Abstract:
This thesis introduces GrowAI Web, a web application designed for monitoring hydroponic
farming in real time. Built using HTML, CSS, and JavaScript, it displays sensor data of pH,
temperature, and nutrient levels along with AI-generated recommendations in the form of in-
teractive graphs and actionable alerts. Our month-long pilot test with one small-scale plant
showed that this tool can reduce manual monitoring time. In line with the Faculty of Computing
guidelines, this project demonstrates how web-based front-end technologies can make preci-
sion agriculture accessible to producers with limited resources.
