• Stephy Thomas
• Omkar Surve
• Shobha Bagle

Modern agriculture relies on advanced technologies to enhance productivity and sustainability. This project proposes an innovative plant monitoring system using Arduino Nano and ESP32 for wireless data transmission. The system integrates temperature sensors for environmental monitoring, soil moisture sensors for assessing hydration levels, and NPK sensors for analyzing soil nutrient content. Arduino Nano and ESP32 facilitate real-time data collection and transmission to a central processing unit. Machine learning algorithms analyze the collected data, predicting optimal growth conditions for plants. This enables farmers to make informed decisions regarding irrigation, nutrient management, and overall crop health. The wireless capabilities of Arduino Nano and ESP32 ensure scalability and flexibility, supporting remote monitoring and management of plant conditions. This combination allows continuous monitoring, early detection of issues, and timely interventions. Advantages include optimized use of water and fertilizers, improved crop yields, and reduced environmental impact, promoting sustainable farming practices

"Soil Moisture Using Esp32 & ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.f335-f338, February-2025, Available :http://www.jetir.org/papers/JETIR2502547.pdf

"Soil Moisture Using Esp32 & ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppf335-f338, February-2025, Available at : http://www.jetir.org/papers/JETIR2502547.pdf