However, the growing shortage of agricultural labour has made the adoption of modern technology increasingly necessary. Lightweight fibre and carbon-duty rods for arecanut harvesting, along with dehusking machines, are already being used to make farming activities easier.

Yet, one major challenge has remained largely dependent on manual labour: sorting peeled, boiled and dried arecanuts into four categories based on quality. The process is both labour-intensive and time-consuming.

Seeking to address this traditional challenge through technology, Anarghya P. Holla, a Class 6 student of Seva Bharathi School and daughter of Prasanna Holla and Sanskrit professor Prabha Holla, has developed an impressive prototype of an AI-powered arecanut sorting machine.

The machine, developed as a Class 6 science model, combines artificial intelligence and microcontroller technology to automate the sorting process.

How the AI-powered machine works:

The machine is designed to operate automatically. Four varieties of dried arecanuts - Hasa, Betta, Rashi Idi and Gorabalu - are loaded through a channel at the top.

A star-wheel mechanism at the bottom regulates the movement of the arecanuts, ensuring that they do not get stuck together and are transferred one by one onto a conveyor belt on the left.

As each arecanut moves along the conveyor belt, a smartphone camera positioned at the centre captures its image. A specially developed application and machine-learning model installed on the smartphone then analyse the shape and visual characteristics of the arecanut and identify its category within seconds.

Once the variety is identified, the application sends a digital signal via Bluetooth to an Arduino microcontroller. The Arduino controls the machine's motors and directs a 360-degree rotating robotic motor positioned at the end of the conveyor belt.

The robotic motor immediately turns towards the bowl designated for the particular variety, allowing the arecanut to fall into the correct container.

Since the entire process can be controlled through the smartphone application, the machine is designed to be simple and convenient for farmers to operate.

Scope for large-scale agricultural use:

Although the current machine is a small prototype developed primarily for demonstration purposes, its underlying concept has considerable potential for practical application in agriculture.

With further development using industrial vision cameras, high-speed processors and air-blower technology, the machine could potentially be scaled up to sort hundreds of kilograms of arecanut per hour.

Anarghya P. Holla's innovative attempt to address a common agricultural challenge with advanced technology offers a promising glimpse into the future of farming in the Malnad region. The project also highlights how young students can apply artificial intelligence and automation to develop solutions for real-world problems.