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E-grāmata: Computing Technologies for Sustainable Development: First International Research Conference, IRCCTSD 2024, Chennai, India, May 9-10, 2024, Proceedings, Part I

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This book constitutes the refereed proceedings of the First International Research Conference on Computing Technologies for Sustainable Development, IRCCTSD 2024, held in Chennai, India, during May 910, 2024.





The 65 full papers and 14 short papers presented here were carefully selected and reviewed from 264 submissions. These papers have been organized in the following topical sections:





Part I: innovations in precision agriculture techniques and strategies for enhancing agriculture production; classification and prediction analysis in healthcare; animal welfare; and innovations in diagnostics.

Part II: video and image processing for security analysis; innovations for smart cities; sustainable practices in e-commerce: challenges and trends.

Part III: environmental analysis and protection; inclusive communication techniques; AI for text, audio, image and video processing; and application of AI for education.

.- Innovations in Precision Agriculture Techniques and Strategies for Enhancing Agriculture Production.
.- Transfer Learning Based Ensemble Models for Rice Leaf Disease Detection.
.- Chat Bot for Crop Yield Prediction and Recommendation through K Nearest Neighbor Algorithm Chat Bot for Crop Yield Prediction.
.- Analysis of Micro Bacteria Organism Classification by Using Convolution Neural Network With Improved Accuracy.
.- Crop Disease Recognition and Classification A Deep Dive into Machine Learning Techniques A Survey.
.- Identification Of Infectious Potato Using CNN.
.- Early Warning prediction system for agriculture using deep learning.
.- A Comparison of Different Deep Learning Models for Plant Leaf Disease Detection.
.- Identifying Paddy Crop Disease using Enhanced Deep Learning Technique.
.- Internet of Things Based Multiple Sensor Monitoring System for Soil Information Diagnosis Using a Smartphone.
.- An Automatic Motor Control System for Smart Irrigation.
.- Classification and Prediction Analysis in Healthcare.
.- Eye Fundus Disease Classification Using Artificial Intelligence.
.- Deep Learning Based Multi Disease Detecting Model.
.- Intelligent Posture Monitoring System with Real Time Notifications using Media Pipe and Open CV.
.- Diabetes Prediction Using Deep Learning.
.- Efficient Information Extraction from Medical Records.
.- Decoding the Mind: Translating Human Thought with EEG Signals.
.- Detection of Thyroid Stages Classification using Convolutional Neural Network Techniques.
.- Evaluating Biglycan as a Biomarker in Breast Cancer Detection: A Custom CNN Architecture.
.- Early Diagnosis of Glaucoma and Diabetic Retinopathy using Fundus Images based on Ensemble Approach.
.- Ultrasound based Breast Cancer Segmentation and Classification with Deep Learning Techniques.
.- Advanced Techniques for Cancer Research with Multimodal Fusion and Deep Learning.
.- Comprehensive Assistive Blind Stick for Visually Impaired Individuals.
.- Brain o vision: Brain Tumor Detection.
.- Elderly Fall Detection Model for Patient Care Using Improvised CNN.
.- Animal welfare: Innovations in Diagnostics.
.- Detection of poultry diseases using ConvNeXt V2.
.- Unveiling the Potential of Audio Classification for Poultry Health Diagnosis: A Deep Learning Approach.
.- Feathered Diagnose Smart Disease Classification in Chicken with Deep Learning and MLOps.