Smart Agriculture System Using IoT and ML

Agriculture is an essential industry that provides the necessities of life, including food, clothing, and shelter. It is crucial in rural areas, as it creates jobs and income opportunities and contributes to the Indian economy. Furthermore, agricultural practices play a critical role in maintaining the environment and preserving its fragile balance. This paper proposes a low-cost system that uses Internet of Things (IoT) and Machine Learning (ML) to maximize crop yield and productivity. The system consists of three key components: an IoT device, a mobile application, and servers. The IoT device uses an Espressif System Platform 32(ESP32) microcontroller, a Digital Humidity and Temperature sensor 11 (DHTII) temperature humidity sensor, and a soil moisture sensor to gather data and sends it to the Amazon web services (AWS) IoT via the Message Queuing Telemetry Transport (MQTT) protocol. The IoT device is interfaced with a relay switch to turn ON/OFF water pumps. The mobile application helps us to monitor the temperature, humidity, soil moisture and light intensity in real time. It also allows us to control the water pump connected to the IoT device and give access to our prediction ML model for crop and fertilizer recommendations. The server is an integral part of this system as it helps us connect the mobile application with the IoT device and provides storage for the sensor values and Representational State Transfer-Application Programming Interface (REST-APIs) to access our ML models. The proposed work concludes that it can highly increase agricultural productivity with the support of IoT.