BIN-CT: Urban waste collection based on predicting the container fill level

The activity of waste collection is fundamental for preserving human health and the environment. As the world population increases, so does the waste production, consequently leading to a higher number of professionals involved in the collection activity. The objective of this study was to identify the main causes of accidents in urban waste collection and to verify if the implementation of containers would reduce the number of accidents in the sector. The causes were identified by analyzing accidents in two waste-collection companies for 4 years. Company A had 3,859 employees with 756 registered accident cases, while company B had 2020 workers with 189 cases. In total, it was analyzed 945 accident cases from urban waste collection. One municipality from company A which implemented the highest number of containers was studied thoroughly to verify if the implementation of containers reduces the number of accidents. The analysis shows that the household collection had the highest accident rate, with 65.61%. Sharp materials and falls were the leading causes of accidents, representing 53% in the company A and 62% in the company B. After containers implementation, the number of accidents caused by sharp materials and falls decreased from 37 without the container in 2014, to 18 with the container in 2015, and 11 with the container in 2016. It was concluded that the implementation of containers improves occupational safety and health during the urban cleaning process. Further studies should be conducted in order to improve the working conditions in the urban cleaning sector.

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Electrification of Urban Waste Collection: Introducing a Simulation-Based Methodology for Technical Feasibility, Impact and Cost Analysis

World Electric Vehicle Journal ◽

10.3390/wevj12030122 ◽

2021 ◽

Vol 12 (3) ◽

pp. 122 ◽

Cited By ~ 2

Author(s):

Ricardo Ewert ◽

Alexander Grahle ◽

Kai Martins-Turner ◽

Anne Magdalene Syré ◽

Kai Nagel ◽

...

Keyword(s):

Open Source ◽

Waste Collection ◽

Commercial Vehicles ◽

Urban Waste ◽

Technical Feasibility ◽

Routing Problem ◽

Agent Based ◽

Simulation Based ◽

Multi Agent ◽

Urban Emissions

Electrification is a potential solution for transport decarbonization and already widely available for individual and public transport. However, the availability of electrified commercial vehicles like waste collection vehicles is still limited, despite their significant contribution to urban emissions. Moreover, there is a lack of clarity whether electric waste collection vehicles can persist in real world conditions and which system design is required. Therefore, we introduce a multi-agent-based simulation methodology to investigate the technical feasibility and evaluate environmental and economic sustainability of an electrified urban waste collection. We present a synthetic model for waste collection demand on a per-link basis, using open available data. The tour planning is solved by an open-source algorithm as a capacitated vehicle routing problem (CVRP). This generates plausible tours which handle the demand. The generated tours are simulated with an open-source transport simulation (MATSim) for both the diesel and the electric waste collection vehicles. To compare the life cycle costs, we analyze the data using total cost of ownership (TCO). Environmental impacts are evaluated based on a Well-to-Wheel approach. We present a comparison of the two propulsion types for the exemplary use case of Berlin. And we are able to generate a suitable planning to handle Berlin’s waste collection demand using battery electric vehicles only. The TCO calculation reveals that the electrification raises the total operator cost by 16–30%, depending on the scenario and the battery size with conservative assumptions. Furthermore, the greenhouse gas emissions (GHG) can be reduced by 60–99%, depending on the carbon footprint of electric power generation.

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Data on urban waste collection: The case of the Apulia region in Italy

Data in Brief ◽

10.1016/j.dib.2019.104380 ◽

2019 ◽

Vol 25 ◽

pp. 104380 ◽

Cited By ~ 1

Author(s):

Corrado lo Storto

Keyword(s):

Waste Collection ◽

Urban Waste ◽

Apulia Region

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A financial and environmental evaluation for the introduction of diesel-hydraulic hybrid-drive system in urban waste collection

Transportation Research Part D Transport and Environment ◽

10.1016/j.trd.2014.05.021 ◽

2014 ◽

Vol 31 ◽

pp. 100-109 ◽

Cited By ~ 5

Author(s):

Leonardo Alencar de Oliveira ◽

Marcio de Almeida D’Agosto ◽

Vicente Aprigliano Fernandes ◽

Cíntia Machado de Oliveira

Keyword(s):

Drive System ◽

Waste Collection ◽

Hybrid Drive ◽

Urban Waste ◽

Environmental Evaluation ◽

Hydraulic Hybrid

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METAHEURISTICS FOR THE WASTE COLLECTION VEHICLE ROUTING PROBLEM IN URBAN AREAS

Facta Universitatis, Series: Working and Living Environmental Protection ◽

10.22190/fuwlep2001001s ◽

2020 ◽

pp. 001

Author(s):

Aleksandar Stanković ◽

Danijel Marković ◽

Goran Petrović ◽

Žarko Čojbašić

Keyword(s):

Vehicle Routing ◽

Vehicle Routing Problem ◽

Urban Areas ◽

Heuristic Algorithms ◽

Municipal Waste ◽

Waste Collection ◽

Swarm Optimization ◽

Urban Waste ◽

Routing Problem ◽

Capacitated Vehicle

This paper presents a methodology for solving the municipal waste collection problem in urban areas. The problem is treated as a distance-constrained capacitated vehicle routing problem for municipal waste collection (DCCVRP-MWC). To solve this problem, four meta-heuristic algorithms were used: Genetic algorithm (GA), Simulated annealing (SA), Particle swarm optimization (PSO) and Ant colony optimization (ACO). Vehicle guidance plays a huge role in large transportation companies, and with this test, we propose one of several algorithms for solving urban waste collection problems.

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Regional Disparities in Urban Population Access to Sanitation Services.Case Study: Romania

10.31235/osf.io/fnz7p ◽

2016 ◽

Author(s):

Florin Constantin MIHAI

Keyword(s):

Waste Management ◽

Urban Population ◽

Temporal Analysis ◽

Waste Collection ◽

Urban Waste ◽

Traditional System ◽

Sanitation Services ◽

Different Types ◽

Spatial Temporal Analysis

Abstract: Sanitation services still not fully cover the urban populationand this leads to different types of pollution and affects the urbanlandscape. This paper aims a geographical approach by highlightingterritorial disparities in the Romanian counties regarding the urbanpopulation access to waste collection services and to examine theenvironmental issues. Statistical database processed by ascendinghierarchical cluster analysis are mapped at the level of Romanian countiesachieving a spatial-temporal analysis for the period 2003-2008. The paperalso discusses the current dysfunctions existing in urban waste managementfrom Romania. Development of waste management facilities is in the processof transition from a traditional system based only on landfilling towardsan integrated waste management system which develops the recycling andrecovery of waste generated. Romania as an EU member country must improvethe quality of sanitation services. Each city must provide the fullcollection of municipal waste generated in order to eliminate the illegaldumping.

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Simulation and optimization of dynamic waste collection routes

Waste Management & Research ◽

10.1177/0734242x19833152 ◽

2019 ◽

Vol 37 (8) ◽

pp. 793-802 ◽

Cited By ~ 7

Author(s):

Mohamed Abdallah ◽

Mohamad Adghim ◽

Munjed Maraqa ◽

Elkhalifa Aldahab

Keyword(s):

United Arab Emirates ◽

Carbon Dioxide Emissions ◽

Waste Generation ◽

Waste Collection ◽

Smart Systems ◽

Simulation And Optimization ◽

Knowledge Based ◽

Main Driver ◽

Fill Level ◽

The Impact

Smart waste collection strategies have been developed to replace conventional fixed routes with dynamic systems that respond to the actual fill-level of waste bins. The variation in waste generation patterns, which is the main driver for the profit of smart systems, is exacerbated in the United Arab Emirates (UAE) due to a high expatriate ratio. This leads to significant changes in waste generation during breaks and seasonal occasions. The present study aimed to evaluate a geographic information system (GIS)-based smart collection system (SCS) compared to conventional practices in terms of time, pollution, and cost. Different scenarios were tested on a local residential district based on variable bin filling rates. The input data were obtained from a field survey on different types of households. A knowledge-based decision-making algorithm was developed to select the bins that require collection based on historical data. The simulation included a regular SCS scenario based on actual filling rates, as well as sub-scenarios to study the impact of reducing the waste generation rates. An operation cost reduction of 19% was achieved with SCS compared to the conventional scenario. Moreover, SCS outperformed the conventional system by lowering carbon-dioxide emissions by between 5 and 22% for various scenarios. The operation costs were non-linearly reduced with the incremental drops in waste generation. Furthermore, the smart system was validated using actual waste generation data of the study area, and it lowered collection trip times by 18 to 42% compared to the conventional service. The present study proposes an integrated SCS architecture, and explores critical considerations of smart systems.

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