AI-Driven Smart Agriculture: An Integrated Approach for Soil Analysis, Irrigation and Crop-Fertilizer Recommendation

Abstract

The proposed system is an IoT-based smart agriculture monitoring and automation system designed to improve crop productivity, optimize water usage, and enable real-time decision-making. Traditional farming methods rely on manual monitoring and fixed irrigation schedules, leading to water wastage and inefficient resource utilization. To overcome these issues, the system integrates sensors, automation, and cloud-based monitoring into a single solution. Environmental sensors such as soil moisture, temperature, and humidity continuously monitor field conditions. The collected data is processed by a microcontroller, which compares values with predefined thresholds and automatically controls irrigation systems like pumps and valves. This ensures optimal water usage and reduces manual effort. For communication, Wi-Fi modules such as ESP8266/ESP32 transmit data to cloud platforms like ThingSpeak, where it is stored, analyzed, and visualized as graphs, allowing farmers to monitor fields remotely through mobile devices or computers. The system also provides alerts and remote control features, enabling quick action during abnormal conditions. Overall, the system is cost-effective, scalable, and energy-efficient, improving productivity while conserving water and supporting sustainable smart farming practices.