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Advances in Computation, Communication and Information technology (ICAICCIT), International Conference on

作者： J. Niveditha T. Venkatesh A. Reethika U. Ramya S. Sreejaa V. Vinothini Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Computer Science and Engineering Sri Ranganathar Institute of Engineering and Technology Coimbatore India

ISBN: (数字)9798331541217

ISBN: (纸本)9798331541224

As we are utilizing Conventional vehicles, Electric Vehicles require charging the batteries, so the chargers for batteries are becoming more and more crucial within the automobile industry. While the current chargers mostly rely on bulky and inefficient transformer models, this proposed work aims to explore the integration of Switched-Mode Power Supply (SMPS) technology. The method employed in this work is that replaces the charging based on transformers with SMPS technology, with the goal of improving efficiency, reducing size, and reducing heat generation. The result of the project has a successfully developed battery charger that utilizes SMPS technology. It has achieved increased efficiency, reduced size, and lower heat generation in comparison to traditional models. Furthermore, the revised charger exhibits a simpler and more affordable circuit, catering to a wider consumer base. As a result, this product can be used in both workshops and automobile showrooms with more efficiency at an affordable cost.

关键词： Battery chargers Industries Lead acid batteries Heating systems Switched mode power supplies Transformers Electric vehicles Batteries Automobiles Integrated circuit reliability

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A Success of Bulk Queueing Service of Expected Waiting Time with Regular Service, Repair, Idle and Single Server Vacation in Real-life Data analysis 7

A Success of Bulk Queueing Service of Expected Waiting Time ...

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7th IET Smart Cities Symposium, SCS 2023

作者： Shakila Devi, G.T. Geetha Rani, K. Rajasekar, B. Sathish Kumar, P.J. Surendran, R. Department of Functional Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Bangalore India Department of Electronics and Communication Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (纸本)9781839539831

This paper deals the four-compartment model for the success of bulk queueing service with regular service;repair, Idle and single sever vacation. We calculated the bulk expected waiting time with the help of bulk queue size, success of bulk service;bulk Intensity, Idle and single server vacation and numerical results by using MATLAB. It helps the real-life data analysis for probabilistic approach. © The Institution of engineering & technology 2023.

关键词： Repair

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Landslide Semantic Segmentation Using Satellite Imagery 19

Landslide Semantic Segmentation Using Satellite Imagery

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19th International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON 2022

作者： Achariyaviriya, Witthawin Kondo, Toshiaki Karnjana, Jessada Nishio, Takayuki Sirindhorn International Institute of Technology School of ICT Thailand National Electronics and Computer Technology Center NSTDA Thailand Tokyo Institute of Technology Department of Information and Communication Engineering Japan

ISBN: (纸本)9781665485845

This work aims to improve the accuracy of landslide detection with single satellite imagery by using slope factor extraction and normalized difference vegetation index (NDVI) extraction and by combining three semantic segmentation models based on a convolutional neural network with a decision tree. The proposed method uses three semantic segmentation models with a decision tree. The first model is trained by a training set of color images. The second model is trained by a training set of slope factor images. The third model is trained by a training set of NDVI images. The slope factor and NDVI are extracted from color images that contain red, green, and blue bands. The results from three models are used to generate features for training the classification decision tree. Evaluation metrics (precision, recall, and F2 score) can be improved by using slope factor and NDVI. In combining three models, the F1 score and F2 score are increased more than using single of color images 16.71% and 24.15%, respectively. Moreover, the slope factor detection model and NDVI detection model can support some areas that color image detection model cannot detect. © 2022 IEEE.

关键词： Satellite imagery

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Multi-Sensor Data Fusion for Detection of Sensor Drifts in a Landslide Monitoring System 7

Multi-Sensor Data Fusion for Detection of Sensor Drifts in a...

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7th International Conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section Conference on Electrical, electronics, computer and Telecommunications engineering, NCON 2022

作者： Smunyahirun, Nathnaree Karnjana, Jessada Laitrakun, Seksan Nishio, Takayuki Deepaisarn, Somrudee Sirindhorn International Institute of Technology School of ICT Thailand NSTDA National Electronics and Computer Technology Center Thailand Tokyo Institute of Technology Department of Information and Communications Engineering Japan

ISBN: (纸本)9781665495103

This paper aims to extend the lifetime of polymer dielectric-based humidity sensors used in landslide monitoring systems by mathematically adjusting the sensor's drifting value as time passes. Therefore, a strategy based on nested Kalman filters, cosine similarity, and Euclidean distance was proposed in this paper. An outer Kalman filter is used top redict humidity values, with the prediction based on an inner Kalman filter that fuses data from surrounding sensors. To adjust the process noise covariance of the nested Kalman filter, cosine similarity and Euclidean distance are used. When the sensor is in normal conditions, the process noise covariance remains constant;however, when the sensor is drifting, the process noise covariance changes depending on the angle and distance between the value from surrounding sensors and the drift. The proposed method could reduce the drifting value error by 14.85 percent, according to the experimental results. © 2022 IEEE.

关键词： Kalman filters

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Development and Implementation of a Smart Blind Stick using IoT

Development and Implementation of a Smart Blind Stick using ...

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Pervasive Computing and Social Networking (ICPCSN), International Conference on

作者： Dhamodharan Srinivasan Dharshana M Lavanya V Sanjith S Kaviyarasu M Karthik. S Computer and Communication Engineering Sri Eshwar College of Engineering Coimbatore India Electronics and Communication Engineering SRM Madurai College for Engineering and Technology Tamil Nadu India

ISBN: (数字)9798331535193

ISBN: (纸本)9798331535209

The Smart Blind Stick is a advanced device aimed at improving mobility and safety for people with visual impairments. An Arduino Uno microcontroller integrates multiple sensors and communication modules to provide real-time assistance. Ultrasonic sensors detect obstacles and activate an LED output, buzzer, and haptic feedback motor to alert the user through visual, auditory, and vibrational cues. Equipped with a GPS module for tracking location, as well as Wi-Fi and GSM modules for communication, emergency alerts can be sent to caregivers or emergency services. An efficient and stable operation provided by a regulated power supply makes the device lightweight, portable, and easy to use. By providing a dependable and efficient navigation tool for those with visual impairments, this seamless merging of sensor technology, haptic feedback, and connectivity boosts user autonomy.

关键词： GSM Visualization Social networking (online) Visual impairment Acoustics Real-time systems Haptic interfaces Intelligent sensors Wireless fidelity Global Positioning System

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A Probabilistic Constellation Shaping Scheme for Molecular Communications 8

A Probabilistic Constellation Shaping Scheme for Molecular C...

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8th International Conference on computer and Communication Systems, ICCCS 2023

作者： Tang, Yuankun Ji, Fei Wen, Miaowen Wang, Qianqian Chae, Chan-Byoung Yang, Lie-Liang School of Electronic and Information Engineering South China University of Technology China Guangdong Provincial Key Laboratory of Short-Range Wireless Detection and Communication China College of Computer Science and Engineering Northwest Normal University China School of Integrated Technology Yonsei University Korea Republic of School of Electronics and Computer Science University of Southampton United Kingdom

ISBN: (纸本)9781665456128

Molecular communication (MC) conveys information via chemical signals between nanomachines, which lays the foundation for the Internet of Bio-Nano Things. Based on the fact that probabilistic constellation shaping (PCS) enables reliable communication by improving energy efficiency, in this paper, we propose molecular shell mapping (MSM) to implement PCS for MC systems. The MSM method employs the concentration se-quences with the lowest sum sequence weight to construct energy-efficient signal constellations, and designs a sorting principle for sequences with the same sequence weight to mitigate inter-symbol interference (ISI). We design a Genie-aided maximum-likelihood (ML) detector and a realistic ML detector to leverage the constructive effect of ISI from the current concentration sequence, and derive their achievable rates. Numerical simulation results confirm that the shaped signaling using the MSM method is more energy-efficient than the equiprobable signaling, achieving an up to 1.5 dB gain at an ultra-short blocklength. © 2023 IEEE.

关键词： Numerical methods

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Leveraging Machine Learning for Constructing Robust Automated Real-Time Data Analysis Systems

Leveraging Machine Learning for Constructing Robust Automate...

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2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario, ICPSITIAGS 2023

作者： Mishra, Awakash Mukuntharaj, C. Sathi, G. Dhabliya, Dharmesh Kharbas, Vikash Kumar Muthukumar, B. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Karpagam College of Engineering Department of Electronics and Communication Engineering Coimbatore641032 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Animation and Virtual Reality Karnataka Bangalore India

ISBN: (纸本)9798350329773

This paper provides a technique to leverage system-study strategies to develop robust automatic real-time information evaluation structures. In particular, it covers the usage of supervised and reinforcement learning to pressure the strong automated characteristic engineering of a massive variety of data analytics tasks, from time collection forecasting to anomaly detection. The paper additionally proposes an architecture that applies deep knowledge of algorithms to reap statistics from uncooked and aggregated statistics streams. The proposed architecture improves upon current fashions by introducing a hierarchical statistics shape to constitute the enter information, supervised gaining knowledge of strategies to initialize the version, and reinforcement learning to refine the styles based totally on the statistics move's dynamics. Checks conducted on a public dataset exhibit the effectiveness of the proposed framework. This method has potential applications across numerous domains, such as financial services, telecoms, and analytics inside the net of things. © 2023 IEEE.

关键词： Reinforcement learning

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B Smart Technologies in engineering Applications of Cyber Physical System in Healthcare: Sensing, Imaging, Computing and Networking

Recent Advances in Computer Science and Communications

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Recent Advances in computer Science and Communications 2021年第1期14卷 225-226页

作者： Kumar, Rajiv Singh, Pradeep Kumar Sharma, Ashutosh Department of Electronics and Communication Engineering Jaypee University of Information Technology India Department of Computer Science & Engineering ABES Engineering College Uttar Pradesh Ghaziabad India Institute of Computer Technology and Information Security Southern Federal University Russia

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AI-Enhanced Intelligent Control Systems for Electric Vehicles 9

AI-Enhanced Intelligent Control Systems for Electric Vehicle...

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9th International Conference on Science, technology, engineering and Mathematics, ICONSTEM 2024

作者： Tagesse, Tamirat Arulkumar, S. Saravanan, A. Vibhakar, Chirag Shobana, D. Chokkalingam, Arun Wachemo University Department of Electrical And Computer Engineering Ethiopia S.A Engineering College Department of Master of Business Administration Chennai Tamil Nadu Thiruverkadu600077 India Department of Electrical Engineering Gujarat Power Engineering &. Research Institute Mevad - Mehsana Gujarat Technological University Gujarat Ahmedabad382710 India Panimalar Engineering College Department of Electrical And Electronics Engineering Tamil Nadu Chennai600125 India R.M.K. College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

A comprehensive overview of the operation of artificial intelligence(AI) in enhancing intelligent control systems for electric vehicles(EVs). As the automotive assiduity transitions towards electrification, the development of advanced control systems becomes decreasingly pivotal to optimize the performance, effectiveness, and safety of EVs. AI ways, including machine literacy, deep literacy, and underpinning literacy, offer promising results to address the complex dynamics and misgivings essential in EV operation. This review explores the integration of AI algorithms into colorful aspects of EV control systems, similar as powertrain operation, battery operation, energy operation, and vehicle autonomy. Case studies and experimental results are presented to demonstrate the effectiveness and benefits of AI- enhanced control systems in perfecting EV performance, extending battery life, and enhancing overall driving experience. likewise, challenges, openings, and unborn directions for exploration and development in this field are bandied to pave the way for the wide relinquishment of AI- driven intelligent control systems in the EV assiduity. © 2024 IEEE.

关键词： Control theory

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Signal Quality Evaluation and Processing for QRS Detection in ECG based Smart Healthcare Systems

Signal Quality Evaluation and Processing for QRS Detection i...

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2022 IEEE International Conference on Knowledge engineering and Communication Systems, ICKES 2022

作者： Singh, Devendra Akram, ShaikVaseem Sivakumar, T. Prakash, U. Loyola Jasmine, J. Chaithra, K.N. Uttaranchal University Dehradun India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Sri Eshwar College of Engineering Department of Information Technology Coimbatore India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9781665456371

The next-generation wearable electrocardiogram (ECG) equipment requires signal processing with low battery usage in order to transmit signals when harmful rhythms are recognized and to capture signals when anomalous rhythms are discovered. The visual deflections that are frequently visible on an ECG make up the QRS complex. This research suggests a real-time QRS recognition and R point detection system that is extremely accurate and simple. The recommended ECG signal modification eliminates baseline wandering while also enhancing QRS intervals and controlling P and T waves. In this work, the peaks and valleys of the converted signal were used to calculate the fiducial point for the QR. The R point could then be determined using four QRS waveform templates, and the initial categorization of cardiac rhythms could be completed simultaneously. On two benchmark datasets, the proposed method's effectiveness is shown. Positive prediction (+P) and detected sensitivity (Se) values for QRS are 99.82 and 99.81 percent, respectively, according to the standard. The outcome demonstrates that the method has a low processing complexity and that real-time software may be successfully executed on both an embedded system and a mobile device. © 2022 IEEE.

关键词： Electrocardiograms

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