In a step toward leveraging technology for sustainable campus living, DWaste, an AI-powered waste management application, collaborated with Department of Artificial Intelligence students to create a comprehensive waste. This partnership brings together academic expertise and practical innovation, aiming to address waste segregation challenges in Nepal.
The collaboration focused on capturing real-world waste data from Panchkhal, Nepal, using mobile cameras to photograph different types of waste in everyday settings. These images are the combined results of the students capturing waste items and the pilot recycling campaign. Each image was annotated using open-source data labeling tools like Label Studio and Annotate Lab to identify waste categories such as paper, plastic, metal, and glass, providing a rich dataset for training AI models.
The resulting WasteSense Dataset is a first of its kind in Nepal, offering high-quality, annotated images for AI research in waste management near campuses. The dataset enables the development of smarter algorithms capable of automatically identifying and sorting waste, empowering initiatives like DWaste to provide real-time guidance on proper waste disposal.
This collaboration is not just about technology, it’s about community impact. By combining students’ research capabilities with DWaste’s field operations, the project provides an opportunity to educate students, local authorities, and residents on sustainable waste practices, while also creating a resource that can be used by AI researchers globally.