International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Agriculture remains the major occupation and source of livelihood for a large section of the population worldwide, especially in developing countries like India. However the sector faces challenges related to weather uncertainty, resource limitation, and lack of scientific decision-making tools. Most farmers usually decide which crop to grow based on guesswork or general government advice, but this information does not always match the exact conditions of their farmland, such as soil moisture, rainfall, and temperature, which can lead to low crop yield and poor income. To overcome these problems, this study presents a simple and low-cost IoT-based crop recommendation system that uses an ESP8266 microcontroller along with sensors like DHT11 for temperature and humidity, a soil moisture sensor, and a rainfall sensor to collect real-time data from the field and suggest suitable crops. In addition, a PIR sensor is used to detect the movement of wild animals or unauthorized people, helping to protect the crops and improve overall farm safety. Collected data processing is achieved by using a rule- based algorithm, extendable to machine learning models for recommending suitable crops and triggering alerts via a Flask- based web interface. This paper covers the system architecture, hardware-software integration, and experimental validation of the introduced prototype, discussing its potential to enhance agricultural productivity and sustainability.

Keywords: Internet of Things (IoT), Precision Agriculture, ESP8266, Crop Recommendation, Intrusion Detection, Smart Farming, Flask Framework.

Downloads: | DOI: 10.17148/IJARCCE.2025.1412130