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Data analytics framework for smart waste management optimisation: A key to sustainable future for councils and communities

conference contribution
posted on 2024-09-30, 04:29 authored by S Ahmed, S Mubarak, Santoso WibowoSantoso Wibowo, J Tina Du
Smart waste management systems (SWMS), including various technologies, including routing, scheduling, infrastructure, and the Internet of Things (IoT), are used to enhance the efficiency and automation of waste management processes. The availability of big data generated by IoT sensors has the potential to significantly improve waste management systems by providing valuable insights and enabling automation. This study presents a data analytics framework that supports decision-makers in implementing, monitoring, and optimising SWMS. The framework utilises IoT sensor data and employs data analytic techniques to analyse and predict municipal bins’ waste generation trends and patterns. Finally, the framework demonstrates the capability to forecast waste generation, leading to the development of a sustainable environment and efficient managerial administration in waste management.

History

Editor

Strauss C; Amagasa T; Kotsis G; Tjoa A; Khalil I

Volume

14147 LNCS

Start Page

134

End Page

139

Number of Pages

6

Start Date

2023-08-28

Finish Date

2023-08-30

eISSN

1611-3349

ISSN

0302-9743

ISBN-13

9783031398209

Location

Penang, Malaysia

Publisher

Springer

Place of Publication

Cham, Switzerland

Peer Reviewed

  • Yes

Open Access

  • No

Era Eligible

  • Yes

Name of Conference

34th International Conference, DEXA 2023

Parent Title

Database and Expert Systems Applications: 34th International Conference, DEXA 2023 Penang, Malaysia, August 28–30, 2023 Proceedings, Part II

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