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Efficient IoT-Assisted Waste Collection for Urban Smart Cities.

Sangrez Khan1, Bakhtiar Ali2, Abeer A K Alharbi3

  • 1Department of Electrical Engineering, École de Technologie Supérieure, Montréal, QC H3C 1K3, Canada.

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Summary
This summary is machine-generated.

This study introduces a novel knapsack-based technique to optimize urban waste collection. The method efficiently disposes of waste, significantly increasing toxic waste collection by up to 47% and reducing collection visits.

Keywords:
IoTsmart citywaste collectionwaste management

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Area of Science:

  • Environmental Science
  • Urban Planning
  • Operations Research

Background:

  • Urban waste management faces significant challenges due to population growth and strained collection/disposal infrastructure.
  • Current waste collection systems are inefficient, hampered by limited resources like trucks and dumping points.
  • There is a critical need for technology-driven solutions and community engagement to address global waste management issues.

Purpose of the Study:

  • To develop an efficient waste collection strategy that maximizes the utilization of existing transportation capacity.
  • To prioritize and maximize the disposal of toxic waste within urban environments.
  • To reduce the overall number of waste collection trips and associated operational costs.

Main Methods:

  • A novel knapsack-based technique was developed to optimize the loading of waste bins onto collection trucks.
  • Internet of Things (IoT) sensors were integrated to assess waste volume and toxicity levels in bins.
  • The technique considers geographic locations, waste amount, and toxicity to maximize truck capacity utilization and toxic waste collection.

Main Results:

  • The proposed knapsack-based technique demonstrated superior performance compared to conventional waste collection methods.
  • High-priority toxic waste collection improved by up to 47% using the novel technique.
  • The number of waste collection visits was significantly reduced, leading to potential equipment cost recovery within a year.

Conclusions:

  • The proposed knapsack-based technique offers a highly efficient and effective solution for urban waste management.
  • Integrating IoT sensors and optimization algorithms can substantially improve toxic waste collection and resource utilization.
  • This approach presents a viable strategy for reducing operational costs and enhancing the sustainability of urban waste management systems.