학술논문

AgriAid: An Intelligent Farmer Companion Using Deep Learning Approach
Document Type
Conference
Source
2024 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE) Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), 2024 International Conference on. :1-6 Jan, 2024
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Robotics and Control Systems
Signal Processing and Analysis
Training
Deep learning
Economic indicators
Computational modeling
Sociology
Decision making
Crops
Voice-based Chatbot
Natural Language Processing
Voice based Query System
Artificial Neural Network
Neural Networks
Language
Abstract
The percentage of farmers in India’s enormous population is roughly 54.6%. However, despite having such a large population, they only contribute roughly 13.9% of the nation’s total yearly GDP. This severe inequality may be reduced by improving farmers’ access to information and expert advice. In order to increase crop output and quality, farmers typically depend on agricultural counselors and professionals to provide correct information for crop decision-making. Frequently, advisors or specialists in agriculture are not always available. A voice-based chatbot has several benefits, such as being real-time, constantly available, requiring little to no training to use, and providing instant access to information rather than requiring users to walk convoluted paths. In this study, we explain my design work for a farmer’s helper, named Farmer Companion, to meet the needs of both rural and urban Indian farmers utilizing Supervised ML Algorithms and Deep Neural Networks, of which the best one is selected. A comparison of recent models that have been used in the literature is also included in the paper.