Aairos

The artificial intelligence module employs advanced algorithms to analyze sensor data and optimize irrigation schedules. Preprocessing techniques are applied to clean and normalize the data before feeding it into machine learning models. These models, such as neural networks or decision trees, learn from historical data to make real-time irrigation decisions based on soil moisture levels. Continuous feedback mechanisms refine the models' predictions over time, ensuring adaptability to changing environmental conditions and improving overallsystem efficiency.

The user interface module focuses on providing a user-friendly interface for interacting with the irrigationsystem. It incorporates intuitive design principles to present relevant information, such as irrigation status and soil moisture levels, in a clear and concise manner. Interactive controls allow users to adjust irrigation schedules and customize system settings as needed. Feedback mechanisms, such as notifications and progress indicators, keep users informed about system actions and status updates, enhancing user experience and facilitating efficient systemmanagement.