Agricultural Chatbot Voice Assistant Using NLP Techniques
Year: 2025
Type: article
Abstract: In modern agriculture, the convergence of technology has become increasingly critical for enhancing productivity and sustainability. This abstract introduces the concept of an Agriculture Chatbot Voice Assistant (ACVA) employing Multi-Layer Perceptron (MLP)neural networks and Natural Language Processing (NLP) techniques. ACVA serves as an innovative virtual advisor, empowering farmers with real-time insights and recommendations. By leveraging MLP, ACVA analyzes complex agricultural datasets encompassing soil health, weather patterns, and crop characteristics to provide tailored guidance on crop management, pest control, and market trends. Additionally, NLP capabilities enable ACVA to understand and respond to farmers' inquiries through natural language interactions. Integrating voice recognition technology further enhances accessibility, allowing farmers tonguefish ACVA seamlessly, even in remote or hands-free environments.
Authors: Maruti saisurya rajanala -, Muppirisetti Sivakiran -, Manduva Sairevanth -, Ms S.Subbulakshmi -, Dr Anand M -
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W4408943329