IoT-based control and monitoring system for hydroponic plant growth using image processing and mobile applications.

ABSTRACT: The HydroFarm project presents an innovative IoT-based control and monitoring system for hydroponic plant growth, integrating advanced image processing techniques and mobile applications to enhance urban farming practices. This system addresses critical challenges faced by urban farmers, such as limited space and the need for precise environmental management. By employing a comprehensive approach that combines various sensors (DHT22, DS18B20, pH, TDS) with an ESP32 microcontroller, HydroFarm enables real-time monitoring of essential parameters like temperature, humidity, pH, and nutrient levels. A significant novelty of this project lies in its use of a convolutional neural network (CNN) for plant health assessment through image processing. This technique allows for accurate detection of p

SUBMITTER: Rofiansyah W 

PROVIDER: S-EPMC12190697 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature