Skip to main content

Advertisement

SpringerLink
Log in

Optimal Management of Solid Waste in Smart Cities using Internet of Things

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Smart cities are benefiting from Internet of Things (IoT) in optimizing their services. Smart waste management systems can provide substantial savings in time, monetary cost, trip length and utilization of vehicles. In this paper, we use the IoT technology to determine the schedule and pathways of waste collection trucks. We discuss our previous work on single truck routing algorithm and develop and simulate two-step heuristic algorithm multiple trucks routing algorithm (MITRA) to discover the ideal route for the management waste fleet, using smart dumpsters and agent-based models. The smart dumpsters are equipped with the sensors that measure levels of waste and a controller to send updates to the central management system using wireless network. Our target is to improve the waste collection process by reducing the congestion on the road, the service time spent and the overall trip length. We developed the MITRA algorithm applying the timing constraint on capacitated vehicle routing problem. MITRA divides the metropolitan area into a set of sectors each containing a number of dumpsters. We guide the routing in waste collection by selecting the order of sectors to be served then then apply genetic algorithm to compute the optimal route to serve the full dumpsters in the sector.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Wyld, D. (2010). Taking out the trash (and the Recyclables): RFID and the handling of municipal solid waste. International Journal Of Software Engineering & Applications (IJSEA),1(1), 1–13.

    Google Scholar 

  2. P. o. C. City of Baton Rouge: Parish of East Baton Rouge. (Online). Available: http://www.brgov.com/. Retrieved 17 Feb 2016.

  3. Hong, I., Park, S., Lee, B., Lee, J., & Park, S. (2014). IoT-based smart garbage system for efficient food waste management. The Scientific World Journal, 2014, 1–13.

    Google Scholar 

  4. Schindler, H. R., Schmalbein, N., Steltenkamp, V., Cave, J., Wens, B., & Anhalt, A. (2012). SMART TRASH: Study on RFID tags and the recycling industry. Santa Monica: RAND Corporation.

    Google Scholar 

  5. Nielsen, I., Lim, M. L., & Nielsen, P. (2010). Optimizing supply chain waste management through the use of RFID technology. In IEEE international conference on RFID-technology and applications (RFID-TA). China.

  6. Akyildiz, I., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Elseveir Journal of Computer Network,38(4), 393–422.

    Article  Google Scholar 

  7. Bashir, A., Banday, S. A., Khan, A. R., & Shafi, M. (2013). Concept, design and implementation of automatic waste management system. International Journal on Recent and Innovation Trends in Computing and Communication,1(7), 604–609.

    Google Scholar 

  8. Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. The Management Science Journal,6(1), 80–91.

    MathSciNet  MATH  Google Scholar 

  9. Mamat, N. J. Z., Jaaman, S. H., & Ahmad, R. R. (2017). Covariance versus correlation in capacitated vehicle routing problem–investment fund allocation problem. In 4th International conference on mathematical sciences—Mathematical sciences: championing the way in a problem based and data driven society, ICMS 2016. Malaysia.

  10. Song, L., Gu, H., & Huang, H. (2012). A lower bound for the adaptive two-echelon capacitated vehicle routing problem. Computers & Operations Research,39(12), 3185–3199.

    Article  MathSciNet  Google Scholar 

  11. Pollaris, H., Braekers, K., Caris, A., Janssens, G. K., & Limbourg, S. (2017). Iterated local search for the capacitated vehicle routing problem with sequence-based pallet loading and axle weight constraints. Networks, An International Journal,69(3), 304–316.

    MathSciNet  Google Scholar 

  12. Uchoa, E., Pecin, D., Pessoa, A., Poggi, M., Vidal, T., & Subramanian, A. (2017). New benchmark instances for the capacitated vehicle routing problem. European Journal of Operational Research,257(3), 845–858.

    Article  MathSciNet  Google Scholar 

  13. Pisinger, D., & Ropke, S. (2007). A general heuristic for vehicle routing problems. Elsevier Journal of Computers and Operations Research,34(8), 2403–2435.

    Article  MathSciNet  Google Scholar 

  14. Schrimpf, G., Schneider, J., Stamm-Wil, H., & Dueck, G. (2000). Record breaking optimization results using the ruin and recreate principle. Journal of Computational Physics,159(2), 139–171.

    Article  MathSciNet  Google Scholar 

  15. REN, C. (2012) Applying genetic algorithm for capacitated vehicle routing problem. In 2nd International conference on electronic & mechanical engineering and information technology (EMEIT-2012).

  16. Mohammed, M. A., Ahmad, M. S., & Mostafa, S. A. (2012) Using genetic algorithm in implementing capacitated vehicle routing problem. In 2012 International conference on computer & information science (ICCIS).

  17. Nazif, H., & Lee, L. S. (2012). Optimised crossover genetic algorithm for capacitated vehicle routing problem. Applied Mathematical Modelling,36(5), 2110–2117.

    Article  MathSciNet  Google Scholar 

  18. Shahab, M. L., Utomo, D. B., & Irawan, M. I. (2005). Decomposing and solving capacitated vehicle routing problem (CVRP) using two-step genetic algorithm (TSGA). Journal of Theoretical and Applied Information Technology,87(3), 461–468.

    Google Scholar 

  19. Holland, J. H. (1995). Hidden order: How adaptation builds complexity. Redwood City: Addison-Wesley.

    Google Scholar 

  20. Borshchev, A. (2013). The big book of simulation modeling: Multimethod modeling with AnyLogic 6. Chicago: AnyLogic North America.

    Google Scholar 

  21. Idwan, S., Zubairi, J., & Mahmood, I. (2016) Smart solutions for smart cities: Using wireless sensor network for smart dumpster management. In Proceedings on IEEE CTS Conference 2016.

  22. Mahmood, I., Zubairi, J. A., Idwan, S., & Matar, I. (2018) Experiments in routing vehicles for municipal services. In International conference on high performance computing & simulation.

Download references

Author information

Authors and Affiliations

  1. Computer Science and Applications Department, Faculty of Prince Al-Hussein Bin Abdallah II For Information Technology, The Hashemite University, Zarqa, Jordan

    Sahar Idwan

  2. Center for Research in Modeling and Simulation (Crimson), School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad, Pakistan

    Imran Mahmood

  3. Computer and Information Sciences Department, College of Liberal Arts and Sciences, State University of New York at Fredonia, Fredonia, NY, 14063, USA

    Junaid Ahmed Zubairi

  4. Software Engineering Department, University of Petra, Amman, Jordan

    Izzeddin Matar

Authors
  1. Sahar Idwan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Imran Mahmood
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junaid Ahmed Zubairi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Izzeddin Matar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sahar Idwan.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Idwan, S., Mahmood, I., Zubairi, J.A. et al. Optimal Management of Solid Waste in Smart Cities using Internet of Things. Wireless Pers Commun 110, 485–501 (2020). https://doi.org/10.1007/s11277-019-06738-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-06738-8

Keywords

Search

Navigation