Innovative Waste Management: The Efficiency of IoT-Enabled Smart Bins

This study is focused on understanding the operation of IoT-based smart bins under a waste management framework that is used in urban setups. The forefront is the objective of tackling the ubiquitous challenge of space garbage and increasing cost inefficiency in highly urbanized areas. This project seeks to assess the capacity of the smart container to enhance the trash pickup efficiency, diminish the environmental impact, and satisfy the community’s required service in a municipal setting by incorporating important features like real-time monitoring and the tracking of the dustbin level. This way implies forming smart bins equipped with ultrasonic, temperature, weight and tilt detectors. These bins, as well as the system architecture that is programmed to receive, transmit and store data, come with a computer software application that is equipped to assemble, encode and decipher data. While a pilot project was carried out in the city within six months, the researcher collected empirical data about garbage buildup patterns, detection accuracy of sensors, reliability system, and the way of optimizing collection routes. The experimental results give the 50% improvement in collection efficiency worth mentioning since now the collection time decreases to two hours against the previous 8 hours. The operational cost decreased by 25%. However, the instances of overspill decreasing by 83.3% indicate the system’s utility in urban waste management. However, a carbon emission impact assessment indicates a significant reduction in carbon emissions that may be directly linked to the optimization of routes for transporting the collections. One of the most important things that had a major effect was the fact that satisfaction ratings among the citizens rose by 1.5 and reached the level of 8.5 on a scale of 10. Indeed, the figures imply that the residents of the city saw an improvement of 30.7% in the way their waste is managed as a result of this program.

Authors

Institutions

Publication Details

Published
2024-08-08
DOI
https://doi.org/10.1109/iccpct61902.2024.10672653
Citations
13
Primary Topic
Internet of Things and AI
Type
article
Field-Weighted Citation Impact
10.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Innovative Waste Management: The Efficiency of IoT-Enabled Smart Bins

Shiva Mehta, Abhinav Rathour
13 citations
Internet of Things and AI
10.13
article

Innovative Waste Management: The Efficiency of IoT-Enabled Smart Bins

Shiva Mehta, Abhinav Rathour
article en
13 citations

Abstract

This study is focused on understanding the operation of IoT-based smart bins under a waste management framework that is used in urban setups. The forefront is the objective of tackling the ubiquitous challenge of space garbage and increasing cost inefficiency in highly urbanized areas. This project seeks to assess the capacity of the smart container to enhance the trash pickup efficiency, diminish the environmental impact, and satisfy the community’s required service in a municipal setting by incorporating important features like real-time monitoring and the tracking of the dustbin level. This way implies forming smart bins equipped with ultrasonic, temperature, weight and tilt detectors. These bins, as well as the system architecture that is programmed to receive, transmit and store data, come with a computer software application that is equipped to assemble, encode and decipher data. While a pilot project was carried out in the city within six months, the researcher collected empirical data about garbage buildup patterns, detection accuracy of sensors, reliability system, and the way of optimizing collection routes. The experimental results give the 50% improvement in collection efficiency worth mentioning since now the collection time decreases to two hours against the previous 8 hours. The operational cost decreased by 25%. However, the instances of overspill decreasing by 83.3% indicate the system’s utility in urban waste management. However, a carbon emission impact assessment indicates a significant reduction in carbon emissions that may be directly linked to the optimization of routes for transporting the collections. One of the most important things that had a major effect was the fact that satisfaction ratings among the citizens rose by 1.5 and reached the level of 8.5 on a scale of 10. Indeed, the figures imply that the residents of the city saw an improvement of 30.7% in the way their waste is managed as a result of this program.

Chitkara University (IN)
Industry, innovation and infrastructure, Responsible consumption and production
Openalex Percentile: Top 2%
Internet of Things and AI
10.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Innovative Waste Management: The Efficiency of IoT-Enabled Smart Bins — Shiva Mehta, Abhinav Rathour · (2024) | TGRS Research Map | TGRS