Smart Agriculture Using IoT

Crop yields are heavily reliant on efficient irrigation management, making agriculture essential to economic growth. This study presents an Internet of Things (IoT)-based system that continuously monitors soil and plant conditions to modernize farming. Real-time environmental data is gathered by sensors like the DHT-11 for temperature and humidity, an LDR for light intensity, and a soil moisture sensor. Based on these readings, a water pump that is managed by an L293D motor driver IC runs automatically, maximizing water use and cutting waste. By enabling remote monitoring and control via an online platform, the system improves user accessibility. To increase efficiency over time, it also includes a database to hold historical data and predicts irrigation requirements using the Partial Least Squares Regression (PLSR) algorithm. This solution provides a farming method that is both sustainable and scalable.