WasteMiner: An Efficient Waste Collection System for Smart Cities Leveraging IoT and Data Mining Technique

Tarannum Shaila Zaman, Tariqul Islam, Sucharan Reddy Vadla, Uday Kiran Rangu

Research output: Chapter in Book/Entry/PoemConference contribution

1 Scopus citations

Abstract

An efficient and automated waste collection system can facilitate the overall waste management of any smart city. Many IoT-based techniques are developed to make waste collection system optimized and autonomous. However, none of them considers any situation when IoT-based technique could fail to transfer data due to any unforeseen reasons (e.g, natural calamity, poor maintenance, device failure, connection outage, etc.). In this work, we propose an IoT-based technique named WasteMiner for collecting waste in an efficient way where we also calculate the shortest distances between the waste bins for making the system fuel and time efficient. Moreover, we collect data of waste levels of the bins and apply data mining technique to the collected data for extracting important information. This information help us collecting waste in an efficient way in the case of any system failure in the IoT-based network of WasteMiner. Our experimental results show that WasteMiner is effective and efficient when, i) IoT-based system functions properly, ii) any system failure or communication problem occurs, and iii) if scaled up properly, can be applicable to real-world systems by integrating WasteMiner as one of the key smart city components.

Original languageEnglish (US)
Title of host publicationSoutheastCon 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages504-510
Number of pages7
ISBN (Electronic)9781665476119
DOIs
StatePublished - 2023
Externally publishedYes
Event2023 IEEE SoutheastCon, SoutheastCon 2023 - Orlando, United States
Duration: Apr 1 2023Apr 16 2023

Publication series

NameConference Proceedings - IEEE SOUTHEASTCON
Volume2023-April
ISSN (Print)1091-0050
ISSN (Electronic)1558-058X

Conference

Conference2023 IEEE SoutheastCon, SoutheastCon 2023
Country/TerritoryUnited States
CityOrlando
Period4/1/234/16/23

Keywords

  • Data Mining
  • Frequent Itemsets
  • IOT
  • Shortest Distance
  • Waste collection

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Signal Processing

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