Detection and Classification of Microwaste in Temple Environment

DOI

10.2991/978-94-6239-650-0_5How to use a DOI?

Keywords

YOLOv8; Object Detection; Deep Learning; Temple Micro Waste Management; Environmental Sustainability

Abstract

Waste management remains a significant urban challenge, particularly in high-footfall areas such as temples, where large volumes of offerings and ritual materials accumulate daily. Currently, temple waste is primarily managed manually, with workers separating and disposing of debris by hand. However, no automated system exists that can efficiently identify, classify, and segregate mixed temple waste—particularly micro-waste—without human interaction. This gap emphasizes the necessity for an automated smart waste-segregation system based on computer vision and deep learning. The proposed system is trained on four critical classes—floral waste (leaves and flowers), plastic wrappers, plastic caps, and ritual waste (coconut shells and incense sticks)—which are frequently observed in religious environments and are among the major contributors to drainage problems. The finalization of the ML model is accomplished by comparing a few established image-processing approaches, such as KNN, SVM, and classical CNN-based classifiers, YOLOv8 to assess their performance on diverse temple-waste photos. However, these systems battled with issues like overlapping objects, micro-waste detection, and excessive background clutter. According to the results, YOLOv8 outperformed other algorithms in terms of detection accuracy and localization precision. Experiments with our proprietary dataset demonstrate that the model can accurately identify and localize small-scale waste items in congested and complicated temple settings. The proposed technique not only presents a new application domain for YOLOv8, but it also provides a useful tool for enhancing cleanliness and promoting sustainable waste management practices in religious and cultural settings.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Vaishnavi Dhane
AU  - Purva Chaudhari
AU  - Karpagavalli Subramanian
PY  - 2026
DA  - 2026/04/20
TI  - Detection and Classification of Microwaste in Temple Environment
BT  - Proceedings of the Conference on Technologies for Future Cities (CTFC 2025)
PB  - Atlantis Press
SP  - 56
EP  - 74
SN  - 3005-155X
UR  - https://doi.org/10.2991/978-94-6239-650-0_5
DO  - 10.2991/978-94-6239-650-0_5
ID  - Dhane2026
ER  -