Research Article Open Access

Bin Bay: An Optimized Smart Waste Disposal System for a Sustainable Urban Life using LSTM and Fog Computing

Shiny Duela1, Dioline Sara2 and Prabavathi3
  • 1 Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram Campus, India
  • 2 Department of Electrical and Electronics Engineering, Gitam School of Technology, India
  • 3 Department of Information Technology, Sri Sairam Institute of Technology, India

Abstract

To create green and smart cities, a smart and planned WasteManagement System (WMS) is a vital requirement. With the increase in the urbanpopulation and service delivery difficulties, smart cities are integratingtechnologies such as smart waste bins and Radio Frequency Identification (RFID)tags into their day-to-day operations to make solid waste management andcontrol more effective. Fog computing in waste management is becoming common insmart utilities as it provides benefits like a minimal amount of data sent tothe cloud, reduced bandwidth, and Low data latency. The proposed work focuseson residential customers using waste collection services. Smart Waste DisposalSystem for a sustainable urban life using Fog Computing called Bin Bay isproposed to optimize the collection of waste with the shortest path usingGoogle Map API support from Fog Layer for which four major parameters areconsidered namely: The distance between truck and bin, the status of the bin(what percentage of it is filled), the capacity of the truck and the positionof the truck. The Bin Bay model helps to savetime by determining the most efficient waste pickup route for waste disposal.The RFID Reader and Scanner help in updating the fog nodes with the date, time,and volume of trash pickup which could be further analyzed to keep on-timeservice delivery. Also, predictions on future waste growth shall be determinedby doing in-depth analysis in the cloud using LSTM which will intelligentlylearn and predict the waste patterns based on the summary submitted by theaggregate node of the fog layer and since the optimized routes lead to lessfuel consumption, CO2 emission also shall be greatly reduced.

Journal of Computer Science
Volume 18 No. 11, 2022, 1110-1120

DOI: https://doi.org/10.3844/jcssp.2022.1110.1120

Submitted On: 29 May 2022 Published On: 16 November 2022

How to Cite: Duela, S., Sara, D. & Prabavathi, (2022). Bin Bay: An Optimized Smart Waste Disposal System for a Sustainable Urban Life using LSTM and Fog Computing. Journal of Computer Science, 18(11), 1110-1120. https://doi.org/10.3844/jcssp.2022.1110.1120

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Keywords

  • Waste Management
  • Internet of Things
  • Fog Computing
  • Supervised Learning Algorithm
  • Sensors
  • CO2 Emission