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Machine Learning-Enhanced Self-Management for Energy-Effective and Secure Statistics Assortment in Unattended WSNs

SN computer science 2025年第2期6卷 1-10页

作者： Biswas, Preesat Mishra, Aishwarya Dixit, Rinku Sharma Dwivedi, Abhishek Choudhary, Shailee Lohmor Tiwari, Shweta Chakravarthi, M. Ayyappa Electronics & Telecommunications Government Engineering College C. G Jagdalpur India Department of Computer Science & Engineering IES College of Technology M.P Bhopal India Department of Artificial Intelligence and Machine Learning New Delhi Institute of Management Delhi India Department of Data Science and Engineering School of AIML IoT & IS CCE DS and Computer Applications Manipal University Jaipur Jaipur Rajasthan India Department of Computer Science and Engineering Gyan Ganga Institute of Technology and Sciences M.P Jabalpur India Department of CSE-Data Science KKR and KSR Institute of Technology and Sciences Guntur India

Unattended Wireless Sensor Networks (UWSNs) operate without human supervision and have limited resources. In a conventional WSN with a fixed sink for data collection, nodes one hop away from the sink consume more energy, causing a hotspot issue. This leads to network fragmentation and reduced sensing efficiency. To address this, a mobile sink is proposed. This study details the development and implementation of Secure MRL, focusing on legitimate message communication to the mobile sink via convex nodes. By using these convex nodes as data collection points, the mobile sink avoids traversing the entire network. We employ an enhanced system to generate keys and authenticate messages, assessing its resilience against various attacks, including sleep deprivation, snooze, network substitution, and modification. Findings indicate that Secure MRL maintains consistent performance across different node counts and significantly reduces energy consumption by 84%, improving the speed of attack detection. This improvement is achieved by monitoring the digital signature and residual energy of nodes. The proposed SVM-based network training establishes a residual energy cut-off, while convex nodes mitigate synchronization issues among other sensor nodes in Secure MRL. Additionally, convex nodes manage the availability checks for the mobile sink. The proposed approach demonstrates a 92% improvement in packet delivery ratio (PDR) and an 89% reduction in end-to-end delay, highlighting its efficacy in enhancing network performance. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Duty-cycled UWSN MRL Sec-MRL SEC-TMP SVM UWSN

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Search Engine for QnA using Distributed Inverted Index System 3

Search Engine for QnA using Distributed Inverted Index Syste...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Dey, Snehasis Moharana, Bhimasen De, Utpal Chandra Samant, Tapaswini Behera, Trupti Mayee Banerjee, Shobhan College of Engineering Electronics & Telecommunication Engineering Bhubaneswar India Lovely Professional University Department of Computer Science & Engineering Punjab India Kalinga Institute of Industrial Technology School of Computer Applications Bhubaneswar India Kalinga Institute of Industrial Technology School of Electronics Engineering Bhubaneswar India Birla Institute of Technology and Science Department of Engineering Technology Pilani India

ISBN: (纸本)9798350381931

The internet along with its global uses has also evolved as a platform where various people can pose their questions on certain sites and get them answered by others from the same domain. Certain sites like Quora, Reddit, Yahoo Answers, etc. are sites enabling people to enhance their range over the net to find solutions to various issues or answers to various questions. But this leads to redundancy in data & hence increased memory consumption where different users can pose the same question in different ways. The same thing stands for the answers posted by different users for the same question in various ways. In this paper, we have worked on a search engine system for Question & Answers where given a question, we can find similar questions with the same semantic meaning using Elastic Search which uses an inverted index system & looks at various aspects of the formulated problem statement. © 2024 IEEE.

关键词： Search engines

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Enabling Smart Home Energy Management through Gesture-Based Control and IoT Technology

Enabling Smart Home Energy Management through Gesture-Based ...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Rambe, Khairul Hawani Ou, Chia-Ho International Master Program in Information Technology and Applications Sweden National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

The Internet of Things (IoTs) have become ubiquitous in all aspects of public needs today. The application of IoT technology is crucial for promoting energy-saving behavior. This paper presents a control system used for smart home devices based on hand gesture control and Android applications. The hardware design uses the ESP32 microcontroller, which has an in-chip Wi-Fi module, making it very suitable for creating IoT application systems. The software was designed using the Arduino IDE, and the application display design was developed using Kodular Creator, which is used to control the lamps and switches. The experiment results show that the electrical equipment can be activated using the Android application with gesture sensors by waving down, up, left, and right. © 2023 IEEE.

关键词： Internet of things

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P2FLF: Privacy-Preserving Federated Learning Framework Based on Mobile Fog Computing

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第17期17卷 72-81页

作者： Ankayarkanni, B. Pani, Niroj Kumar Anand, M. Malathy, V. Bhupati Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science Engineering and Applications Indira Gandhi Institute of Technology Odisha Sarang India Department of ECE Dr M.G.R Educational and Research Institute Tamil Nadu Chennai India Department of ECE SR University Telangana Warangal India Department of IoT KL Deemed to be University Andhra Pradesh Vaddeswaram Guntur India

Mobile IoT devices provide a lot of data every day, which provides a strong base for machine learning to succeed. However, the stringent privacy demands associated with mobile IoT data pose significant challenges for its implementation in machine learning tasks. In order to address this challenge, we propose privacy-preserving federated learning framework (P2FLF) in a mobile fog computing environment. By employing federated learning, it is possible to bring together numerous dispersed user sets and collectively train models without the need to upload datasets. Federated learning, an approach to distributed machine learning, has garnered significant attention for its ability to enable collaborative model training without the need to share sensitive data. By utilizing fog nodes deployed at the edge of the network, P2FLF ensures that sensitive mobile IoT data remains local and is not transmitted to the central server. The framework integrates privacy-preserving methods, such as differential privacy and encryption, to safeguard the data throughout the learning process. We evaluate the performance and efficacy of P2FLF through experimental simulations and compare it with existing approaches. The results demonstrate that P2FLF strikes a balance between model accuracy and privacy protection while enabling efficient federated learning in mobile IoT environments. © 2023 by the authors of this article. Published under CC-BY.

关键词： Fog computing

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Harnessing the Potential of the Internet of Things: Navigating Choices Between Fog and Cloud Infrastructure in Agriculture 2nd

Harnessing the Potential of the Internet of Things: Navigati...

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2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Singh, Malikhan Arora, Kavita Pathak, Sonal Quraishi, Suhail Javed Singh, Anupam Ather, Danish Computer Science and Engineering Modern Institute of Technology and Research Centre Rajasthan Alwar India School of Computer Applications Manav Rachna International Institute of Research and Studies Haryana Faridabad India Department of Computer Science and Engineering Graphic era Hill University Dehradun India Amity University in Tashkent Tashkent Uzbekistan

ISBN: (纸本)9789819776023

In recent years, the Internet of Things (IoT) has become a pivotal force in transforming various sectors, with agriculture being a prominent beneficiary. The integration of smart devices, sensors, and data-driven decision-making tools has led to the emergence of a more efficient and sustainable farming landscape. Central to this transformation is the decision of where and how to process and store the vast amounts of data generated by these devices. This paper delves into the practical implications of fog and cloud computing systems in the agricultural domain taking Delhi NCR and region as a sample area by considering factors like efficiency, scalability, and real-world challenges faced by farmers. The aim here is to provide a comprehensive guide to stakeholders in making an informed choice between fog and cloud infrastructure for their IoT-enabled agricultural endeavors. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Smart agriculture

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Intelligent Energy Management Energy Storage Systems Using Machine Learning

Intelligent Energy Management Energy Storage Systems Using M...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Govindasamy, Chinnaraj Dayana, T.R Nisha Adkar, Siddhika Dilip Prakash, D. Shyam Gupta, A. Shilpa Trivedi, Sanjeev Kumar Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai602105 India Vels Institute of Science Technology and Advance Studies Department of Computer Science Chennai India School of Computer Science Engineering and Applications D y Patil International University Akurdi India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore India Department of Electrical and Electronics Engineering Aurora's Technological Research Institute Uppal Hyderabad India Khwaja Moinuddin Chishti Language University Faculty of Engineering and Technology Department of Electronics Lucknow India

ISBN: (纸本)9798350375237

A nevertheless-emerging generation called cloud computing permits customers to pay for services on a usage-based foundation. Internet-primarily based IT offerings are supplied through cloud computing, at the same time as virtualization enables the availability of PC sources. The muse of cloud computing is the information center, which is made up of networked computers, cables, electricity components, and different components that host and shop corporate records. With cloud facts centers, high overall performance has continually been the most critical concern, yet it compromises strength utilization. The key hassle is to lessen power consumption at the same time as preserving provider nice and performance a good way to stability device performance and strength intake. A detailed grasp of strength use styles within the cloud environment is needed for our suggested technique. We look at power consumption tendencies and reveal how, through the use of the right optimization standards based on our strength intake models, we can keep more strength in cloud records facilities. All through the prediction section, tablet optimization, which has a 97 percent accuracy rate, permits this era to provide extra correct future price forecasts. © 2024 IEEE.

关键词： Machine learning

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A Hybrid Watermarking Scheme Using DWT and Haar Transform for Image Authentication 3rd

A Hybrid Watermarking Scheme Using DWT and Haar Transform fo...

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3rd International Conference on Advanced Computing and applications, ICACA 2024

作者： Jana, Sachchidananda Pal, Pabitra Mahadani, Asim Kumar Giri, Debasis Department of Computer Science & Applications Prabhat Kumar College Contai West Bengal Purba Medinipur721404 India Department of Computer Applications Maulana Abul Kalam Azad University of Technology West Bengal Nadia741249 India Department of Computer Science and Engineering Bankura Unnayani Institute of Engineering West Bengal Bankura India Department of Information Technology Maulana Abul Kalam Azad University of Technology West Bengal Nadia741249 India

ISBN: (纸本)9789819747986

The safe transfer and preservation of medical images is crucial in the age of digital healthcare. Watermarking medical images is an essential method of adding patient data, hospital logos, and other pertinent information to these images without compromising their confidentiality, integrity, or validity. To overcome the aforementioned difficulties, this abstract offers a unique and reliable medical image watermarking system that makes use of Particle Swarm Optimization (PSO), Discrete Wavelet Transform (DWT), and Singular Value Decomposition (SVD) approaches. There are three main phases to the suggested plan. The medical image is first broken down into its frequency components using DWT, which makes watermark embedding more effective. Subsequently, the PSO method is utilized to maximize the choice of image segments for incorporation, guaranteeing that the watermark remains undetectable and robust against diverse attacks. In the last step, the watermark’s strength is increased by using the SVD approach to embed it in the singular values of certain image blocks. Comprehensive tests are conducted to assess the efficacy of the suggested approach, taking into account performance measures like the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR), as well as resistance against typical assaults such as noise addition, compression, and cropping. The testing findings show that the method effectively embeds the watermark while maintaining image quality and making sure it is robust to attack. The suggested method is appropriate for clinical and telemedicine applications as it also protects the confidentiality and integrity of patient data. By advancing the development of effective and safe medical image watermarking methods, this research helps to protect the privacy and veracity of critical healthcare data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Discrete wavelet transforms

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Pesticide Usage Forecasting for Agriculture using Prophet Model 5

Pesticide Usage Forecasting for Agriculture using Prophet Mo...

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5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Wani, Afshan Hassan Moharana, Bhimasen Samant, Tapaswini De, Utpal Chandra Dey, Snehasis Banerjee, Shobhan Department of Computer Science and Engineering Lovely Professional University Punjab India School of Electronics Engineering Kalinga Institute of Industrial Technology Bhubaneswar India School of Computer Applications Kalinga Institute of Industrial Technology Bhubaneswar India College of Engineering Bhubaneswar India Department of Engineering Technology Birla Institute of Technology and Science Pilani India

ISBN: (纸本)9798350361155

Agriculture plays a vital role in our day-to-day life for the life sustenance of not just human beings but also various domestic and livestock animals. In addition to this, agriculture also contributes significantly to the economy of a country, impacting its growth across the globe. India had always been an agriculture-dominated country before the companies from the West started investing in India. But alongside agriculture come various challenges such as infestation by insects or weeds which eventually lead to the damage of crops and even diseases. But pesticides can even contribute to the contamination of soil, water, and other vegetation in areas where they are been used. In this paper, we have used the Prophet model to study the use of pesticides and analyze the trends of usage of organic pesticides over inorganic pesticides. © 2024 IEEE.

关键词： Pesticides

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Shortest Route ∗ Bidirectional Search Algorithm for Predicting Shortest Routes in Traffic 4

Shortest Route ∗ Bidirectional Search Algorithm for Predict...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Lakshna, A. Gokila, S. Ramesh, K. Hindustan Institute of Technology and Science Department of Computer Applications Chennai India Sri Krishna College of Engineering and Technology Department of Cse Coimbatore India

ISBN: (纸本)9798350300888

Road traffic congestion is a pressing issue that plagues urban areas, causing delays, inefficiency, and environmental problems. Smart traffic management systems aim to tackle this problem by utilizing advanced Shortest route ∗ Bidirectional Search algorithms. The Shortest route ∗ bidirectional search algorithm(SRSBSA) in smart traffic systems is used to efficiently avoid road traffic congestion and find the shortest route to reach the destination. Simultaneously exploring the search space from both the starting point and the destination, the algorithm significantly reduces the computational effort required to find the optimal path. distance, driver behavior, estimated travel considers road, type of holiday, peak hours, tr flow, and road capacities, vehicle characteristics. It considers the characteristic road type, holiday typing one-way streets, turn road capacities, and d limits, to generate accurate and feasible route suggestions to determine the best shortest route. The algorithm leverages heuristic estimates and evaluates various route options to guide drivers toward the shortest route. Implementing the Shortest route ∗ bidirectional Search algorithm in smart traffic produces the result in high accuracy level of 95%. This leads to improved travel time, increased transportation efficiency, and a more sustainable urban environment. © 2023 IEEE.

关键词： Traffic congestion

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A Paradigm Shift in Real-Time Detection: The YOLOv7 Approach to Trainable Freebie Optimization 3

A Paradigm Shift in Real-Time Detection: The YOLOv7 Approach...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Vinitha, A. Jeevitha, S. Kumar, N.B. Mahesh Sathish Kumar, L. Saravanan, D. Karpagam Academy of Higher Education Department of Computer Applications Tamilnadu Coimbatore India Kalasalingam Academy of Research and Education Department of Computer Science and Information Technology Krishnankoil Tamilnadu Virudhunagar India Hindusthan Institute of Technology Computer Science and Engineering Tamil Nadu Coimbatore India Madhya Pradesh Sehore India

ISBN: (纸本)9798331509675

Significant progress has been made in real-time object detection, with YOLOv7 emerging as a state-of-the-art model that achieves the highest levels of accuracy and speed. This study combines Bag-of-Freebies (BoF) strategies with YOLOv7 to improve performance without incurring extra computational expenses. Our tests show that adding BoF preserves real-time inference capabilities while increasing mAP@0.5 by 3.5%. The accuracy and FPS of YOLOv7 with BoF are superior to those of the current YOLO-based models (YOLOv4, YOLOv5, YOLOv6). According to the results, YOLOv7 with BoF sets a new standard for real-time object detection by achieving a mAP@0.5 of 55.3% and 83 FPS on the COCO dataset. © 2025 IEEE.

关键词： Contrastive Learning

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