Advanced Computing and Communications: Technologies for a Sustainable Future
Description
This book constitutes the refereed proceedings of the 30th International Conference on Advanced Computing and Communications, ADCOM 2025, held in Bangalore, India, during December 17-19, 2025.
The 13 full papers included in these proceedings were carefully reviewed and selected from 76 submissions. The thematic scope of Advanced Computing and Communications Conference, ADCOM 2025, was classified into the following: Computation, Control, and Automation, Energy and Environment, Machine Learning and Natural Language Processing, and the PhD Forum.
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Content
.- Computation, Control, and Automation
.- Quantitative Evaluation of Software Carbon Intensity for Serverless Applications.
.- A Hybrid Genetic Algorithm with Restricted Mutation (GA-RM) for Task Scheduling in Cloud Computing.
.- Multi-Modal Automatic Detection of Distress Behaviors in Surveillance Systems.
.- EAMO: An Algorithm for Exploration Among Movable Objects using a Ground Robot.
.- Hybrid Method for Automatic Flight Manoeuvre Recognition using Signal Processing and Classification Learner.
.- Energy and Environment
.- Net Zero Energy Home with Solar Powered Photovoltaic System.
.- Automated Assessment of Rooftop Solar Energy Potential Using Deep Learning-Driven Building Footprint Extraction Model.
.- Analysis of Energy Efficiency of a Distributed STAR-RIS-Assisted Wireless System.
.- Multi-Task Graph Convolutional Network Framework for Ward-Level Urban Sustainability in Bengaluru.
.- Machine Learning and Natural Language Processing
.- TamilBookAnnot: A Strategic e-Book Annotation Framework in Tamil Integrating Semantic Intelligence Interfaced with Knowledge.
.- AssameseDocRec: A Strategic Framework for Assamese Document Recommendation Integrating Generative Semantic Intelligence and Quantitative Semantic Reasoning.
.- AssameseVidRec: A Strategic Framework for Assamese Video Recommendation Integrating Generative Semantic Intelligence.
.- A Comprehensive Survey of Traditional, Machine Learning, Deep Learning, and Federated Learning Methods for Multimodal Autism Spectrum Disorder Diagnosis.
. - PhD Forum
.- An Explainable Deep Learning Framework for Suspicious Activity Recognition and Person Identification in Video Surveillance.
.- Prediction of Respiratory and Cardiovascular Health Risks due to Air Pollutants using Similarity Measures.
.- Development of Interpretable and Efficient Visual Question Answering Models.