Project Bin is a UWCSEA East Initiative aimed at reducing food waste in canteens, with a specific focus on Singapore's school and hawker centers. Our project is dedicated to addressing the global issue of food waste, particularly in canteens and similar food-serving establishments.
We are committed to minimizing food waste in Singapore's 180 schools and 115 hawker centers. Our approach combines data analytics and behavioral economics to understand and reduce food wastage.
Our strategy to combat food waste includes:
- Tracking and Classifying Plate Waste: We use AI-powered cameras to identify and categorize waste in bins.
- Data Analysis: Analyzing data to understand behavioral patterns and trends in wastage.
- Implementing Changes in Kitchens: Collaborating with kitchens to apply changes targeting the root causes of waste. We use principles of behavioral economics to influence consumer choices.
- Publishing Findings: Sharing insights with consumers through reports and interactive platforms to educate them about their consumption habits.
Our goal is not only to reduce costs for food vendors but also to educate consumers, creating a collaborative network to address the multifaceted issue of food waste.
Our team is currently focused on data collation and labeling to improve our machine learning model's accuracy. We have chosen the YOLO v7 model for its efficiency in real-time object detection. Our efforts are centered on training this model to recognize various food items, thereby increasing its specificity in waste classification.
- YOLO v7
- ReactJS
- MongoDB
- Flask
- OpenAI API
- Hanming Ye, Anika Sharma, Aditya Agrawal and Antoine Lee