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Data Processing and Pattern Recognition for Electronic Nose 3

Data Processing and Pattern Recognition for Electronic Nose

引用

3rd International conference on electronics and Renewable systems, ICEARS 2025

作者： Raymond, David Chaudhri, Shivnath Shaikh, Kahkasha Datta Meghe Institute of Higher Education and Research Faculty of Enfineering and Technology Department of Computer Science and Medical Engineering Wardha India Datta Meghe Institute of Higher Education and Research Faculty of Enfineering and Technology Depertment of Computer Science and Design Wardha India

ISBN: (纸本)9798331509675

Electronic nose (e-nose) technology has become a powerful tool for identifying and evaluating complex scents in a variety of contexts, such as environmental monitoring, medical diagnostics, and food quality control. This review study looks at how important pattern recognition and data processing are to improving e-nose system performance. This study covered challenges, including data complexity, cross-sensitivity and interference, sensor drift, and a lack of standardization. The article covers several future directions, such as the use of artificial intelligence (AI) and machine learning to advance pattern recognition and predictive analytics, integration with the Internet of Things (IoT) and big data for real-time monitoring, and advancements in sensor technology for improved sensitivity and *** research work is underway towards the development of low power flexible sensors, improved multi sensor fusion Methodologies, smart adaptive algorithms, Application for personalized health monitoring and diagnostics as well to make it green technologies. To move forward with emerging technologies and for e-nose technology to be applicable, it will have to overcome these weaknesses. © 2025 IEEE.

关键词： Electronic nose

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A Scalable and Secure Facial Recognition Attendance system Leveraging CNN Algorithms for Real-Time Accuracy and Efficiency

A Scalable and Secure Facial Recognition Attendance System L...

引用

2025 IEEE International Students' conference on Electrical, electronics and Computer Science, SCEECS 2025

作者： Kumar, Aakash Sharma, Jiya Renjith, P.N. Vellore Institute of Technology School of Computer Science and Engineering India

ISBN: (纸本)9798331529833

The facial recognition attendance system represents a modern approach to attendance tracking, designed to improve efficiency, accuracy, and security in various organizational settings. Advanced biometric technologies are leveraged to capture and encode facial features, creating unique digital identifiers for each individual. The methodology employs cutting-edge facial recognition algorithms powered by convolutional neural networks (CNNs) with a 99.5% recognition accuracy rate. These algorithms extract and encode facial vectors with sub-millisecond latency, which are then compared in real-time against a secure, encrypted database of preregistered individuals. Upon a successful match, the system automatically records the attendance, ensuring an accurate and efficient process. With an intuitive web interface built on ReactJS and a backend supported by *** and MongoDB, the system provides seamless access to attendance records and administrative functionalities. The entire attendance recording process is optimized for speed, typically completing within two seconds per individual. Additionally, advanced anti-spoofing measures and integration support with existing HR management systems redefine traditional attendance management practices with a scalable, robust, and secure solution. (Abstract) © 2025 IEEE.

关键词： Efficiency

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Real-Time Gender Classification Using MiniXception and Hand Gesture Detection Using MediaPipe Framework

Real-Time Gender Classification Using MiniXception and Hand ...

引用

2025 IEEE International conference on Computational, Communication and Information technology, ICCCIT 2025

作者： Kulkarni, Manas Girish Aute, Revati Tushar Desai, Rajlakshmi Nilesh Deshpande, Atharva Vishwas Pandit, Dipti Pratik Vishwakarma Institute of Information Technology Dept. of Electronics & Telecommunications Pune India

ISBN: (纸本)9798331512965

In human-computer interaction, gender classification and hand gesture recognition are essential technologies. This paper presents a real-time system that integrates gender prediction and face and hand gesture detection, utilising the Mini Xception model and MediaPipe framework. We address the requirements for efficient real-time operation by utilizing frame-skipping mechanisms in our work. The system comprises video capture with OpenCV, model integration using TensorFlow, and efficient data handling with NumPy. Extensive testing has proven its generalization to diverse settings and excellent performance, with 84% accuracy for both tasks, capable of real-time processing. © 2025 IEEE.

关键词： Interactive computer systems

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Enhancing Renewable Energy integration: An Analysis of Bidirectional Converters And Multilevel Inverter Technologies

Enhancing Renewable Energy Integration: An Analysis of Bidir...

引用

2025 IEEE International Students' conference on Electrical, electronics and Computer Science, SCEECS 2025

作者： Allabakshu, Shaik Venkatesh, P.M. Vignan's Foundation for Science Technology & Research Department of Eee Guntur India

ISBN: (纸本)9798331529833

The need to mitigate resource depletion and the adverse environmental consequences associated with fossil fuels is driving the world's growing reliance on renewable energy sources like wind and solar. However, because energy supply is inherently unpredictable, integrating renewables presents problems for system stability and power quality. In order to control energy flow, maintain grid stability, and enable the integration of renewable energy sources at a lower cost, power electronic converters - particularly switched-mode power converters - are essential in tackling these issues. This paper offers a thorough analysis of several converter topologies, such as multilevel inverters, which maximize AC power supply with the least amount of harmonic distortion, and bidirectional DC-DC converters, which control bidirectional power flow for energy storage. It focusses on different multilevel inverter types, such as neutral-point-clamped, flying capacitor, and cascaded H-bridge designs, and converter classes, such as non-isolated and isolated bidirectional DC-DC converters. A Single stage power conversion system named Dual leg DC-AC converter is also explored. Furthermore, innovative semiconductor technologies like GaN and SiC as well as control strategies are examined to improve reliability, efficiency, and power density. By supporting the design of high-performance power converters, this study hopes to contribute to the development of robust and sustainable energy systems in the future. © 2025 IEEE.

关键词： Dual Leg Converter Multilevel Inverters Power Electronic Converters Renewable Energy Sources

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Hive Destruction Protocol: An Automated Defense system Utilizing YOLO Human Recognition and Real-Time GPS Tracking 3

Hive Destruction Protocol: An Automated Defense System Utili...

引用

3rd International conference on Intelligent and Innovative Technologies in Computing, Electrical and electronics, IITCEE 2025

作者： Vyshak, T.M. Gaayana, G.R. Sarala, T. Dept. of Electronics and Communication Engineering Bnm Institute of Technology Affiliated to Vtu Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

The Hive Destruction Protocol (HDP) introduces a cutting-edge automated border defense system that enhances security operations through advanced human recognition using YOLO, precise GPS tracking, and coordinated drone responses. Soldiers are equipped with camera-integrated spectacles that facilitate the rapid identification of enemy targets via visual cues and hand gestures. Upon confirming a target, the system transmits accurate GPS coordinates in real time to autonomous drones, which are deployed to neutralize threats from multiple angles, creating confusion and minimizing detection risk. To ensure reliability and real-time processing in dynamic environments, HDP employs optimized communication protocols for secure data exchange between ground personnel and drones, allowing for seamless coordination among multiple units, each capable of independently engaging identified threats based on shared GPS data. The integration of machine learning algorithms improves the system even more flexible to changing field conditions, improving detection accuracy and robustness under various environmental constraints. Overall, the Hive Destruction Protocol represents a forward-thinking solution for border defense, leveraging artificial intelligence and automation to provide proactive and responsive capabilities in critical security applications. © 2025 IEEE.

关键词： Target drones

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Smart Wireless EV Charging Station Using Raspberry Pi and Web-Based Monitoring

Smart Wireless EV Charging Station Using Raspberry Pi and We...

引用

2025 International conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Kabilamani, P. Karthikeyan, R. Praanesh, J. Karthik Raja, R. Srm Institute of Science and Technology Faculty of Engineering Department of Electronics and Communication Engineering Vadapalani Campus Chennai India

ISBN: (纸本)9798331509828

The increasing prevalence of electric vehicles (EVs) highlights the need to create effective and accessible charging systems. However, wireless charging methods for electric vehicles currently face several obstacles. This encompasses challenges such as decreased efficiency resulting from energy losses, difficulties in coil alignment while charging, and the necessity for sophisticated safety devices to prevent overheating, overcurrent, and voltage swings. Furthermore, numerous current systems do not incorporate Internet of Things (IoT) technology, which is vital for real-time monitoring and predictive maintenance to improve user experience and system dependability. This study presents a smart wireless electric vehicle charging system that integrates low voltage inductive power transmission with Internet of Things capabilities to address these difficulties. The system facilitates real-time monitoring of critical parameters, including voltage, current, and temperature, through the integration of the IoT. The aggregated data are accessible via a simple web-based interface, enabling customers to remotely supervise and manage the charging process. In addition, the system has safety mechanisms that automatically identify and respond to irregular charging circumstances, guaranteeing efficient and secure functionality. So,the primary objective of this project is to demonstrate the feasibility of integrating wireless charging with IoT to improve the efficiency, convenience, and safety of EV infrastructure. Through this approach, the system aims to provide a seamless, automated, and user-centric EV charging experience, addressing the limitations of current systems and contributing to the advancement of sustainable transportation technology. © 2025 IEEE.

关键词： Charging stations

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Smart Gloves for Communication: A Survey on technology for the Hearing and Speech Impaired 4

Smart Gloves for Communication: A Survey on Technology for t...

引用

4th International conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Anitha, A. Rajput, Bhuvan Singh Madarkhandi, Aneelkumar Naik, Mahendra Naresh Kumar, R. Nishanth, V.K. New Horizon College of Engineering Electrical and Electronics Engineering Bengaluru India New Horizon College of Engineering Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798331523923

Sharing ideas and opinions requires communication, but it can be difficult for people with disabilities. A barrier between these people and the larger community is created by the fact that they daily use sign language, which many others do not comprehend. The smart gloves facilitate smooth communication between those with impairments and others by translating hand motions into text and audio outputs. The gloves also encourage independence by enabling users to interact with household equipment. Through the facilitation of efficient communication and the removal of barriers, this system aids in the greater integration and advancement of society for people with speech and hearing impairments. The existing system has complexity and cost is more while using flux sensors and machine learning techniques. The proposed method with aluminum foil circuit create an affordable, user-friendly smart glove mechanism. © 2025 IEEE.

关键词： Audio equipment

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Investigations on Jamming and Black Hole Attacks in Wireless Sensor Networks: An Industrial Case Study

Investigations on Jamming and Black Hole Attacks in Wireless...

引用

International conference on 6G Communications Networking and Signal Processing, SGCNSP 2023

作者： Lavanya, A. Udhayakumar, P. Rajkumar, K. Revathi, S. Department of Electrical and Electronics Engineering National Institute of Technology Puducherry Karaikal609609 India Department of Engineering Karaikal Port India Department of Instrumentation and Control Engineering National Institute of Technology Trichy Tiruchirappalli620015 India

ISBN: (纸本)9789819778751

As industries rapidly advance towards Industry 4.0 and the Industrial Internet of Things (IIoT), the integration of automation and digitalization has brought unprecedented efficiency gains to various sectors. Among the critical components of Industry 4.0, belt conveyors play a pivotal role in streamlining material handling processes. Many crucial parameters in the Industrial Conveyor system require constant attention and monitoring. However, this integration of digital systems also exposes these conveyor systems to new vulnerabilities, notably cyber-attacks. This paper, investigate the potential impacts of availability attack on Industrial Conveyor system. The study employs a multi-faceted approach, combining cyber-physical experiments and simulations. Black holes and jamming attacks are considered, targeting the Wireless Sensor Network (WSN) of the Industrial conveyor system. The effects of these attacks on conveyor movement, material flow, and overall production are meticulously examined. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Jamming

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A CLIP-based Video Question Answering framework with Explainable AI

A CLIP-based Video Question Answering framework with Explain...

引用

2025 IEEE International Students' conference on Electrical, electronics and Computer Science, SCEECS 2025

作者： Jeshmol, P.J. Kovoor, Binsu C. Cochin Univesity of Science and Technology Division of Information Technology School of Engineering Kerala Kochi India

ISBN: (纸本)9798331529833

Video analytics utilizing Video Question Answering (VideoQA) techniques to develop AI systems capable of comprehending and responding to user-specific questions from the content of the custom video datasets. The proposed system detects objects from the custom video datasets using YOLO v8, a deep learning-based object detection algorithm driven by the provided questions. The SORT algorithm helps to track detected objects throughout the entire video. Also, significant frames are extracted from the input questions utilizing a pre-trained model Contrastive Language-Image Pretraining (CLIP) specialized for analyzing video clips. The proposed model comprises video processing where the raw video data is analyzed and transformed for further analysis. Subsequently, questions are encoded and processed facilitating the integration of natural language understanding into the system. The proposed model integrates video comprehension with questions and enables it to correlate the content of the videos with the queries posed by the user. Finally, the model generates answers to the questions asked, accompanied by the selection of the most pertinent frame from the video based on similarity scores. The explainable LIME algorithm enhances the interpretability of the frame with the highest similarity score. This selection process ensures that the provided answers are grounded in the relevant visual context, enhancing the overall quality and relevance of the responses generated by the system. The model exhibited superior performance when applied to specialized custom video datasets. © 2025 IEEE.

关键词： Video analysis

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Evolutionary Intelligence: A Hybrid Neural Framework for Dynamic system Innovation 3

Evolutionary Intelligence: A Hybrid Neural Framework for Dyn...

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3rd International conference on electronics and Renewable systems, ICEARS 2025

作者： Sharma, Puneet Khan, J. Sulthan Ali Radhika, K. Thatipudi, Jayendra Gopal Sridevi, K. Upadhyay, Shrikant School of Cs & Ai Sr University Telangana Warangal India VelTech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of It India Department of Mca Angallu Andhrapradesh Madanapalle517325 India University of North Texas Dept. of Computer Science United States S.R.K.R Engineering College Department of It Chinamiram Andhra Pradesh Bhimavaram India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798331509675

The Adaptive Neural Evolutionary Framework for Building Dynamic systems with Hybrid Intelligent Architectures is designed to address challenges in real-time adaptability, optimization, and performance of complex systems. This framework integrates Neural Networks (NNs), such as Long Short-Term Memory (LSTM) and Residual Networks (ResNet), with Evolutionary Algorithms (EAs), including Genetic Algorithms, to dynamically optimize hyperparameters and structural configurations. Preprocessing techniques like Wavelet Transform and Adaptive Contrast Enhancement (ACE) enhance data clarity and signal quality, significantly improving system input. The proposed hybrid framework achieves superior accuracy compared to traditional models, with a training accuracy of 96.8%, validation accuracy of 95.5%, and a testing accuracy of 96.9%. Experimental results demonstrate that the system performs exceptionally well under dynamic scenarios such as sudden input shifts, unseen data distributions, and resource constraints. Furthermore, the integration of adaptive feedback loops and neural plasticity ensures continual learning and model evolution in real-time. The framework's robustness and adaptability make it suitable for applications in predictive modeling, decision-making systems, and dynamic environments. © 2025 IEEE.

关键词： Wavelet transforms

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