Smart Cities and Urban Development

In addition to the development of the Internet of Things (IoT), waste management has developed as a major concern. Waste management is a daily task in urban areas that requires substantial amounts of work resources and obstacles to environmental, tax and social factors. However, the results are too inaccurate to be implemented in real systems such as universities and cities. The combination of optimal strategies for waste management with inexpensive IoT architectures has recently become popular. In this article, we propose a new method for implementing waste management management in a vigorous and efficient way by predicting the probability of garbage container overflow. With the help of mechanical learning and graph theory, the system can optimize the quickest method of waste collection. During this period of globalization, researchers found that waste management alone does not guarantee efficient treatment and disposal of a clean, sustainable environment. IoT-based smart waste management solutions and waste management services are provided through technically supported research. Enter the Space Initiative to save time and energy to reduce waste production. Unfortunately, a variety of factors, including the socioeconomic climate of the ambitious country, limits the current use of funds. The main focus of this research is on the development of an Internet-based internet of things for the development of a country. Provides IoT-based solutions for waste collection for Müllcontainers.Create effective solutions for garbage disposal/dumping and human/vehicle management using ML-based methods. This ensures efficient collection, transportation, disposal and recycling of household waste.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.15727317
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Cities and Urban Development

Zenodo (CERN European Organization for Nuclear Research)
Municipal Solid Waste Management
article

Smart Cities and Urban Development

article en

Abstract

In addition to the development of the Internet of Things (IoT), waste management has developed as a major concern. Waste management is a daily task in urban areas that requires substantial amounts of work resources and obstacles to environmental, tax and social factors. However, the results are too inaccurate to be implemented in real systems such as universities and cities. The combination of optimal strategies for waste management with inexpensive IoT architectures has recently become popular. In this article, we propose a new method for implementing waste management management in a vigorous and efficient way by predicting the probability of garbage container overflow. With the help of mechanical learning and graph theory, the system can optimize the quickest method of waste collection. During this period of globalization, researchers found that waste management alone does not guarantee efficient treatment and disposal of a clean, sustainable environment. IoT-based smart waste management solutions and waste management services are provided through technically supported research. Enter the Space Initiative to save time and energy to reduce waste production. Unfortunately, a variety of factors, including the socioeconomic climate of the ambitious country, limits the current use of funds. The main focus of this research is on the development of an Internet-based internet of things for the development of a country. Provides IoT-based solutions for waste collection for Müllcontainers.Create effective solutions for garbage disposal/dumping and human/vehicle management using ML-based methods. This ensures efficient collection, transportation, disposal and recycling of household waste.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 51%
Municipal Solid Waste Management
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Smart Cities and Urban Development · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS