Automatic regulation of valves for release of water based upon soil moisture availability in the root zone of the crop, using artificial intelligence, in a piped and micro irrigation network of irrigation system.
This system employs artificial intelligence to continuously assess soil moisture levels around crops. When the soil becomes too dry and requires irrigation, the AI triggers the (Solenoid) valves to release water precisely where and when it's needed. This ensures efficient water use, reduces waste, and promotes healthy crop growth. It's a smart solution for sustainable and automated irrigation management.
The approach involves utilizing artificial intelligence to monitor soil moisture levels within the crop's root zone in a piped and micro-irrigation network. When the AI detects that the soil is sufficiently dry, it autonomously regulates the irrigation valves, releasing water precisely where and when it's needed. This intelligent system optimizes water use, minimizes wastage, and supports healthy crop growth by ensuring that irrigation is provided only when necessary.
- IoT Sensors: Various sensors (e.g., soil moisture sensors) to collect data from the field.
- Python: Python is a versatile language commonly used in machine learning and speech processing tasks.
- Arduino: For sensor data collection and processing.
- Machine Learning Libraries: TensorFlow, PyTorch, and scikit-learn for building AI models.
- Automation and Control:
- Control Systems: Implementing logic for valve control using Python or other programming languages.
- Actuators: Solenoid valves or pumps for irrigation control.
- User Interface:
- Figma: It enables collaborative and efficient UI/UX development, helping to create visually appealing and user-friendly interfaces for controlling and monitoring the irrigation system. Figma allows for real-time collaboration, which aids in streamlining the design process and ensuring that the UI meets the project's requirements effectively.
Version Control:
- Git and Github: A version control system and platform that helps you manage your codebase, collaborate with others, and track changes.
IDE (Integrated Development Environment):
- Jupyter Notebook: These are popular choices for Python development, offering features like code autocompletion and debugging.
This project has been proposed and prepared by the team Technoholics.