionally, the system offers valuable insights to city planners and facility managers, supporting optimal space allocation and dynamic pricing models. By reducing vehicle idling and unnecessary driving while searching for parking, the system helps minimize emissions, contributing to environmental sustainability. The study builds an automated smart car parking system for parking slot monitoring and gate control. The system ensures correct slot occupancy reading, status displayed in real time, and smooth operation of an opening and closing system. It manages additional features such as real-time sensor calibration and effective gate control with a high degree of accuracy and accountability. The proposed Smart Car Parking System represents a key innovation in urban mobility, offering a user-friendly, efficient, and eco-friendly solution to one of the most persistent challenges faced by modern cities.

关键词： Space vehicles Urban areas Automated parking Logic gates Real-time systems Sensor systems Internet of Things Resource management intelligent sensors Traffic congestion

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