International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI-Driven Decision Support and Market Intelligence for Smart Agriculture Using Random Forest and LSTM Networks |
|---|---|
| ABSTRACT | Agriculture faces mounting challenges including unpredictable climate patterns, declining soil health, and volatile market prices that often leave smallholder farmers financially vulnerable. This paper presents FarmLink, an AI-powered Agricultural Decision Support System (ADSS) designed to help farmers make smarter, data-backed decisions with minimal technical expertise. The system integrates three intelligent modules: (1) a Random Forest (RF) classifier for precision crop recommendation using soil and environmental parameters (N, P, K, temperature, humidity, pH, rainfall); (2) a Long Short-Term Memory (LSTM) deep learning network for market price and demand forecasting; and (3) a Cosine Similarity-based matching engine that connects farmers directly with buyers. The RF classifier achieves over 99% classification accuracy; the LSTM forecasting module attains a MAPE of 5.8%. Deployed as a lightweight Flask web application, FarmLink bridges the information gap between farm-level production and market-level demand, empowering farmers to plan, connect, and trade efficiently. |
| AUTHOR | CHAMPASHREE KM, PROF B. SOWMYA Post Graduate Student, Department of Computer Science and Engineering, East West Institute of Technology, Bangalore, Karnataka, India Professor, Department of Computer Science and Engineering, East West Institute of Technology. Bangalore, Karnataka, India |
| VOLUME | 187 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1408023 |
| pdf/23_AI-Driven Decision Support and Market Intelligence for Smart Agriculture Using Random Forest and LSTM Networks.pdf | |
| KEYWORDS | |
| References |
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