Smart Farming Advisor: AI-Based System for Crop Recommendation and Market Prediction

Authors:

Shete Shiwani Ramhari*1, Hawaldar Arbaz Shakil*2, Gavande Rahul Ankush*3, Lohote Sumit Sampat*4

*1,2,3BE Student, Department Of Electronics and Telecommunication Engineering, Sharad Chandra Pawar College of Engineering, Otur, India.

*4Project Guide, Professor, Sharad Chandra Pawar College Of Engineering, Otur, India.

ABSTRACT

This paper presents an automated approach to smart farming within the domain of precision farming and sustainability. In many farmers face challenges related to unpredictable weather, improper soil management, and using wrong fertilizer, which often lead to reduced productivity and financial losses. To address these issues, the concept of a Smart Farming Advisor System is proposed—an integration of hardware and software technologies that connects field sensors to a cloud-based analytical platform using an ESP32 NodeMCU. The system monitors real-time parameters such as soil moisture, temperature, humidity, light intensity, and NPK nutrient levels, enabling accurate soil health assessment and environmental monitoring.

Using IoT and AI technologies, the data collected from multiple sensors is transmitted to a cloud database for intelligent processing. The integrated AI model analyzes this information to recommend optimal crops, predict future market prices, and provide actionable insights for farmers. The system also displays live farm data on a 0.96” OLED screen, including time, temperature, humidity, and alert status, while detailed crop and soil analytics are accessible through a web dashboard Operating on a client–server architecture, the proposed system promotes sustainable agriculture by supporting data-driven decision-making, efficient resource utilization, and enhanced farm profitability.

Keywords: IoT, AI Based Smart Farming, NodeMCU, Soil NPK Sensor, Crop Recommendation, Market Prediction, Cloud Dashboard.