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Challenges in Cyber Physical Social Systems and Internet of Things 5

Challenges in Cyber Physical Social Systems and Internet of ...

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

作者： Revathi, S. Raja, J. Mohanraj, M. Malathi, K. Mallala, balasubbareddy Vidhya, R.G. B.S. Abdur Rahman Crescent Institute of Science and Technology Department of Computer Science Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai India Sri Eshwar college of engineering Department of Computer Science and Business Systems Coimbatore India Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Hkbk College of Engineering Department of Ece Bangalore India

ISBN: (纸本)9798331504403

This research analyses the complex dynamics of Cyber-Physical-Social Systems (CPSS), encompassing cyber-physical systems, cybersecurity, the Internet of Things (IoT), and social media. by exploring the interactions among these elements, this study analyses the vulnerabilities, risks, and potential benefits within the CPSS framework. This research study analyses the evolving landscape of cybersecurity by considering various aspects such as data integrity, privacy in the IoT era, and the influence of social media on user behaviour and influence dynamics. The study also introduces innovative strategies to enhance CPSS resilience, including methods to mitigate cyber threats and enhance overall system integrity. Additionally, we investigate how social media shapes CPSS behaviours, offering valuable insights into influence dynamics. This research advances the comprehensive understanding of CPSS to support future studies and advancements in the protection and improvement of interconnected systems. © 2024 IEEE.

关键词： Cyber-Physical Systems Cyber-Physical-Social Systems (CPSS) Cybersecurity Internet of Things (IoT) Social Media

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An electronic warfare approach for deploying a software-based Wi-Fi jammer

An electronic warfare approach for deploying a software-base...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Keshav Kaushik Rahul Negi Prabhav Dev School of Computer Science University of Petroleum and Energy Studies Dehradun India B.Tech Computer Science and Engineering University of Petroleum and Energy Studies Dehradun India

Some prominent instances have been centered on electronic warfare. For example, the American military has made significant investments in automation through UAV programs, only for competitors like the Iranians to create strategies to interfere with these systems. Iran managed to capture a top-secret U.S. surveil-lance drone by fooling it into descending in the incorrect place by jamming its control signals and providing it with bogus GPS data. In this paper, the authors have focused on the electronic warfare approach for deploying a software-based Wi-Fi jammer. The software-based Wi-Fi jammer can disconnect the targets using the DoS pursuit mode. The paper describes the unique methodology of how software can also be used for jamming wireless signals.

关键词： Performance evaluation Wireless networks Poles and towers Switches Virtual machining Software Security

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A Recommendation System for Crop Prediction Under Diverse Weather Conditions

A Recommendation System for Crop Prediction Under Diverse We...

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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： P ShunmugaLakshmi V Ram Kishore Pillai Pratham Ramachandran S Santhi S Kalaiselvi B.Tech Information Technology National Engineering College Kovilpatti Tamil Nadu Dept. of Information Technology National Engineering College Kovilpatti Tamil Nadu Dept. of Computer Science and Engineering National Engineering College Kovilpatti Tamil Nadu

In order to develop strategic initiatives in agricultural belonging for trading protocol and tripling countrymen earnings, early and accurate agricultural output estimation is pivotal in computable and commercial decision at the territory plane. Crop production forecasting, which is done to foresee a greater crop output, is the impressive difficulty in the agronomic division. To help farmers increase agricultural yield, this study has collected and evaluated data on N, P, K, temperature, humidity, ph, rainfall and soil_moisture. The superior values of this work are to recommend the crop to cultivate, suggest the appropriate fertilizers to use and predict the disease of a crop. A python environment is used to perform initial preprocessing on the data. KNN classification is used for developing the recommendation system. The link between the count, nutrients, temperature, humidity, pH, rainfall, and crop, are visualized using bar graphs and scatter plots. The tensor and torch were used to forecast crop disease and also to suggest appropriate fertilizer based on the data. The application was developed using Python Flask. This Classification was compared with other algorithms such as SVM, DT , RF and K-means.

关键词： Support vector machines Temperature sensors Linear regression Crops Humidity Prediction algorithms Classification algorithms

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Cloud Computing-Enhanced and Raspberry Pi-powered Solution for Remote Ear, Nose, and Throat Consultations with AI-Driven Diagnostics 5

Cloud Computing-Enhanced and Raspberry Pi-powered Solution f...

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5th IEEE International Conference for Emerging technology, INCET 2024

作者： Giriprasad, S. Karpagam, T. Nalini, V. Mishra, Nilamadhab Mohankumar, N. Malathi, N. Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai India Department of Artificial Intelligence and Data Science R.M.K College of Engineering and Technology Tamil Nadu Chennai India Department of Mathematics Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Tamil Nadu Chennai India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Department of Electronics and Communication Engineering B.V. Raju Institute of Technology Telangana India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350361155

The cutting-edge telemedicine program presents a game-changing alternative for patients seeking ENT (ear, nose, and throat) consultations from a distant location. Utilizing the capabilities of Raspberry Pi devices, powerful artificial intelligence, and cloud computing, the system allows otoscopic tests to be performed without interruption while securely transmitting data to the cloud. On a web-based platform, interactive patient-professional consultations are made possible via real-time communication, which is made possible by WebRTC. Cloud services are very important because of their ability to provide scalable storage as well as AI-driven diagnostics for accurate evaluations. The system complies with the requirements for healthcare compliance, emphasizes security and privacy, and features encryption from beginning to finish. This integrated approach promises scalability, reliability, and advanced diagnostic capabilities, and it reshapes the landscape of remote ENT care with accessible and technologically advanced healthcare solutions. With a user-friendly interface for patients and a cloud-hosted application for healthcare professionals, this integrated approach provides patients with advanced healthcare solutions. © 2024 IEEE.

关键词： Artificial intelligence

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Real-Time Video Enhancement with Spatio-Temporal Attention via Deep Convolutional Neural Networks 3rd

Real-Time Video Enhancement with Spatio-Temporal Attention v...

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3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Maria, Anto bennet balasubramanian, Swaminathan Vijayan, Rajmohan Sonthi, Vijaya Krishna Ramakrishnan, Jayapratha Manogaran, Umamaheswari Sengan, Sudhakar Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai600062 India Karnataka Bengaluru560069 India Tamil Nadu Chennai602107 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522502 India Department of Information Technology V.S.B. College of Engineering Technical Campus Tamil Nadu Coimbatore642109 India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627451 India

ISBN: (纸本)9789819783540

The realm of video content has witnessed exponential growth, and alongside it emerges the challenge of enhancing video quality efficiently. Traditional techniques, although valuable, often fall short of addressing the intricate details and temporal consistencies required for high-quality video upscaling. Moreover, real-time processing demands methods ensuring accuracy and swift computational speeds. Addressing these challenges, this paper introduces the STA-DCNN. This innovative architecture is rooted in combining spatial and temporal attention mechanisms to produce superior video super-resolution. The Spatio-Temporal Attention Module (STAM) acts as a cornerstone, singling out essential features across frames, while the Deep Convolutional backbone (DCb) intensifies these frames, capitalizing on attention-informed features. Furthermore, the Temporal Memory Unit (TMU) preserves crucial aspects from preceding frames, guaranteeing a seamless video rendition. Empirical tests confirm that STA-DCNN notably surpasses its counterparts, offering an ideal balance of quality and real-time processing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Spatio-temporal data

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IOT and AI-based Energy Monitoring and Control System for NZEb

IOT and AI-based Energy Monitoring and Control System for NZ...

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Advances in Science and engineering technology International Conferences (ASET)

作者： Zaher Ahmed Altaf Ahmed Mir Sihab bin Islam Ravishankar Dudhe bhakti More Mirza Azmat baig B.Tech Electrical and Electronics Engineering Manipal Academy of Higher Education Dubai UAE School of Design & Architecture Manipal Academy of Higher Education Dubai UAE Three Phase Technical Services LLC Dubai UAE

Climate change and global warming are rapidly intensifying, and one of the biggest contributors is the construction sector. According to World Economic Forum, buildings contribute 40% of greenhouse gas emissions. The study demonstrates the role of the Internet of Things (IoT) and Artificial Intelligence (AI) in the monitoring of a net zero energy building to understand energy savings and methods to combat usage. The study is a case study of a smart and sustainable real-life project built and discusses how tools and technologies can be adapted for monitoring energy consumption in buildings.

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Novel VPDU based framework in V2X communication for Internet of vehicles (IoV) and performance evaluation of VAN in urban scenario 5

Novel VPDU based framework in V2X communication for Internet...

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5th International Conference on Communication and electronics Systems, ICCES 2020

作者： Mishra, Ayaskanta Chaki, Soubhik Sadhukhan, Sukanya Sinha, Sounak Students B.Tech [Electronics & Telecommunication Engineering School of Electronics Engineering Kalinga Institute of Industrial Technology Bhubaneswar751024 India

ISBN: (纸本)9781728153711

Automobile industry is rapidly growing with new technologies. One of such prominent technologies is communication and network connectivity. New era smart vehicles are coming equipped with network adaptors for data connectivity. Modern smart vehicles are aided with hundreds or sensors and manufactures are working on making all sensors and driving statistics to make available to centralized cloud servers for different applications using IoT and cloud technologies making Internet of Vehicles (IoV). Even manufactures are working on some advance features like actuator control and vehicle control and telemetry using data network infrastructure. This work is focused on a proposed novel vehicular protocol data unit (VPDU) and its complete layered network stack implementation framework for vehicle to everythi ng (V2X) communication in an urban scenario. For validation of network framework and evaluation of performance matrices, the simulated vehicular area network (VAN) is proposed in an urban scenario using complete network stack and terrain data in QualNet® simulator. Two industry standard MAC protocols as IEEE 802.11a and 802.11p. AODV, bellman-Ford and OS PFv2 are used as routing protocols to analyze the network performance for all test cases. IEEE 802.11p MAC shows significant performance improvements from 802.11a counterparts with the proposed novel VPDU in a typical urban VAN scenario. The IEEE 802.11p MAC outperforms 802.11a with 11% less overall End-to-End delay, 29% overall less average jitter and overall 127% increase in packet delivery ratio (PDR). AODV routing protocol performs the best with minimum latency and packet error by improving PDR. The detailed performance analysis is presented in the scope of the paper. © 2020 IEEE.

关键词： Network layers

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DeepMind Trainer: Harnessing Cognitive Neural Networks on Raspberry Pi for Advanced Cognitive Enhancement Games 2

DeepMind Trainer: Harnessing Cognitive Neural Networks on Ra...

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2nd International Conference on Advancement in Computation and computer technologies, InCACCT 2024

作者： Abirami, P. Antony Joseph Rajan, D. Vivekanandan, T. Saillaja, V. Mohankumar, N. Rajmohan, M. Velammal Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Sakunthala Engineering College Vel Tech Multi Tech Dr Rangarajan Dr Department of Mathematics Tamil Nadu Chennai India SRM Institute of Science and Technology Faculty of Management Studies Tamil Nadu Kattankulathur Chennai India B.V. Raju Institute of Technology Department of Electronics and Communication Engineering Telangana India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350371314

The presentation summarizes a groundbreaking cognitive training program designed specifically for those who suffer from cognitive impairments or neurodevelopmental abnormalities. The work creates a dynamic platform for immersive and adaptable cognitive training games by combining cutting-edge Convolutional Neural Networks (CNNs) with Raspberry Pi technology. Memory, focus, and ability to think creatively are all qualities directly targeted by these games. The CNN model, trained on a broad dataset, interprets real-time user inputs, delivering quick feedback and altering game complexity depending on an individual's performance. The incorporation of Raspberry Pi guarantees a solution that is both affordable and easily accessible. The capacity of the system to redefine cognitive rehabilitation by providing a solution that is individualizable, interactive, and broadly deployable is the potential source of the system's influence. The goal of the work is to make a substantial contribution to the field, which will eventually be to the advantage of users, caregivers, and healthcare professionals and ultimately improve the cognitive well-being of those coping with cognitive issues. © 2024 IEEE.

关键词： Convolutional neural networks

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Comparative Analysis of ResNet, EfficientNet, and MobileNetV2 for Detecting Skin Conditions in Deep Learning Models

Comparative Analysis of ResNet, EfficientNet, and MobileNetV...

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： M. Rajkumar Shreenath Raghunath Siriyala Ananya Sharma D. Naga Sujith Kumar Department of Smart Computing School of Information Technology & Engineering Vellore Institute of Technology VIT University Vellore Campus Tamil Nadu India B.Tech-Information Technology School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology VIT University Vellore Campus Tamil Nadu India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

Comparing the effectiveness of Skin Condition Detection using ResNet, EfficientNet and MobileNetV2 deep learning models. The 3 skin conditions that have been considered are Acrochordon, Lichenoid Keratosis and Vascular Lesions. The ResNet Model, EfficientNet Model and MobileNetV2 Model have been assessed against one another. ResNet and EfficientNet both predicted the skin condition with an accuracy of 92.1875% which is greater than MobileNetV2, which predicted the skin condition with 90.625% accuracy. Through this research, it has been concluded that ResNet and EfficientNet are significantly better than MobileNetV2 in terms of training models to accurately detect skin conditions.

关键词： Deep learning Training Analytical models Accuracy Quantization (signal) Green communications Skin Reliability Lesions Tuning

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Introduction and Development of Cyber Physical Systems in Smart Grid with blockchain technology to Enhance Sustainability 2

Introduction and Development of Cyber Physical Systems in Sm...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Valarmathi, P. Manoj, G. Das, Sandip Kumar Oommen, Sujo Tiwari, Mohit B. S Abdur Rahman Crescent Institute Department of Computer Science & Engineering Tamil Nadu India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Management Studies Tamilnadu Chennai India School of Electrical Engineering Odisha Bhubaneswar751024 India Reva University School of Electrical and Electronics Engineering Karnataka Bangalore560064 India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350325799

The need for increased sustainability and efficiency in the energy industry has led to a major increase in interest in the development of cyber-physical systems (CPS) in the smart grid domain in recent years. In the context of the smart grid, the term "CPS"refers to a network of physical objects, sensors, and communication systems that are interconnected and allow for the smooth exchange of data and control signals to optimize the production, distribution, and use of electricity. Demand response, energy management, and grid optimization are just a few of the smart grid applications that can be successfully implemented by utilizing CPS's capabilities. On the other side, blockchain technology provides a decentralized and secure framework for logging and validating transactions among numerous organizations. Since it is distributed, there is no need for middlemen, transparency is improved, and data integrity and immutability are all guaranteed. These qualities make blockchain an excellent choice for tackling the issues that the smart grid is facing, such as data privacy, security, and stakeholder confidence. There are many advantages to integrating blockchain and CPS in the smart grid. First and foremost, a decentralized and democratized energy market is made possible by blockchain, which enables safe and effective peer-to-peer energy trade among prosumers. This increases sustainability by encouraging the use of renewable energy sources and reducing dependency on centralized power generation. In conclusion, there is enormous potential for improving sustainability through the smart grid's integration of blockchain technology with cyber-physical systems. © 2023 IEEE.

关键词： Cyber Physical System

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