Sustainability Assistant Using Natural Language Processing
1.B Mamatha (CSE) Assistant Professor at Geethanjali College of Engineering and Technology, Hyderabad, India botlamamatha.cse@gcet.edu.in
2. Veena Siva (CSE), Student at Geethanjali College of Engineering and Technology, Hyderabad, India 21r11a05q7@gcet.edu.in
3. Chatla Sneha (CSE), Student at Geethanjali College of Engineering and Technology, Hyderabad, India 21r11a05m3@gcet.edu.in
4. Shruthi Stumpum (CSE), Student at Geethanjali College of Engineering and Technology, Hyderabad, India 21r11a05q9@gcet.edu.in
Abstract
The Sustainability Assistant App addresses the challenge of effective waste handling in a time of growing environmental awareness. Many households struggle with proper recycling and creative reuse of items, leading to wasted opportunities. Current recycling apps often provide generic advice, lacking personalized solutions for specific items and conditions. They also fail to engage users in creative waste reduction methods. A key issue is the absence of NLP in these systems, limiting their ability to offer tailored suggestions. Most apps focus only on traditional recycling, overlooking the potential for creative repurposing and DIY sustainability projects.
The proposed Sustainability Assistant App addresses these challenges by leveraging NLP to process user queries and provide optimized, personalized recycling and reusing methods based on the specific type and condition of household items. By analyzing the user's description, the app offers the most suitable recycling method, ensuring efficiency in waste management. Furthermore, the app introduces a unique Handi-Hobby Module, which empowers users to reduce waste creatively by offering visual and practical eco-friendly DIY projects. This module encourages innovative reuse, such as turning onion peels into a natural dye or making bioplastic bags at home, making sustainability more engaging and accessible. This dual approach of precise recycling recommendations and creative repurposing helps users participate actively in environmental preservation, fostering a deeper culture of sustainability.
Index Terms – Kotlin, TornadoFX, Natural Language Processing (NLP), SQLite, JavaFX, Waste Management, Recycling, DIY Projects, Sustainability Education, Desktop Application
