Agricultural-Centric Computation

Nyhet

Third International Conference, ICA 2025, Guwahati, India, May 13–16, 2025, Revised Selected Papers

Häftad, Engelska, 2026

Av Hanumant Singh Shekhawat, Mukesh Kumar Saini, Neeraj Goel, Anwar Hossain, Dhananjay Singh

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This book constitutes the proceedings of the Third International Conference on Agricultural-Centric Computation, ICA 2025, held in Guwahati, India, during May 13–16, 2025.The 25 full papers and 3 short papers included in this volume were carefully reviewed and selected from 115 submissions. They were organized under the following thematic areas: AI & Machine Learning in Agriculture, IoT and Sensor Networks for Smart Farming, Robotics and Automation, Climate-Resilient and Sustainable Technologies, and Precision Agriculture and Data Analytics.

Produktinformation

Utgivningsdatum2026-04-11
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieCommunications in Computer and Information Science
Antal sidor199
FörlagSpringer Nature Switzerland AG
ISBN9783032170828

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Assessing Multi-Mode Temporal PolSAR Data for Winter Wheat and Barley Discrimination Using Convolutional Neural Networks.- Early Disease Detection in Pearl Millet Using YOLO v11 Model for Improved Agricultural Monitoring.- AgriFed: A Federated Learning Approach for Scalable and Secure Crop Disease Detection.- Remote Sensing and Environmental parameter analysis of Rajpura, Punjab using GIS for Precision farming application.- Optimal Hyperspectral Band selection using Amended Lyrebird optimization algorithm.- Optimally Designed High-Efficiency Drone-Based Spray System for Precision Nutrient Delivery in Agricultural Farms.- Assessing applicability and adoption of agriculture-centric computation technologies in Punjab: A multi-district farmer survey.- A Model Based Comparative Study for Conventional and Drone Based Farming: Case Studies from India.- Enhancing Large Language Model Performance for Agricultural Domain Translation via Specialised Dictionaries and Embeddings.- A Detailed Perspective on Vertical Farming – An Innovative Agricultural Trend with AI/ML and Smart Robotics.- LeADS (Leaf Anomaly Detection System):Deep Learning Pipeline for Leaf Stress, Disease & Severity Estimation.- Enhancing Agricultural Intelligence: A Comparison of AI Models for Plant Disease Categorisation and Crop Yield Prediction.- Integration of Mechanical Systems and IoT for Smart and Climate-Resilient Irrigation in Agriculture.- Deep Learning-Based Framework for Early Detection and Classification of Mango Crop Diseases.- Residual Biomass Utilization: A Review on Newly Emerging Techniques for Mitigating Climate Change.- NIR spectroscopy based non-invasive assessment of tea quality.- Comparative Analysis of DSSAT and APSIM Crop Models for Wheat Yield Prediction in Chhattisgarh State of India.- An IoT Smart Irrigation System using Raspberry Pi and ThingSpeak: Design, Implementation, and Validation.- Quantum Reinforcement Learning Framework for Agricultural Seed Treatment Optimization and Yield Prediction.- Multimodal Fusion for Cow Behavior Prediction.- Real-Time DEM-Based Terrain and Step Farming Suitability Analysis via Geospatial Processing in VR.- Swarm Robotics for Agricultural Drones: A Transformative Approach to Smart Farming.- Sodium Ion Detection using Polymer-Based Sensor for Monitoring Soil Health in Agriculture.- LEAFNET Model for Early Crop Disease Detection: Integrating CNNs and Vision Approach in Precision Agriculture.- Energy Consumption Analysis for a Robotic Arm in Vertical Farming Process: An Experimental Validation.- AgriRover: A GPS-Guided Smart Rover for Environmental Monitoring.- Optimized Conv-LSTM Model for Analyzing Negative Affective State Vocalization in Dairy Cattle for an Edge Device.- Drone RCS Statistical Behaviour and its Implications for Agriculture Drones Air Traffic Management.