Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Urban waste generation has increased significantly due to rapid population growth and lifestyle changes. Traditional collection systems based on fixed schedules lead to bin overflow, inefficient routing, fuel wastage, and poor hygiene. This project proposes a Smart Waste Management System that simulates IoT-enabled bins, monitors fill levels, and dispatches trucks automatically when thresholds are exceeded. Route optimization is performed using OSRM, ensuring realistic road navigation and improved efficiency. A comprehensive literature review highlights existing IoT-based smart bins [4], sensor-based data-analysis techniques [2], multi-agent simulations [3], and optimization strategies [5], aligning this work with modern smart-city requirements. The system demonstrates reduced operational cost, improved responsiveness, and suitability for large-scale urban deployment.
"SMART WASTE MANAGEMENT SYSTEM WITH TRUCK DEPOT ROUTE OPTIMIZATION", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.b46-b49, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511107.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator