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Advancements in Sustainable Charging Infrastructure: Integrating Solar Energy and IoT for Smart E-Vehicle Charging Stations

Advancements in Sustainable Charging Infrastructure: Integra...

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2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Sivasankar, C. Saravanan, G. Pradeepa, H. Arun, V. Ganesh, E.N. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Sri Sairam Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Thiagarajar College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Madurai India School of Computing Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Tamil Nadu Chennai India Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350313987

An effective and environmentally friendly charging infrastructure is essential due to the rising popularity of Electric Vehicles (EVs). The proposed system offers an efficient approach to this problem by suggesting a solar charging station for EV incorporating the Internet of Things (IoT). In order to encourage the use of renewable energy and lessen the environmental impact, the system uses solar energy to power EV charging stations. IoT technologies improve the charging station's performance by allowing realtime monitoring and control, remote access and data analytics. Considerations for solar panel layout optimization and energy storage are central to this study's emphasis on the design and execution of a solar-powered EV charging station. In addition, the station can easily respond to changes in demand and grid circumstances thanks to dynamic load control made possible by IoT. This research proves the feasibility and efficiency of the proposed Solar with IoT Charging Station for Electric Vehicles via practical assessment and simulations. The results provide a scalable and long-term answer that promotes a cleaner and greener transportation environment by aiding the development of electric mobility and integrating renewable energy. © 2023 IEEE.

关键词： Charging Station Dynamic Load Management Electric Vehicle Internet of Things Solar Energy

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Automated Door to Prevent COVID-19 using Fuzzy Logic 4

Automated Door to Prevent COVID-19 using Fuzzy Logic

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4th International Conference on Electrical, Communication and Computer Engineering, ICECCE 2023

作者： Khokhar, Salah-Ud-Din Sohaib, Rana Muneeb, Abdul Bibi, Irfana Noor, Muhammad Yasir Imran, Muhammad School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Shandong Jinan China Department of Computer Science G.C. University Lahore Punjab Lahore Pakistan Department of Computer Science Faculty of Computing and Information Technology University of Punjab Punjab Lahore Pakistan Department of Electronics G.C. University Lahore Punjab Lahore Pakistan

ISBN: (纸本)9798350369694

Due to the vagueness and uncertainties due to the coronavirus, it is crucial to implement the standard operating procedures (SOPs) issued by the World Health Organization and the authorities. Therefore an effective control system is required that minimizes the vagueness and uncertainties of people who are on the front line during the period of this pandemic checking the entering persons in an indoor area where it is necessary to maintain a distance of six feet from one another to avoid the spread of coronavirus. In this research work, a robust and efficient system has been proposed that takes protective mask and feverishness values as input and applies them using the fuzzy logic algorithm. If these input values are according to the rules defined in the system, then the door will open as an output. Otherwise, the door will not open. It is, finally, analyzing the output values. This fuzzy model had been implemented using a microcontroller. The genuine difference in the duty cycle of the microcontroller’s output pulse was measured using a 100 MHz digital oscilloscope. Our proposed system was compared with different systems reported in the literature. This work reduces the human effort as well as the negligence of people and builds up the management system without the labor in a mint. © 2023 IEEE.

关键词： Fuzzy logic

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A Discussion of Improving Efficiency and Addressing Obstacles with the use of Data mining and IoT for crop production 4

A Discussion of Improving Efficiency and Addressing Obstacle...

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4th IEEE International Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Bisht, Sandeep Alabdeli, Haider Alsailawi, H.A. Kirubananthan, P. Dhabalia, Dharmesh Attiwi, Madi Hashem Al-Khuzaie, Mohammed Y. Mezaal, Ali Abdulkareem Graphic Era Hill University School of Management Uttarakhand Bhimtal India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq University of Kerbala College of Medicine Department of Chemistry and Biochemistry Kerbala56001 Iraq Srm Institute of Science and Technology School of Computing College of Engineering and Technology Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur SRM Nagar Chennai India Vishwakarma Institute of Information Technology Pune India Al-kunooze University College Dental Department Basra Iraq National University of Science and Technology College of Technical Engineering DhiQar64001 Iraq Kut University College Business Administration Department wasit Al kut52001 Iraq

ISBN: (纸本)9798350360165

The advancement of industries such as supply chain management, smart grids, and healthcare has been made possible by the Internet of Things (IoT), which also improves people's daily lives and interactions. However, the growing size and complexity of IoT networks pose challenges in security, authenticity, reliability, and scalability. Blockchain emerges as a solution due to its security, transparency, reliability, and traceability. This study examines the problems with Internet of Things (IoT) systems, talks about how blockchain might help solve them, assesses the state of the art, and suggests a two-layer architectural solution that combines blockchain and IoT utilizing dew and cloudlet computing. This study presents an analysis of a blockchain-based trade origination and verification system, comparing its performance to the Hyperledger Fabric framework. The system comprises three phases: Trade Origination, Verification & Authentication, and Commit. Through experiments, the system demonstrates superior performance in transaction validation, block closing times, and memory scalability as the number of trades and participating nodes increases. © 2024 IEEE.

关键词： Smart contract

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Revolutionizing Aquaculture Practices: IoT and Deep Learning-based Remote Monitoring for Sustainable Fish Farming 5

Revolutionizing Aquaculture Practices: IoT and Deep Learning...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Chelladurai, S. Prince Shiny, G.Susan Jeevitha, S.V. Swapna, P. Pavithra, R. Arulraj, S. Srm Institute of Science and Technology Faculty of Engineering and Technology School of Computing Department of Computational Intelligence Chennai Kattankulathur India Sethu institute of Technology Department of information technology Kariapatti Virudhunagar Tamil Nadu Pulloor626115 India Bannari Amman Institute of Technology Department of information technology Erode India Velammal college of engineering and technology Department of Cse Madurai India Rathinam Technical Campus Department of Ece Coimbatore India

ISBN: (纸本)9798331504403

Aquaculture plays a vital role in meeting the growing demand for seafood while addressing sustainability concerns in fisheries. To optimize fish growth and ensure efficient resource utilization an innovative IoT and Deep Learning-based remote monitoring system is proposed tailored for aquaculture operations. Our system integrates sensor technology, IOT connectivity, and Deep Learning algorithms to provide real-time monitoring and control of key environmental parameters such as water temperature, pH levels, oxygen concentration, and feeding behavior. By leveraging a network of sensors deployed in aquaculture facilities, our system collects and analyzes environmental data to optimize aquaculture practices and ensure optimal conditions for fish growth. Through a user-friendly interface accessible via web or mobile applications, aqua-culturists can remotely monitor the status of their facilities and adjust operational parameters as needed. Additionally, our system utilizes Deep Learning algorithms to analyze historical data and predict optimal feeding schedules, thereby enhancing feed efficiency and fish growth rates. Field trials demonstrate the effectiveness of our IOT and Deep Learning-based monitoring system in improving fish health and productivity while reducing environmental impacts and operational costs. Our findings highlight the potential of IoT and Deep Learning technologies in revolutionizing aquaculture practices, promoting sustainability, and enhancing food security in fisheries © 2024 IEEE.

关键词： Fish

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Smart Ports Solutions for Cargo Container Tracking and Vessel Traffic Counting Systems using IoT and Cloud computing 10

Smart Ports Solutions for Cargo Container Tracking and Vesse...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Priya, S. Sairam, A. Azath, H. Manivannan, S.K. Mohankumar, N. Vedasundara Vinayagam, P. Deemed To Be University Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Vit Bhopal University School of Computing Science and Engineering Bhopal India Faculty of Management Srm Institute of Science and Technology Chennai Tamil Nadu Kattankulathur India Symbiosis Institute of Technology Maharashtra Nagpur India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

This research examines current port operations that use Internet of Things (IoT) technologies for cargo container monitoring and vessel traffic counts. Effective port management is crucial for smooth commodities movement and congestion reduction as global commerce grows. Addressing these issues with IoT solutions is promising. It analyzes cargo container IoT sensors and devices for real-time location, condition, and security monitoring. These IoT-enabled containers provide port status data for better logistical planning and security. IoT devices are used to count and control vessel traffic in the research. Sensors and data analytics at important port locations provide real-time vessel tracking and traffic monitoring. This data improves safety and optimizes vessel traffic flow, lowering congestion and wait times. The pros and downsides of using IoT in port operations include data privacy, security, and infrastructure needs. Smart port technologies may enhance marine efficiency, cost savings, and sustainability. The IoT can revolutionize port operations, notably cargo container monitoring and vessel traffic counts. Port capacity, security, and the environmental and economic viability of worldwide trade may all be improved with the help of the IoT. © 2024 IEEE.

关键词： Internet of things

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Blockchain-Enabled Energy Trading in Microgrids for Sustainable computing Infrastructure 5

Blockchain-Enabled Energy Trading in Microgrids for Sustaina...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Kokila, M.L. Sworna Sunitha, R. Kalyanakumar, P. Raj, J. Relin Francis Krishnan, R. Santhana Gopikumar, S. School of Computing College of Engineering and Technology Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Chennai Kattankulathur India Rajarajeswari College of Engineering Department of Electronics and Communication Engineering Bangalore India Velammal College of Engineering and Technology Department of Information Technology Madurai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Civil Engineering Chennai India

ISBN: (纸本)9798350379945

This research investigates Blockchain-enabled energy trading within microgrids to enhance sustainable computing infrastructure. A novel algorithm, GridCoin, is proposed and evaluated against existing methodologies including Optimal Power Flow (OPF), Microgrid Energy Management System (MEMS), and Hierarchical control Algorithms (HCA). The study employs simulation metrics such as Transaction Throughput, Energy Trading Efficiency, and Transaction Latency to compare the performance of these algorithms. GridCoin demonstrates superior capabilities in optimizing energy trading operations, achieving higher transaction throughput, improved efficiency in energy utilization, and reduced transaction latency. These results highlight the potential of Blockchain technology to revolutionize energy markets by providing secure, transparent, and decentralized transaction mechanisms. Future research directions include enhancing optimization techniques, integrating renewable energy sources, addressing scalability and security challenges, conducting real-world deployments, and analyzing economic and policy implications. This study contributes to advancing sustainable computing infrastructure through innovative Blockchain-based solutions. © 2024 IEEE.

关键词： Blockchain technology energy trading GridCoin algorithm microgrids optimization renewable energy integration sustainable computing

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Automated Pneumonia Classification Using DensePneumoNet in Chest CT Scans 5

Automated Pneumonia Classification Using DensePneumoNet in C...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Nithila, Ezhil E. Bibin Christopher, V. Raj, J. Relin Francis Srinivasan, A. Soundiraraj, N. Krishnan, R. Santhana Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai Avadi India School of Computing College of Engineering and Technology Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Chennai Kattankulathur India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India Velammal College of Engineering and Technology Department of Information Technology Madurai India Psna College of Engineering and Technology Department of Electrical and Electronics Engineering Dindigul India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India

ISBN: (纸本)9798350379945

'DensePneumoNct' is a specialized deep learning algorithm designed for accurate and efficient detection of pneumonia from CT chest images. Leveraging the DenseNet architecture within TensorFlow, this algorithm demonstrates superior performance across critical metrics including accuracy, recall, precision, and F1 score. The implementation utilizes the ImageNet dataset, preprocessed to ensure standardization and resizing, optimizing input uniformity for robust model training. The DenseNet model architecture features dense blocks and transition layers, fostering strong feature propagation and effective downsampling of feature maps. Hyperparameter tuning, including a learning rate of 0.001, a batch size of 64, and training over 100 epochs, enhances model convergence and performance refinement. Training enhancements such as early stopping and learning rate scheduling further stabilize model training and prevent overfitting. Evaluation on a validation set showcases 'DensePneumoNet''s capability to distinguish COVID-19 pneumonia, viral pneumonia, and healthy lung tissues with unparalleled accuracy. Comparative analysis against ResNet-50, Inception-v3, SqueezeNet, and LeNet confirms DensePneumoNet's superiority in all evaluated parameters, affirming its efficacy for critical medical imaging tasks. 'DensePneumoNet' represents a significant advancement in pneumonia detection, poised to enhance diagnostic accuracy and clinical decision-making in medical settings. © 2024 IEEE.

关键词： Medical imaging

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Air Traffic Management and Communication over ATN/IPS for Future Datalink Communication

Air Traffic Management and Communication over ATN/IPS for Fu...

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2025 Integrated Communications, Navigation and Surveillance Conference, ICNS 2025

作者： Aydogan, Emre Ozmen, Sergun Cetek, Fulya Aybek Valdes, Rosa Maria Arnaldo Jurado, Raquel Delgado-Aguilera Fernandez, Angel Ernesto Carmona Miralles, Adrian Martinez Vendruscolo, Tommaso Bonelli, Stefano Delahaye, Daniel Chaimatanan, Supatcha Chen, Feng Hamzaoui, Raouf Eskişehir Technical University Faculty of Aeronautics and Astronautics Air Traffic Control Department Eskişehir Turkey Turkish Airlines Îstanbul Turkey Universidad Politėcnica de Madrid Department of Aerospace Systems Air Transport and Airports Madrid Spain Servicios Aeronáuticos Control y Navegación Madrid Spain Deep Blue srl Rome Italy OPTIM Lab Toulouse France De Montfort University Faculty of Computing Engineering and Media Leicester United Kingdom

ISBN: (纸本)9798331534738

The growing demand for air traffic presents challenges in air traffic management, making seamless gate-to-gate communication essential. Traditional radio frequency communication faces limitations such as weather dependency and frequency restrictions. To address these issues, data link communications have gained importance, using VHF channels, satellite systems, and ATN/IPS-based networks. This study introduces the ATMACA (Air Traffic Management and Communication Over ATN/IPS) protocol, an advanced context management framework for ATN/IPS, designed to enhance aviation communications. ATMACA integrates instant messaging and software-defined nodes to improve connectivity, session continuity, and mobility management across networks and devices. It ensures seamless user interaction, reduces pilot workload, and enhances flight safety through automated Air Traffic control (ATC) sector handoff in controller-Pilot Data Link Communications (CPDLC) and Data Link Initiation Capability (DLIC) applications. Another key innovation of the ATMACA framework is Green Route Operations (GRO), which enables real-time trajectory prediction and optimization. © 2025 IEEE.

关键词： Air traffic control

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Data analysis using neural networks and Kohonen maps in a comparative perspective

Data analysis using neural networks and Kohonen maps in a co...

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2023 International Conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Degtyareva, Ksenia Borodulin, Aleksey Soloveva, Tatiana Nelyub, Vladimir Kukartsev, Vladislav Reshetnev Siberian State University of Science and Technology Department of Systems Analysis and Operations Research Krasnoyarsk Russia Moscow State Technical University Artificial Intelligence Technology Scientific and Education Center Bauman Moscow Russia Reshetnev Siberian State University of Science and Technology Department of Information Economic System Krasnoyarsk Russia Moscow State Technical University Informatics Artificial Intelligence and Control Systems Faculty Bauman Moscow Russia

ISBN: (纸本)9798350319200

This paper discusses two powerful methods of data analysis, neural networks and self-organising Kohonen maps. The main emphasis is on the importance of correct data preparation before analysis. Their impact on the accuracy and quality of research results is analysed. The paper provides deep insight into the effective application of these techniques in various data analysis scenarios. © 2023 IEEE.

关键词： accuracy of analysis data analysis data clustering data preparation neural networks relationships in data self-organising Kohonen maps

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Testing user Attitudes in IoT-load interface Based Healthcare attention management system 4

Testing user Attitudes in IoT-load interface Based Healthcar...

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4th IEEE International Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Tewari, Ramanuj Alsalami, Zaid Alsailawi, H.A. Kirubanantham, P. Dhabalia, Dharmesh Saadoun, Osama Nazim Abdulhussain, Zahraa N. Alwan, Ali Saad Graphic Era Hill University School of Management Uttarakhand Bhimtal India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq University of Kerbala College of Medicine Department of Chemistry and Biochemistry Kerbala56001 Iraq Srm Institute of Science and Technology School of Computing College of Engineering and Technology Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur SRM Nagar Chennai India Vishwakarma Institute of Information Technology Information Technology Pune India Al-kunooze University College Law Department Basra Iraq National University of Science and Technology College of Technical Engineering Dhi Qar64001 Iraq Kut University College Business Administration Department wasit Al kut52001 Iraq

ISBN: (纸本)9798350360165

The study aims to analyze consumer perception toward adopting Internet of Things (IoT) technology in healthcare. In contrast to earlier studies that focused on the technical aspects, the proposed integrated paradigm measures how user trust is affected by the existence of security and privacy concerns, and knowledge of the Internet of Things. The proposed architecture presents a holistic system for health data management that is secure and efficient in modern health systems, designed and developed using four layers: hospital, remote IoT integrated medical device, distributed medical record, and AI-based smart contract. The system is supposed to enhance security of data and efficiency in its management with integration of the blockchain technology and the AI-based intelligence. The hospital layer is similar to the database that stores the data of the patient, and the distributed medical record layer makes the storage of the data and the access from it secure through blockchain. The data transfer of the health parameters of the patient through the IoT-enabled medical node can be done using the blockchain. The Al-based smart contract layer brings in the intelligence of the system for automatic decision-making and proactive breach detection. Evaluation was made on the system's performance under different conditions, such as transaction processing time, average delay, where it demonstrated scalability, reliability, and robustness in the management of health data and hence sounds quite promising for this domain of modern healthcare. © 2024 IEEE.

关键词： Electronic health record

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