ESP32 Smart Irrigation Controller with Soil and Weather Data

Intelligent irrigation controller uses ESP32 with inputs: capacitive soil moisture sensor, DHT22 for local temperature/humidity, and OpenWeatherMap API for weather forecast. Controller skips watering if rain is forecasted in next 24 hours. Watering schedule: configurable zones (6 zones via 6-relay module), daily/weekly schedules per zone, manual trigger from web interface. Smart mode: calculates ET (evapotranspiration) using Penman-Monteith equation considering temperature, humidity, wind speed, solar radiation from weather API. Logs all watering events to SD card. Web dashboard: zone status, soil moisture per zone, forecast widget, schedule calendar, manual controls. Push notifications via Pushover app when watering starts/stops or system error. Offline mode: if WiFi/API unavailable, falls back to time-based schedule with soil moisture override. Libraries: HTTPClient, ArduinoJson, RTC library, SD, WiFi, ESPAsyncWebServer.

Detailed Project Description

ESP32 Smart Irrigation Controller with Soil and Weather Data automates watering / feeding based on real sensor data instead of fixed timers, saving water and effort while keeping conditions stable.

How It Works
1. Sensors measure the relevant conditions (soil moisture, water level, pH, temperature).
2. The controller compares readings with set-points and decides when to run the pump, valve or feeder.
3. Actions and readings are logged and can be viewed/overridden from a phone or web page.
4. Schedules and thresholds are configurable without re-flashing the firmware.

Key Components and Their Role
- ESP32: dual-core Wi-Fi + Bluetooth microcontroller that runs the firmware, reads the sensors and hosts the network connection.
- DHT22: digital temperature and humidity sensor with better accuracy than DHT11.
- Relay module: electrically isolated switch that lets the controller turn AC/DC loads on and off.
- Soil moisture sensor: capacitive probe that measures water content of soil.
- microSD card module: storage for logs, audio or images over SPI.
- Solar panel: renewable power source for off-grid operation.

Implementation Steps
1. Collect the components and study each module's datasheet (pin-out, voltage, interface).
2. Wire the circuit on a breadboard following the pin mapping; power sensors from the correct rail (3.3 V / 5 V).
3. Install Arduino IDE, OpenWeatherMap API, ArduinoJson and the required libraries; flash a minimal test sketch for each module separately.
4. Write the main firmware: read sensors → process → drive outputs / send data.
5. Configure network or cloud credentials and test communication end-to-end.
6. Calibrate thresholds, add error handling (reconnect, sensor time-out) and run a long-duration test.
7. Finalise on a PCB / enclosure and document wiring, code and results.

Key Features
- Sensor-based automation
- Manual override
- Configurable thresholds
- Remote monitoring

Expected Output
On completion the student will have automatic pump/feeder operation with a log of every action and reading.

Deliverables
- Complete source code with comments
- Circuit diagram and pin mapping
- Project report with screenshots and results
- Demonstration-ready build