About us
Our App - BinScan
BinScan works by using an AI model trained on Google Teachable Machine to recognise waste items through a camera in real time. When a waste item is detected, the app classifies it into one of three categories — Recyclable, Organic, or General Waste — in under one second. The result is instantly displayed on screen, showing exactly which bin to use. At the same time, a connected Arduino board lights up the correct LED — green, red, or blue — giving a clear and immediate physical signal.
See BinScan in Action
BinScan makes waste sorting instant and effortless. Simply point your camera at any waste item and our AI identifies it in under one second — displaying the correct bin on screen and lighting up the matching LED on the Arduino board. No guessing, no confusion, just a smarter and greener way to sort waste every single day.
BinScan AI
Meet our dedicated team
Dedicated students driving our success in sustainability
Sheshnag Sunil
Class IX F
Sheshnag is the lead developer of BinScan and the driving force behind the project. He built the web application, integrated the AI model, and connected the Arduino hardware. His passion for technology and sustainability inspired the entire idea of using AI to solve real-world waste sorting problems in Oman.
Anashwar Nitin Panicker
Class IX A
Anashwar is the AI specialist of the team. He was responsible for training the machine learning model using Google Teachable Machine, collecting the waste image data, and improving the model's accuracy. His interest in artificial intelligence and environmental issues made him the perfect person to lead the AI side of BinScan.
Arjun Deepak Nair
Class IX F
Arjun designed and built the Arduino LED circuit, handled all the wiring and breadboard connections, and made sure the physical LEDs responded correctly to the AI output. His hands-on technical skills brought the project from a screen to a real-world working device.
Steffan Jude Rocha
Class IX A
Steffan is the designer and presenter of the team. He created the Canva website, designed the project poster, and prepared the presentation slides. He also researched the environmental impact of waste missorting in Oman and connected the project to Oman Vision 2040, making sure the story behind BinScan was as strong as the technology.