PetalGrid: An AI–IoT Based Smart Garden Monitoring and Automated Irrigation System

Modern horticulture and botanical garden management require continuous monitoring of environmental conditions to maintain plant health and optimize resource usage. Traditional irrigation and monitoring methods rely heavily on manual observation, which often leads to inefficient water usage and delayed responses to environmental changes. This paper presents PetalGrid, an Artificial Intelligence (AI) and Internet of Things (IoT) based smart garden monitoring system designed to automate plant care using real-time environmental sensing and predictive analytics. The system integrates multiple sensors including soil moisture, temperature, humidity, and light sensors connected to a NodeMCU microcontroller. Sensor data is transmitted through Wi‑Fi to a cloud-based dashboard where analytics and monitoring are performed. Machine learning techniques are utilized to analyze environmental patterns and predict irrigation requirements. Based on these predictions, the system can automatically control actuators such as water pumps and lighting systems. Experimental implementation demonstrates that PetalGrid enables efficient water management, reduces manual intervention, and improves plant health through intelligent automation. The system is scalable, secure, and suitable for applications ranging from small indoor gardens to large botanical environments.