This paper presents an automated agriculture solution that integrates IoT sensors, machine learning and automation to improve plant monitoring and management. Using a Raspberry Pi 4, the system collects real-time data from sensors such as DHT11, soil moisture sensor, MQ-135 and PIR to monitor environmental conditions. A camera module combined with a deep learning model detects plant diseases and pest infestations. Based on the sensor data and analysis, the system automatically controls irrigation and pesticide spraying while displaying information through a web interface and storing data on the ThingSpeak cloud. This approach reduces manual intervention, optimizes water and pesticide usage and promotes efficient and sustainable plant care.
G et al. (Sun,) studied this question.