Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM9049
Volume:
5 |
6 |
Jun 2021
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This project presents an IoT and Machine Learning (ML)-powered system designed to revolutionize traditional municipal waste collection practices by enabling real-time monitoring and dynamic route optimization. The proposed solution utilizes ultrasonic sensors placed within waste bins to accurately measure fill levels and wirelessly transmit this data via a central gateway to a cloud-based platform. The system’s core innovation lies in its integration of a dynamic route optimization algorithm, which processes the real-time fill-level data. Instead of following fixed, inefficient schedules, this algorithm generates the most efficient collection route for the garbage fleet, targeting only those bins that are near capacity. This approach significantly reduces collection frequency and vehicle mileage.
KEYWORDS
Publication Date
11/24/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
1
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...