Smart Drip Irrigation with Weather Forecast Integration

BACKGROUND: Smart Drip systems are not automated, and traditional irrigation wastes water because it is controlled by hand. Irrigation is automated to reduce overwatering and increase efficiency by combining IoT sensors with weather forecasts on an ESP32 platform. AIM: This project creates a smart drip irrigation system based on the Internet of Things that uses weather forecasts and real-time sensor data to automatically water plants. It reduces labor costs, conserves energy and water, and makes remote monitoring possible through IoT platforms. MATERIAL AND METHOD: To control irrigation, the system makes use of an ESP32 equipped with sensors for soil moisture, DHT11, rain, and water level, as well as pumps that are managed by a relay module. It allows for automated, forecast-based irrigation with real-time remote monitoring and control through integration with IoT platforms and weather APIs. RESULTS: By automating irrigation based on real-time data and weather forecasts, this smart irrigation system ensures healthier crop growth while reducing water and energy waste. It is a sustainable, effective solution that reduces manual labor and avoids over-irrigation because of its scalability and automation. Keywords: ESP32, IoT, Soil Moisture Sensor, DHT11, Rain Sensor, Water Level Sensor, Relay Module, Water Pumps, Weather API, Blynk, Thing Speak, Real-Time Monitoring, Automatic Irrigation, Water Saving, Energy Efficiency, Crop Health, Automation, Over-Irrigation Prevention, Scalability, Sustainable Farming.