Skip to main content

Digital Garbage Bin Monitoring System (DGBMS)

A Smart Garbage Monitoring and Management Cyber-Physical System

  • Conference paper
  • First Online:
Proceedings of the 6th Brazilian Technology Symposium (BTSym’20) (BTSym 2020)

Abstract

In day-to-day life, all could witness the odor of scattered garbage and unkempt garbage bins because there is no proper time interval schedules and routines, which results in garbage overflow. It also creates hygienic problems, land pollution, and landscape unpleasantness. This scenario demands a system that observes the garbage bin status and provides evidence to the authorities administrating the collection intervals for emptying the bins. The so-called Digital Garbage Bin Monitoring System (DGBMS) is a smart garbage management system relying on the Internet of Things (IoT) technology that can solve this problem. This system monitors the garbage excess and the moisture in the garbage bin. In this project, a sensor network detects the garbage level and the garbage moisture in the dustbin via an Infrared (IR) sensor and then sends evidence to the decision-making party through an IP address. The UNO ARDUINO board interfaces the sensors with the IP address and handles the actuators. An RFID channel constantly monitors the necessary garbage information regarding the different locations of the wastebaskets. Developing countries, especially the rural areas, are severely concerned with these issues that can cause severe health problems among the population. Implementing this solution could contribute to addressing many health-related issues in these countries.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Mahajan K, Chitode JS (2014) Waste bin monitoring system using integrated technology. Int J Innov Res Sci Eng Technol 3(7):14953–14957

    Google Scholar 

  2. Pavithra (2014) Smart trash system: an application using Zigbee. Int J Sci Technol 1(8)

    Google Scholar 

  3. Patil MV, Gajbhiye SM (2015) A review on internet of things based garbage bins detection systems. Int Sci Res (IJSR) 1699–1702. ISSN (Online) 2319-7064

    Google Scholar 

  4. Nithya R, Velumani A (2011) Optimal location and proximity distance of municipal solid waste collection bin using GIS: a case study of Coimbatore City. WSEAS Trans Env Dev 8:107–119

    Google Scholar 

  5. Velumani A (2013) GIS based optimal collection routing model for municipal solid waste: case study in Singanallur, India. Int J Eng Innov Tech (IJEIT) 3(5). ISSN 2277-3754

    Google Scholar 

  6. Bhambulkar AV (2008) Municipal solid waste collection routes optimized with Arc GIS network analyst. Int J Adv Eng Sci Tech 11(1):202–207

    Google Scholar 

  7. Shoba B, Rasappan K (2013) Application of GIS in solid waste management for Coimbatore city. Int J Sci Res Publ 3(10). ISSN 2250-3153

    Google Scholar 

  8. Estrela VV, Hemanth J, Saotome O, Grata EGH, Izario DRF (2019) Emergency response cyber-physical system for flood prevention with sustainable electronics. In: Iano Y, Arthur R, Saotome O, Estrela VV, Loschi HJ (eds) Proceedings of the 3rd Brazilian technical symposium BTSym 2017. Springer, Cham

    Google Scholar 

  9. Anantharam P, Barnaghi P, Thirunarayan K, Sheth A (2015) Extracting city traffic events from social streams. ACM Trans Intell Syst Technol 6:1–27

    Article  Google Scholar 

  10. Estrela VV, Monteiro ACB, França RP, Iano Y, Khelassi A, Razmjooy N (2019) Health 4.0: applications, management technologies and review. Med Tech J 2(4):262–276

    Article  Google Scholar 

  11. De S, Zhou Y, Abad IL, Moessner K (2017) Cyber–physical–social frameworks for urban big data systems: a survey. Appl Sci 7. https://doi.org/10.3390/app7101017

  12. Digiesi S, Facchini F, Mossa G, Mummolo G, Verriello RA (2015) Cyber-based DSS for a low carbon integrated waste management system in a smart city. In: IFAC 2015, vol 48, pp 2356–2361

    Google Scholar 

  13. Zhou Y, De S, Moessner K (2016) Real world city event extraction from Twitter data streams. Proc Comput Sci 98:443–448

    Article  Google Scholar 

  14. McAfee A, Brynjolfsson E (2012) Big data: the management revolution. Harv B Rev 90(10):60–66

    Google Scholar 

  15. Miller S (2014) Collaborative approaches needed to close the big data skills gap. J Org Des 3(1):26–30

    Google Scholar 

  16. Schadt EE (2012) The changing privacy landscape in the era of big data. Mol Syst Biol 8(1):1–3

    Article  Google Scholar 

  17. Schouten P (2013) Big data in health care solving provider revenue leakage with advanced analytics. Healthc Financ Manag 67(2):40–42

    Google Scholar 

  18. Yang B, Castell N, Pei J, Du Y, Gebremedhin A, Kirkevold, Ø (2016) Towards crowd-sourced air quality and physical activity monitoring by a low-cost mobile platform. In: Proceedings of the international Conference on smart homes and health telematics, 25–27, Wuhan, China, pp 451–463

    Google Scholar 

  19. Hemanth DJ, Estrela VV (2017) Deep learning for image processing applications, advances in parallel computing. IOS Press. ISBN 978-1-61499-821-1 (print). 978-1-61499-822-8 (online)

    Google Scholar 

  20. Aviso KB, Mayol AP, Promentilla MAB, Santos JR, Tan RR, Ubando AT, Yu KDS (2018) Allocating human resources in organizations operating under crisis conditions: A fuzzy input-output optimization modeling framework. Resour Conserv Recycl 128:250–258

    Article  Google Scholar 

  21. Estrela VV, Saotome O, Loschi HJ, Hemanth DJ, Farfan WS, Aroma RJ, Saravanan C, Grata EGH (2018) Emergency response cyber-physical framework for landslide avoidance with sustainable electronics. Technologies 6:42

    Article  Google Scholar 

  22. Teo TA, Cho K-H (2016) BIM-oriented indoor network model for indoor and outdoor combined route planning. Adv Eng Inform 30:268–282

    Article  Google Scholar 

  23. Razmjooy N, Mousavi BS, Khalilpour M, Hosseini H (2014) Automatic selection and fusion of color spaces for image thresholding. Sig Image Video Process 8(4):603–614

    Article  Google Scholar 

  24. Mousavi B, Somayeh F, Razmjooy N, Soleymani F (2014) Semantic image classification by genetic algorithm using optimised fuzzy system based on Zernike moments. Sig Image Video Process 8(5):831–842

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yogamoorthi, T. et al. (2021). Digital Garbage Bin Monitoring System (DGBMS). In: Iano, Y., Saotome, O., Kemper, G., Mendes de Seixas, A.C., Gomes de Oliveira, G. (eds) Proceedings of the 6th Brazilian Technology Symposium (BTSym’20). BTSym 2020. Smart Innovation, Systems and Technologies, vol 233. Springer, Cham. https://doi.org/10.1007/978-3-030-75680-2_54

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-75680-2_54

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-75679-6

  • Online ISBN: 978-3-030-75680-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics