ItemConference Paper

Proposing an AI-Enabled Waste Segregation System for Domestic Settings

Title
Proposing an AI-Enabled Waste Segregation System for Domestic Settings
Creator
Rao, Devnarayan G.; Sangeetha, G.; Sandeep, J.; Sreeja, C.S.; Vincent, Agnes Nalini; Mary, Teena
Description
This paper proposes an innovative AI-based system for automated domestic waste segregation. Utilizing Teachable Machine and MobileNet, the system accurately categorizes waste into dry and wet components, laying the foundation for sustainable waste management practices. Embedded in a Raspberry Pi 4, the system integrates real-time image processing with various sensors to streamline the sorting process. While the model has been simulated due to budgetary constraints, future implementation envisions real-world application. Potential advancements include expanding the dataset, enabling multi-category waste classification, and exploring low-power alternatives. This research contributes to the evolving landscape of smart waste management, addressing environmental sustainability and the pressing need for automated, efficient waste segregation at the domestic level. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Source
Lecture Notes in Networks and Systems;Volume;1378 LNNS;pp.21-33
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Artificial intelligence for sustainability; IoT; Smart waste management; Transfer learning; Waste segregation
Coverage
Rao D.G., Department of Computer Science, Christ University, Bangalore, India; Sangeetha G., Department of Computer Science, Christ University, Bangalore, India; Sandeep J., Department of Computer Science, Christ University, Bangalore, India; Sreeja C.S., Department of Computer Science, Christ University, Bangalore, India; Vincent A.N., Department of Information Technology, AMITY Institute of Higher Education, Quatre Bornes, Mauritius; Mary T., Department of Computer Science, Christ University, Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 23673370; ISBN: 978-981965780-3;
Format
online
Language
English
Type
Conference paper

Citation

Rao, Devnarayan G.; Sangeetha, G.; Sandeep, J.; Sreeja, C.S.; Vincent, Agnes Nalini; Mary, Teena, “Proposing an AI-Enabled Waste Segregation System for Domestic Settings,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 21, 2026, https://archives.christuniversity.in/items/show/25574.

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