AI Coconut Monitoring and Tagging System

Amrita Vishwa Vidyapeetham’s research centers have been revolutionizing coconut farming with a comprehensive, AI-powered platform designed to optimize monitoring and management. A pilot test is currently underway in the Kollam district of Kerala. This system empowers farmers by improving yield, reducing costs, and enabling data-driven decision-making for more efficient farming practices.

The main features of the system are outlined below:

• Total Coconut Count: Provides real-time, accurate counts of coconuts across regions, aiding in precise decision-making and planning.
• Area-Wise Coconut Count Range: Delivers detailed coconut distribution data by village, enabling targeted resource allocation and better yield management.
• Geo-Tagged Coconut Mapping: Maps coconut plantations precisely on interactive platforms, allowing farmers to visualize patterns, assess plantation density, and identify areas requiring attention as shown in Figure 4. 
• AI Coconut Health Prediction: Utilizes advanced AI and cloud computing to predict potential health issues affecting coconuts, enabling early intervention and minimizing crop losses as shown in Figure 3.
• Drone-Based Data Collection: Employs drones to capture high-resolution imagery for accurate coconut counting, estimating ranges of coconuts present, and assessing their primary health status. A glimpse of the drone in action is shown in Figures 1 and 2.

Figure 1: The drone in action to capture the photo of the coconuts

Figure 2: The view from the drone camera is seen on the right bottom corner and the path of the drone to the different coconut trees are seen on the main screen when the drone is on flight

Figure 3: The AI model output of the coconuts with the health status

Figure 4: This is the dashboard where the geo-tagged coconut trees are visible along with the range of coconuts on the coconut tree with a basic health status of the coconuts