Plants are the foundation of life on earth because they provide us with food and oxygen.
The project involves the development of several advanced systems powered by machine learning and automation.
The Automated Plant Recognition system utilizes computer vision to identify plant species and diagnose diseases in real-time, significantly reducing the time and effort required for traditional plant identification.
The Fire Detection and Alert System uses deep learning to detect potential fire incidents, providing timely alerts to prevent hazards and ensure safety.
The Soil Moisture Sensing and Irrigation Control system integrates moisture sensors to autonomously manage irrigation based on real-time data, optimizing water usage for plant growth.
Finally, the Remote-Controlled Robot allows users to remotely navigate a robot using a smartphone interface, enhancing precision and control in various tasks.
These systems collectively aim to revolutionize fields such as agriculture, environmental management, safety, and automation.
Automated Plant Recognition: Uses computer vision to identify plant species and diagnose diseases in real-time, reducing the effort and time needed for traditional methods.
Fire Detection and Alert System: Utilizes deep learning to detect fire incidents early, providing timely alerts to prevent hazards and improve safety.
Soil Moisture Sensing and Irrigation Control: Employs moisture sensors to manage irrigation automatically, optimizing water usage for plant growth based on real-time data.
Remote-Controlled Robot: Allows users to control a robot remotely through a smartphone interface, enhancing precision and control in tasks like plant monitoring and maintenance.
