Intelligent waste management: Maximize profits and minimize waste using IOT and AI

The article presents an innovative waste Container Management System for restaurants which incorporates the IoT and AI to increase effectiveness and decrease waste. Through smart dust bins that has embedded sensors and machine learning, the system can classify and measure food waste effectively in real time. This innovation affords the restaurants precise data on the waste cycles as well as the stock control to avoid over-ordering. The success of the proposed system can be also attested through high classification accuracy of food waste and the usage of models such as MLP which reached up to 96.44%. Through these technologies, food wastage, and operational costs are reduced while at the same time ensuring sustainable practices that have a reduced impact on the environment are employed. In general, the system supports better decision-making and increased profitability in the restaurant business concerning waste management and supply chain management. This optimised approach does away with the wastage which would have reduced revenues, consequently improving the business’ financial performance.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-30
DOI
https://doi.org/10.5281/zenodo.15012295
Primary Topic
Food Waste Reduction and Sustainability
Type
article
Field-Weighted Citation Impact
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article

Intelligent waste management: Maximize profits and minimize waste using IOT and AI

Zenodo (CERN European Organization for Nuclear Research)
Food Waste Reduction and Sustainability
article

Intelligent waste management: Maximize profits and minimize waste using IOT and AI

article en

Abstract

The article presents an innovative waste Container Management System for restaurants which incorporates the IoT and AI to increase effectiveness and decrease waste. Through smart dust bins that has embedded sensors and machine learning, the system can classify and measure food waste effectively in real time. This innovation affords the restaurants precise data on the waste cycles as well as the stock control to avoid over-ordering. The success of the proposed system can be also attested through high classification accuracy of food waste and the usage of models such as MLP which reached up to 96.44%. Through these technologies, food wastage, and operational costs are reduced while at the same time ensuring sustainable practices that have a reduced impact on the environment are employed. In general, the system supports better decision-making and increased profitability in the restaurant business concerning waste management and supply chain management. This optimised approach does away with the wastage which would have reduced revenues, consequently improving the business’ financial performance.

Zenodo (CERN European Organization for Nuclear Research)
Engineering Software Research and Development (United States) (US)
Responsible consumption and production
Openalex Percentile: Top 57%
Food Waste Reduction and Sustainability
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Intelligent waste management: Maximize profits and minimize waste using IOT and AI · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS