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MANAS: Integrating Advanced AI for Personalized Mental Health Support, Crisis Intervention, and Medical Insights 3

MANAS: Integrating Advanced AI for Personalized Mental Healt...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Gayathri, S. Pradeep, Mutyala Sri Siva Sai Lakshmi Vara Prasad, N. School Of Computing Sathyabama Institute Of Science and Technology India

ISBN: (纸本)9798331527549

MANAS (Mental Assistance Network for Alleviating Suffering) is an AI-based system designed to address the pressing challenges in mental health care, including limited access to personalized, timely support and crisis intervention. By leveraging advanced AI techniques such as personality analysis using the Big Five model and emotion recognition through NLP, MANAS offers personalized responses to users’ mental health concerns. It also detects traces of crisis and triggers appropriate interventions, including notifying relevant authorities. The system generates detailed medical reports to aid healthcare professionals in diagnosing and managing mental disorders more effectively. This research demonstrates MANAS's capability to bridge the gap in mental health care with innovative and practical AI-driven solutions. © 2025 ieee.

关键词： emotion Recognition

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Smartphone Price Prediction and Category Classification using Machine Learning 3

Smartphone Price Prediction and Category Classification usin...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Agalayil, Helen Terese Radha, D. Kirthika Devi, V.S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The rapid evolution of smartphone technology and the diverse range of available models have made selecting a cost-effective mobile phone a complex decision for consumers. Although brand, internal memory, camera quality, battery life, processor speed are all important determinants of purchase decisions, it is frequently unclear how these factors relate to the price. This work explores the application of machine learning algorithms to predict mobile phone prices and their price category classification based on these characteristics, offering insights to aid consumer decision-making. Five classifiers and five regressors were compared using accuracy and time complexity as evaluation metrics and k-NN was found to be the best classifier for the price class classification and LightGBM was found to be the best regressor for price prediction. © 2025 ieee.

关键词： Smartphones

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Development of an Adaptive Smart Toy with emotional Feedback 3

Development of an Adaptive Smart Toy with Emotional Feedback

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Mohandas, Gayathri Sanay Santh, V. Padmakumar, Keshav Thangam, S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Traditional toys often do not adapt to the emotional and physical needs of children, particularly those who may have limited verbal communication abilities. The project’s goal is to create a smart toy that is adaptive and can communicate with a child by using nonverbal signs to express his or her physical and emotional states. There are sensors like accelerometers to detect movement, a gesture sensor indicating light intensity, a buzzer sensor to produce sound, and an IR sensor to detect the child’s hand when the child is near the toy. All these components will help the user to get in-time feedback with a set of visual indicators (LeDs) and tactile feedback in the form of vibration motors. This smart toy seeks to improve the experience of play and developmental support for children by being more responsive and engaging with individual needs. © 2025 ieee.

关键词： Intelligent robots

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An enhanced Framework for Churn Prediction using Stratifed Bagging and Stacked Multi-Output Random Forests 3

An Enhanced Framework for Churn Prediction using Stratifed B...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Bhardwaj, Anay Radha, D. Kirthika Devi, V.S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidhyapeetham Bengaluru India Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidhyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Customer churn prediction is an important task in customer relationship management because it helps businesses know who is at risk of leaving and retain such at-risk *** and time-efficient churn prediction is essential to identify the factors driving churn, enabling businesses to implement timely and effective retention strategies.A framework is proposed which combines stratified bagging with multi-output Random Forest and stacked feature transformation, to enhance prediction accuracy. This approach balances the dataset, trains a custom Random Forest using stratified bagging, and applies stacked learning using Logistic Regression on transformed features. Tested on real-world data, the model demonstrated 99% accuracy, showing improvements over the classic Random Forest in precision, recall, and prediction time. © 2025 ieee.

关键词： Sales

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A Survey of 3D Gaussian Splatting: Optimization Techniques, Applications, and AI-Driven Advancements 3

A Survey of 3D Gaussian Splatting: Optimization Techniques, ...

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3rd international conference on Intelligent and Innovative Technologies in computing, electrical and electronics, IITCee 2025

作者： Santosh Reddy, P. Abhiram, H. Archish, K.S. B.N.M. Institute of Technology Department of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798331515911

3D Gaussian Splatting (3DGS) has emerged as a transformative technique for real-time, high-quality 3D rendering. This paper surveys the advancements in 3DGS, focusing on optimization strategies, applications across diverse domains, and AI-driven innovations that enhance its utility. Optimization techniques, such as Mini-Splatting and sparsification frameworks, address challenges like computational overhead and memory inefficiency while maintaining visual fidelity. AI has further expanded the capabilities of 3DGS through frameworks like SceneTeller, ART3D and Gaussianeditor, enabling text-to-3D generation, object-level manipulation, and artistic scene creation with multi-view consistency. Applications of 3DGS range from autonomous driving and robotics to virtual and augmented reality, highlighting its adaptability and efficiency. This survey underscores the importance of continued research to refine 3DGS's scalability and applicability, solidifying its role at the intersection of computer graphics and artificial intelligence. © 2025 ieee.

关键词： Augmented reality

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QuickPark: efficient Parking with Real-Time Pre-Booking 3

QuickPark: Efficient Parking with Real-Time Pre-Booking

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Dharshan, J.Y. Amarnath, Arjun R. Adithya, Gadamsetty Siva Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The parking is one of the biggest problems. One of the emerging features of parking management is congestion in urban centres due to the increase in the number of vehicles on the road, which has added anxiety to drivers. These conventional or legacy parking systems fail to respond adequately to the increasing needs, especially in Smart City contexts. To this end, a Smart Parking Management System (SPMS) is developed with real-time data, incorporating a parking sensor, parking information, an easy-to-navigate parking lot, and favourable methods of payment accepted. This prototype optimises parking space, provides better convenience to drivers, and leads to the sustainability of such a structure in the urban area. The proposed SPMS promises to be a revolutionary and practical approach to addressing some of the modern parking management issues in delivering an efficient mobility regime. © 2025 ieee.

关键词： Parking

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Detection and Classification of Monkeypox Disease with Chatbot 3

Detection and Classification of Monkeypox Disease with Chatb...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Chandu, P. Siddardha, P. Priyadharshini, K. Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798331527549

Monkeypox detection is essential for effective public health management and controlling its spread. Timely detection enables early intervention in outbreaks, reducing transmission risk. This project presents an innovative framework that enhances monkeypox detection and classification using deep learning and an interactive chatbot. It employs the VGG16 convolutional neural network (CNN) for accurate classification of monkeypox from medical images, utilizing performance metrics like precision, recall, and F1 score for reliability. Additionally, the system includes a neural network-based chatbot that provides interactive assistance, answers user questions, offers symptom information, and guides users through the diagnostic process. This chatbot improves user engagement and accessibility, linking clinical diagnostics with patient interaction. Built on the Flask framework, the system ensures a smooth, user-friendly interface for both image classification and chatbot functionalities. © 2025 ieee.

关键词： Convolutional neural networks

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Blockchain Integration for Robust Intellectual Property Protection in New Product Development (NPD) 3

Blockchain Integration for Robust Intellectual Property Prot...

引用

3rd international conference on electronics and Renewable Systems, ICeARS 2025

作者： Chinnasamy, P. Subashini, B. Nijanthan, Nijanthan Madasamy Raja, G. Swetha, Devulapally Sreenivasulu Reddy, L. School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India School of Computing Srmist Department of Data Science and Business Systems Kattankulathur India Paavai Engineering College Tamilnadu Namakkal India Paavai Engineering College Tamilnadu Namakkal India Vaagdevi Engineering College Dept. of Computer Science and Engineering Warangal Dist. Telangana Bolli Kunta506005 India School of Advanced Sciences Kalasalingam Academy of Research and Education Department of Mathematics Tamilnadu Krishnankoil India

ISBN: (纸本)9798331509675

The rapid advancement of Blockchain technology has led to its widespread application in several domains of digital activities, such as e-government concerns and monetary security. This article presents a smart contract-based Blockchain solution for protecting intellectual property rights in new product development. The proposed solution effectively tackles the challenges associated with the confidentiality of personally identifiable information, efficiency in storing transaction-related information, as well as cooperation and monitoring in IPR. Initially, we create a mathematical model based on smart contract enabled Blockchain and intelligent contracts. Subsequently, we develop algorithms for Blockchain generation, and intelligent contracts. The system is suitable for protecting IPR in a blockchain network, by implementation of distributed identity authentication and real-time extensible storage. These features enhance the security and expandability of circuit copyright protection based on blockchain technology. The experimental results demonstrate that the suggested algorithm has decreased the cost for communication and enhanced the effectiveness of storing information and administration. Furthermore, it demonstrates resilience against many common attacks such as double-spending assaults, while maintaining low cost and overhead. Additionally, it exhibits a superior level of security in comparison to three other competing algorithms. © 2025 ieee.

关键词： Smart contract

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Power quality monitoring and analysis method of distribution station area based on edge computing 3

Power quality monitoring and analysis method of distribution...

引用

2024 3rd international conference on energy Internet and Power Systems, ICeIPS 2024

作者： Meng, Xiangliang Zhang, Zhe Liao, Xiao Cui, Wei Wang, Shilin State Grid Information and Telecommunication Group Changping District Beijing102200 China

Facing the demand for multi-scenario, differentiated, and decentralized monitoring, and analysis of power quality in distribution networks under the new situation, this paper proposes an edge computing-based power quality monitoring and analysis method for distribution station areas. It introduces the three-layer architecture of the power quality monitoring system for the distribution station area. It designs three monitoring modes based on edge computing, namely light monitoring, normal monitoring, and intensive monitoring. The key indicator calculation and statistical analysis method of power quality under an edge computing framework are presented. Typical application scenarios are selected for pilot application and verification. The results show that this method can realize the quantitative analysis of power quality operation in the power distribution area, actively discover potential power quality problems in the power distribution area, and meet the diversified needs of power quality monitoring and analysis in the power distribution area. © Published under licence by IOP Publishing Ltd.

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Deep Learning to effectively Detect and eliminate Real-Time Network Intrusions 3

Deep Learning to Effectively Detect and Eliminate Real-Time ...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Harikesh, S. Sujatha, G. Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamilnadu Chennai India

ISBN: (纸本)9798331527549

Network traffic has been growing exponentially for the past several years. As a result, it has become more and more difficult to detect cyber intrusions - especially in unbalanced environments, where the attacks are usually covered up by normal traffic. This investigation is set to deal with the problem by coming up with an intrusion detection system that uses a deep learning approach to effectively find and eliminate the unbalanced network intrusions. The process includes data preprocessing for balancing the classes, feature engineering for choosing optimal features, and comparison of CNN and RNN models for improving detection accuracy. The tests have shown precision of 93% and recall of 88% which in total brought 99.8% accuracy. Also, the real-time deployment has demonstrated the model’s ability to dynamically traffic patterns, which induced false positives to be reduced remarkably. The results help in the improvement of intrusion detection systems by providing a scalable, adaptive, and efficient way to handle constantly altering cyber threats. © 2025 ieee.

关键词： Network intrusion

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