the internet of things aids waste management case study

Internet of Things & Waste Management

• First Online: 30 March 2022

Cite this chapter

• Vanda Klučariková 4  

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 420))

586 Accesses

The Internet of Things and its applications have been exponentially coming to the forefront over the past years. In our highly complex present-day world, it becomes exponentially more and more important to consider large amounts of data to make good decisions and operate efficiently. And because humans are not themselves able to do so, we must turn to technologies such as the IoT. Waste management is among the areas where IoT has a potential of making a significant difference to our everyday lives. To ease understanding of the concept and its possible applications to waste management, we propose a comprehensive overview of IoT technology, its architecture, networks, and several examples of smart waste management applications.

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

Access this chapter

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or Ebook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime
• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Application of Internet of Things (IoT) in Waste Management

Critical Analysis of Intelligent IoT in Creating Better Smart Waste Management and Recycling for Sustainable Development

Leveraging AI and IoT for Sustainable Waste Management

Sensoneo Smart Waste Management: Smart waste management using IOT—real benefits of Sensoneo. Youtube (2021). Retrieved from: https://www.youtube.com/watch?v=qsfr_HNdHZo&list=PLg3hnRX6v-L74xpChdyVzOMVLPzzUd7wJ . Accessed 12 July 2021

Pardini, K., et al.: A smart waste management solution geared towards citizens. Sensors 20 (8) (2020)

Google Scholar  

Rose K., Eldridge S., Chapin L.: The Internet of Things: An Overview. Understanding the Issues and Challenges of a More Connected World. The Internet Society, Geneva, Switzerland (2015)

Romkey, J.: Toast of the IoT: the 1990 interop internet toaster. IEEE Consumer Electron. Mag. 6 (1), 116–119 (2017)

Article   Google Scholar  

Hanes, D., et al.: IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things. Cisco Press, Indianapolis, USA (2017)

Fell, M.: Roadmap for the emerging “Internet of Things”. Carré & Strauss (2014)

ETSI: ETSI worldwide (2021). Retrieved from: https://www.etsi.org/about/etsi-worldwide . Accessed 15 July 2021

CISCO: The internet of things reference model (2014). Retrieved from: http://cdn.iotwf.com/resources/71/IoT_Reference_Model_White_Paper_June_4_2014.pdf

El Hakim, A.: Internet of Things (IoT) System Architecture and Technologies, White Paper (2018)

Weinstein, R.: RFID: a technical overview and its application to the enterprise. IT Profess. 7 (3), 27–33 (2005)

EMnify: Globalized M2M & IoT connectivity. Retrieved from: https://bit.ly/2Ud9w9k

Ricquebourg, V., et al.: The smart home concept: our immediate future. In: 2006 1ST IEEE International Conference on E-Learning in Industrial Electronics, pp. 23–28 (2006)

Dameri, R.P.: Searching for Smart City definition: a comprehensive proposal. Int. J. Comput. Technol. 11 (5), 2544–2551 (2013)

Al-Masri, E., et al.: A serverless IoT architecture for smart waste management systems. In: 2018 IEEE International Conference on Industrial Internet (ICII), pp. 179–180 (2018)

Al-Jabi, M., Diab, M.: IoT-enabled citizen attractive waste management system. In: 2017 2nd International Conference on the Applications of Information Technology in Developing Renewable Energy Processes & Systems (IT-DREPS), pp. 1–5 (2017)

Marchiori, M.: The smart cheap city: efficient waste management on a budget. In: 2017 IEEE 19th International Conference on HPCC; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on DSS, pp. 192–199 (2017)

Kim, Y., Bang, H.: Introduction to Kalman filter and its applications. In: Govaers, F. (ed.) Introduction and Implementations of Kalman Filter, pp. 7–22. IntechOpen, London (2019)

Ananthasayanam, M.R.: Tuning of the Kalman filter using constant gains. In: Govaers, F. (ed.) Introduction and Implementations of Kalman Filter, pp. 25–54. IntechOpen, London (2019)

Chowdhury, B., Chowdhury, M.U.: RFID-based real-time smart waste management system. In: 2007 Australasian Telecommunication Networks and Applications Conference, pp. 175–180 (2007)

Google OR-Tools: Vehicle Routing (2021). Retrieved from: https://developers.google.com/optimization/routing . Accessed 10 July 2021

Google OR-Tools: Vehicle Routing Problem (2021). Retrieved from: https://developers.google.com/optimization/routing/vrp . Accessed 10 July 2021

Google OR-Tools: Capacity Constraints (2021). Retrieved from: https://developers.google.com/optimization/routing/cvrp . Accessed 10 July 2021

Columbus, L.: Roundup of Internet of Things Forecasts and Market Estimates (2021). Retrieved from: https://www.forbes.com/sites/louiscolumbus/2016/11/27/roundup-of-internet-of-things-forecasts-and-market-estimates-2016/#6a558beb292d . Accessed 2 Oct 2021

Poniszewska-Maranda, A., Kaczmarek, D., Kryvinska, N., Xhafa, F.: Studying usability of AI in the IoT systems/paradigm through embedding NN techniques into mobile smart service system. Computing 101 (3) (2019)

Welch, G., Bishop, G.: An Introduction to the Kalman Filter (1997)

Tkachenko, R., Izonin, I., Kryvinska, N., Dronyuk, I., Zub, K.: An approach towards increasing prediction accuracy for the recovery of missing IoT data based on the GRNN-SGTM ensemble. Sensors 20 (9), 2625 (2020). https://doi.org/10.3390/s20092625

Baumgarten, C., Ivanochko, I.: The impact of electronic services on traditional services. In: Kryvinska, N., Greguš, M. (eds.) Developments in Information & Knowledge Management for Business Applications. Studies in Systems, Decision and Control, vol. 330. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-62151-3_7

Fedushko, S., Ustyianovych, T., Gregus, M.: Real-time high-load infrastructure transaction status output prediction using operational intelligence and big data technologies. Electronics. 9 (4), 668 (2020). https://doi.org/10.3390/electronics9040668

Download references

Author information

Authors and affiliations.

Faculty of Management, Comenius University, Odbojárov 10, 820 05, Bratislava 25, Slovakia

Vanda Klučariková

You can also search for this author in PubMed   Google Scholar

Editor information

Editors and affiliations.

Department of Information Systems, Faculty of Management, Comenius University, Bratislava, Slovakia

Natalia Kryvinska

Michal Greguš

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Klučariková, V. (2022). Internet of Things & Waste Management. In: Kryvinska, N., Greguš, M. (eds) Developments in Information & Knowledge Management for Business Applications. Studies in Systems, Decision and Control, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-95813-8_5

Download citation

DOI : https://doi.org/10.1007/978-3-030-95813-8_5

Published : 30 March 2022

Publisher Name : Springer, Cham

Print ISBN : 978-3-030-95812-1

Online ISBN : 978-3-030-95813-8

eBook Packages : Intelligent Technologies and Robotics Intelligent Technologies and Robotics (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Modernizing medical waste management: unleashing the power of the internet of things (iot).

1. Introduction

• RQ1: What is the current status of digitalization in waste management?
• RQ2: What are the existing challenges and barriers to the adoption of digitalization and IoT technologies in medical waste management?
• RQ3: How can IoT technologies contribute to achieving net-zero waste goals?

1.1. Challenges

• The implementation of advisable procedures in waste management;
• Violation in the segregation of waste;
• The effect of improper waste management on humans and the environment;
• Minimizing manual labor in monitoring waste management;
• The digitalization of the entire process of waste management.

1.2. Contribution

• This paper provides a systematic literature review of waste management procedures recommended by the World Health Organization under the surveillance of the United Nations.
• This paper provides an overview of challenges in waste management and the frameworks in the proposed projects associated with successful implementation.
• This paper aims to facilitate a deeper understanding of application complexity and provide insights into suitable benchmarking practices. Additionally, it will present an evaluation of the implementation costs associated with the proposed architecture.

2. Research Methodology

3. monitoring medical waste management, 3.1. segregation.

3.2. Storage

3.3. transportation, 3.4. disposal process and treatment.

• Thermal treatment is a popular method for waste disposal. Low-heat thermal processes, such as microwave treatment, are sufficient to eliminate all pathogens, even those that cannot be combusted. This process can be carried out at temperatures ranging from 100 °C to 180 °C [ 15 ].
• Incineration is considered the most efficient method as it can handle large quantities of waste at once. It is recommended to be conducted under controlled operational conditions at temperatures between 1100 °C and 1600 °C [ 18 ]. All medical waste incinerators should adhere to air emission standards to minimize the potential for air pollution. However, incineration requires high maintenance costs and proper ash disposal, and the gas emissions resulting from the combustion of medical waste can have harmful effects on human health and the environment [ 25 ]. Consequently, some countries resort to backyard burning without proper monitoring.
• Chemical processes are often employed to disinfect or sterilize medical waste. Dissolving items in chlorine dioxide, sodium hypochlorite, peracetic acid, lime solution, ozone gas, or calcium oxide powder is a common practice to eliminate infectious bacteria from medical tools and equipment before disposal [ 24 ].
• Steam heat generated by autoclaves is commonly used for sterilization. Autoclaves can ethically and legally treat waste when sufficient time and temperature are applied. The Ethiopian government has acquired two high-technology autoclaves (T100) capable of treating up to 10–15 kg (100 L) of waste at a time, with a steam pressure of 3.8 bar and a temperature of 138 °C, followed by cooling. These machines were procured for the purpose of establishing centers for disposing hazardous medical waste in Kohtla-Jarve [ 32 ]. Malaysian health centers are advised to autoclave all clinical human waste and non-reusable general waste before incineration.
• Biological processes utilize enzymes to accelerate the degradation of organic waste containing pathogens, while mechanical techniques are employed to reduce waste volume. Mechanical methods include shredding, grinding, mixing, and compacting. Both processes contribute to enhancing the heat rate during incineration or any heat treatment. Some wastes are shredded prior to being placed in the autoclave machine to maximize space utilization [ 16 ].

4. Digitalization of Waste Management Monitoring

4.1. internet of things in waste management monitoring, 4.2. internet of things systems, 4.2.1. sensors, network, and application, presence of waste, air contaminant.

4.2.2. Technology Used in Monitoring Waste Proposals

4.2.3. data transporting device, 4.2.4. software application technology.

5. Critique and Further Development

• Inadequate waste segregation: Insufficient attention to and the improper segregation of medical waste pose significant risks to the public and waste management workers. Manual segregation processes are time consuming and prone to errors. Research projects have focused on waste segregation, but it remains a pressing issue, with healthcare centers sometimes violating waste separation regulations.
• The partial digitalization of waste management: While digitalization efforts have been made in some countries using QR codes and RFID, the current practice still relies on manual processes for waste separation and quantification. Real-time tracking, particularly for surveillance purposes, is lacking. Proper storage facilities, including monitoring humidity and duration, are crucial to prevent the environmental impact. Monitoring heat treatment procedures is also essential to ensure safe disposal.
• The lack of a unified platform: Hospitals and medical facilities use different platforms for purchasing, administration, and waste monitoring. There is a need for a communication platform that connects manufacturing companies, hospital purchasing and inventory departments, waste generators, storage facilities, transportation contractors, and disposal process occupiers. Such a platform would facilitate accountability for waste generation and management.

6. Conclusions

Author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Roy, A.; Manna, A.; Kim, J.; Moon, I. IoT-Based Smart Bin Allocation and Vehicle Routing in Solid Waste Management: A Case Study in South Korea. Comput. Ind. Eng. 2022 , 171 , 108457. [ Google Scholar ] [ CrossRef ]
• Azyze, N.L.A.M.S.; Isa, I.S.M.; Chin, T.S. IoT-Based Communal Garbage Monitoring System for Smart Cities. Indones. J. Electr. Eng. Comput. Sci. 2022 , 27 , 37. [ Google Scholar ] [ CrossRef ]
• Gopalrao Wawale, S.; Shabaz, M.; Mehbodniya, A.; Soni, M.; Deb, N.; Elashiri, M.A.; Dwivedi, Y.D.; Naved, M. Biomedical Waste Management Using IoT Tracked and Fuzzy Classified Integrated Technique. Hum.-Cent. Comput. Inf. Sci. 2022 , 12 , 32. [ Google Scholar ] [ CrossRef ]
• Statistics|Eurostat. Available online: https://ec.europa.eu/eurostat/databrowser/view/env_wastrt/default/line?lang=en (accessed on 14 June 2023).
• NHS. England Appendices to the NHS Clinical Waste Strategy ; NHS: Edinburgh, Scotland, 2023; Volume 1. [ Google Scholar ]
• Omran, A.; Mohammed, M.K.A. An Investigation into Medical Waste Management Practices in Hospitals in Northern Peninsula Malaysia. J. Environ. Manag. Tour. 2020 , 11 , 1779–1798. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Sri Suvetha, C.; Saravanamani, C.; Subiksha, S.; Umamaheswari, S. Automatic Bio Medical Waste Segregator ; Institute of Electrical and Electronics Engineers (IEEE): Los Alamitos, CA, USA, 2022; pp. 1124–1130. [ Google Scholar ]
• Chauhan, A.; Jakhar, S.K.; Chauhan, C. The Interplay of Circular Economy with Industry 4.0 Enabled Smart City Drivers of Healthcare Waste Disposal. J. Clean. Prod. 2021 , 279 , 123854. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Tricco, A.C.; Lillie, E.; Zarin, W.; O’Brien, K.K.; Colquhoun, H.; Levac, D.; Moher, D.; Peters, M.D.J.; Horsley, T.; Weeks, L.; et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann. Intern. Med. 2018 , 169 , 467–473. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021 , 372 , n71. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Rhee, S.W. Management of Used Personal Protective Equipment and Wastes Related to COVID-19 in South Korea. Waste Manag. Res. 2020 , 38 , 820–824. [ Google Scholar ] [ CrossRef ]
• Malaysia Department of Environment. Guidelines on the Handling and Management of Clinical Wastes in Malaysia ; Malaysia Department of Environment: Persiaran, Malaysia, 2009. [ Google Scholar ]
• Nuzaimah, M.; Sapuan, S.M.; Nadlene, R.; Jawaid, M. Recycling of Waste Rubber as Fillers: A Review. Proc. IOP Conf. Ser. Mater. Sci. Eng. 2018 , 368 , 012016. [ Google Scholar ] [ CrossRef ]
• Hamizah Mohamed, N.; Khan, S.; Jagtap, S. Towards Digitalization of Malaysian Medical Facilities Waste Management. In Proceedings of the 11th International Conference on Through-Life Engineering Services, Cranfield, UK, 8–9 November 2022. [ Google Scholar ]
• El-Ramady, H.; Brevik, E.C.; Elbasiouny, H.; Elbehiry, F.; Amer, M.; Elsakhawy, T.; Omara, A.E.D.; Mosa, A.A.; El-Ghamry, A.M.; Abdalla, N.; et al. Planning for Disposal of COVID-19 Pandemic Wastes in Developing Countries: A Review of Current Challenges. Environ. Monit. Assess 2021 , 193 , 592. [ Google Scholar ] [ CrossRef ]
• Chartier, Y.; Emmanuel, J.; Pieper, U.; Pruss, A.; Rushbrook, P.; Stringer, R.; Townend, W.; Wiburn, S.; Zghondi, R. Safe Management of Wastes from Health-Care Activities , 2nd ed.; World Health Organization: Geneva, Switzerland, 2014; ISBN 9789241548564. [ Google Scholar ]
• Jang, Y.C.; Lee, C.; Yoon, O.S.; Kim, H. Medical Waste Management in Korea. J. Environ. Manag. 2006 , 80 , 107–115. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Yoon, C.W.; Kim, M.J.; Park, Y.S.; Jeon, T.W.; Lee, M.Y. A Review of Medical Waste Management Systems in the Republic of Korea for Hospital and Medical Waste Generated from the COVID-19 Pandemic. Sustainability 2022 , 14 , 3678. [ Google Scholar ] [ CrossRef ]
• Agamuthu, P.; Barasarathi, J. Clinical Waste Management under COVID-19 Scenario in Malaysia. Waste Manag. Res. 2021 , 39 , 18–26. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ministry of Health Malaysia. COVID-19 Cases in Malaysia—COVIDNOW. Available online: https://covidnow.moh.gov.my/cases/ (accessed on 18 July 2022).
• Borders of Estonia Latvia Russia. In Medical Waste ELRII-448 Outputs and Results Outputs ; European Union: Brussels, Belgium, 2015.
• Dulneva, J. Eco-Friendly Disposal of Hazardous Medical Waste in the Cross-Border Region Medical Waste Priority 2 Common Challenges Measure 2.1 Joint Actions Aimed at Protection of Environment and Natural Resources. 2013. Available online: http://www.estlatrus.eu/uploaded_files/project_files/Portfolio_448.pdf (accessed on 30 April 2023).
• Dulneva, J. International Project’ Eco-Friendly Disposal of Hazardous Medical Waste in the Cross Border Region’ Medical Waste. 2014. Available online: http://www.estlatrus.eu/uploaded_files/project_files/Portfolio_448.pdf (accessed on 30 April 2023).
• Dulneva, J. Opening of a Centre for Disposal of Hazardous Medical Waste in Ida-Viru Central Hospital. 2015. Available online: http://www.estlatrus.eu/eng/news/medical_waste_opening_of_centr1/_gv/print_1 (accessed on 30 April 2023).
• Shirke, S.I.; Ithape, S.; Lungase, S.; Mohare, M. Automation of Smart Waste Management Using IoT. Int. Res. J. Eng. Technol. 2019 , 6 , 414. [ Google Scholar ]
• Hussain, A.; Draz, U.; Ali, T.; Tariq, S.; Irfan, M.; Glowacz, A.; Daviu, J.A.A.; Yasin, S.; Rahman, S. Waste Management and Prediction of Air Pollutants Using IoT and Machine Learning Approach. Energies 2020 , 13 , 3930. [ Google Scholar ] [ CrossRef ]
• Kumari, R.; Srivastava, K.; Wakhlu, A.; Singh, A. Establishing Biomedical Waste Management System in Medical University of India—A Successful Practical Approach. Clin. Epidemiol. Glob. Health 2013 , 1 , 131–136. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Wang, H.; Zheng, L.; Xue, Q.; Li, X. Research on Medical Waste Supervision Model and Implementation Method Based on Blockchain. Secur. Commun. Netw. 2022 , 2022 , 5630960. [ Google Scholar ] [ CrossRef ]
• Chen, W.E.; Wang, Y.H.; Huang, P.C.; Huang, Y.Y.; Tsai, M.Y. A Smart IoT System for Waste Management. In Proceedings of the 2018 1st International Cognitive Cities Conference, IC3 2018, Okinawa, Japan, 7–9 August 2018; Institute of Electrical and Electronics Engineers Inc.: Piscataway, NJ, USA, 2018; pp. 202–203. [ Google Scholar ]
• Raundale, P.; Gadagi, S.; Acharya, C. IoT Based Biomedical Waste Classification, Quantification and Management ; IEEE: Erode, India, 2017; ISBN 9781509048908. [ Google Scholar ]
• Park, H.S.; Jang, S.C.; Kang, I.S.; Lee, D.J.; Kim, J.G.; Lee, J.W. A Detailed Design for a Radioactive Waste Safety Management System Using ICT Technologies. Prog. Nucl. Energy 2022 , 149 , 104251. [ Google Scholar ] [ CrossRef ]
• Dulvena, J. MEDICAL WASTE: Opening of Centre for Disposal of Hazardous Medical Waste in Kohtla-Jarve, Estonia. Available online: http://www.estlatrus.eu/eng/news/medical_waste_opening_of_centr1/_gv/print_1 (accessed on 22 October 2022).
• Praveena, S.M.; Mohd Rashid, M.Z.; Mohd Nasir, F.A.; Wee, S.Y.; Aris, A.Z. Occurrence, Human Health Risks, and Public Awareness Level of Pharmaceuticals in Tap Water from Putrajaya (Malaysia). Expo. Health 2021 , 13 , 93–104. [ Google Scholar ] [ CrossRef ]
• World Bank Group Solid Waste Management (SWM) in Korea Learning 2: Waste Segregation and Collection. Available online: https://olc.worldbank.org/content/solid-waste-management-swm-korea-learning-2-waste-segregation-and-collection (accessed on 25 July 2022).
• Malaysian Department of Environment ESWIS—List of Licensed Schedule Waste Facility/Transporter. Available online: https://eswis.doe.gov.my/facilityList.aspx (accessed on 9 August 2022).
• Malaysia Ministry of Environment. Electronic Scheduled Waste Information System ESWIS. Available online: https://eswis.doe.gov.my/facilityList.aspx?Status=R&CategoryID=5 (accessed on 27 July 2022).
• Kothla-Jarve City Council. General Information—Kohtla-Järve City Council. Available online: https://www.kohtla-jarve.ee/web/guest/uldinfo# (accessed on 22 September 2022).
• Das, A.; Shukla, A.; Manjunatha, R.; Lodhi, E.A. IoT Based Solid Waste Segregation Using Relative Humidity Values. In Proceedings of the 3rd International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021, Tirunelveli, India, 4–6 February 2021; Institute of Electrical and Electronics Engineers Inc.: Piscataway, NJ, USA, 2021; pp. 312–319. [ Google Scholar ]
• Ramson, S.R.J.; Moni, D.J.; Vishnu, S.; Anagnostopoulos, T.; Kirubaraj, A.A.; Fan, X. An IoT-Based Bin Level Monitoring System for Solid Waste Management. J. Mater. Cycles Waste Manag. 2021 , 23 , 516–525. [ Google Scholar ] [ CrossRef ]
• Joshi, L.M.; Bharti, R.K.; Singh, R.; Malik, P.K. Real Time Monitoring of Solid Waste with Customized Hardware and Internet of Things. Comput. Electr. Eng. 2022 , 102 , 108262. [ Google Scholar ] [ CrossRef ]
• Sen Gupta, Y.; Mukherjee, S.; Dutta, R.; Bhattacharya, S. A Blockchain-Based Approach Using Smart Contracts to Develop a Smart Waste Management System. Int. J. Environ. Sci. Technol. 2021 , 19 , 7833–7856. [ Google Scholar ] [ CrossRef ]
• Che Soh, Z.H.; Al-Hami Husa, M.A.; Che Abdullah, S.A.; Shafie, M.A. Smart Waste Collection Monitoring and Alert System via IoT ; IEEE: Piscataway, NJ, USA, 2019; pp. 50–54. [ Google Scholar ]
• Atayero, A.A.; Williams, R.; Badejo, J.A.; Popoola, S.I. Based IoT-Enabled Solid Waste Monitoring System for Smart and Connected Communities. Int. J. Civ. Eng. Technol. 2019 , 10 , 2308–2315. [ Google Scholar ]
• MySejahtera. Available online: https://mysejahtera.moh.gov.my/ms/ (accessed on 13 June 2023).
• Mohammed Aarif, K.O.; Mohamed Yousuff, C.; Mohammed Hashim, B.A.; Mohamed Hashim, C.; Sivakumar, P. Smart Bin: Waste Segregation System Using Deep Learning-Internet of Things for Sustainable Smart Cities. Concurr. Comput. 2022 , 34 , e7378. [ Google Scholar ] [ CrossRef ]
• Nielsen, I.; Lim, M.; Nielsen, P. Optimizing Supply Chain Waste Management through the Use of RFID Technology. In Proceedings of the 2010 IEEE International Conference on RFID-Technology and Applications, RFID-TA 2010, Guangzhou, China, 17–19 June 2010; pp. 296–301. [ Google Scholar ]
• Gawande, N.A.; Reinhart, D.R.; Thomas, P.A.; McCreanor, P.T.; Townsend, T.G. Municipal Solid Waste in Situ Moisture Content Measurement Using an Electrical Resistance Sensor. Waste Manag. 2003 , 23 , 667–674. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• DHT11 Sensor Pinout, Features, Equivalents & Datasheet. Available online: https://components101.com/sensors/dht11-temperature-sensor (accessed on 28 March 2023).
• FC-28 Soil Moisture Sensor Module—Datasheet Hub. Available online: https://datasheethub.com/fc-28-soil-moisture-sensor-module/ (accessed on 28 March 2023).
• Ultrasonic Sensor HC-SR04 and Arduino—Complete Guide. Available online: https://howtomechatronics.com/tutorials/arduino/ultrasonic-sensor-hc-sr04/ (accessed on 28 March 2023).
• HX711 Datasheet by SparkFun Electronics|Digi-Key Electronics. Available online: https://www.digikey.co.uk/htmldatasheets/production/1836471/0/0/1/hx711.html (accessed on 28 March 2023).
• World Bank Group. Solid Waste Management (SWM) in Korea Learning 4: Waste to Energy Facilities in the SUDOKWON Landfill Corporation (SLC). Available online: https://olc.worldbank.org/content/solid-waste-management-swm-korea-learning-4-waste-energy-facilities-sudokwon-landfill (accessed on 26 July 2022).
• Voudrias, E.A. Healthcare Waste Management from the Point of View of Circular Economy. Waste Manag. 2018 , 75 , 1–2. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Amal, L.; Son, L.H.; Chabchoub, H.; Lahiani, H. Analysis of Municipal Solid Waste Collection Using GIS and Multi-Criteria Decision Aid. Appl. Geomat. 2020 , 12 , 193–208. [ Google Scholar ] [ CrossRef ]
• Sohag, M.U.; Podder, A.K. Smart Garbage Management System for a Sustainable Urban Life: An IoT Based Application. Internet Things 2020 , 11 , 100255. [ Google Scholar ] [ CrossRef ]
• Reis, P.; Pitarma, R.; Gonçalves, C.; Caetano, F. Intelligent System for Valorizing Solid Urban Waste. In Proceedings of the Iberian Conference on Information Systems and Technologies, CISTI, Barcelona, Spain, 18–21 June 2014; IEEE: Piscataway, NJ, USA, 2014. [ Google Scholar ]
• ThingSpeak vs. Firebase. Available online: https://blog.back4app.com/thingspeak-vs-firebase/ (accessed on 28 March 2023).

Click here to enlarge figure

Share and Cite

Mohamed, N.H.; Khan, S.; Jagtap, S. Modernizing Medical Waste Management: Unleashing the Power of the Internet of Things (IoT). Sustainability 2023 , 15 , 9909. https://doi.org/10.3390/su15139909

Mohamed NH, Khan S, Jagtap S. Modernizing Medical Waste Management: Unleashing the Power of the Internet of Things (IoT). Sustainability . 2023; 15(13):9909. https://doi.org/10.3390/su15139909

Mohamed, Nurul Hamizah, Samir Khan, and Sandeep Jagtap. 2023. "Modernizing Medical Waste Management: Unleashing the Power of the Internet of Things (IoT)" Sustainability 15, no. 13: 9909. https://doi.org/10.3390/su15139909

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

• Browse the MarketPlace
• Sell on the MarketPlace
• Post a Job Listing
• Job Openings
• View all issues
• Collection/Transfer
• Compost/Organic Recycling
• Government and Regulations
• Heroes on the Frontline
• Magazine Articles
• Slideshows & Trivia
• Waste Conversion
• Waste Industry Products
• Talking Trash
• Supplier Directory
• E-Newsletter
• Print Ad Specifications
• Digital Ad Specifications
• Publisher’s Statement
• Advisory Board
• Privacy Policy

The Internet of Things (IoT): Making Waste Collection Part of a Smarter Future

IoT drives digital transformation for smart cities featuring smarter waste collection. By Don Diego Padilla II

Put simply, IoT is about connecting and controlling the different objects in our world with the help of the Internet. With proliferating IT analytics, cloud computing, smart devices and apps, IoT is rapidly connecting businesses, processes and people on a scale that was previously inconceivable. Research from McKinsey estimates that IoT applications could deliver a potential economic impact of as much as $11.1 trillion per year by 2025.

IoT revolves around increased machine-to-machine communication. Built on cloud computing and networks of data-gathering sensors, it delivers a mobile, virtual and immediate connection. And it has the power to make everything “smart”. According to Cisco, 500 billion devices are expected to be connected to the Internet by 2030. Each device includes sensors that collect data, interact with the environment and communicate over a network.

IoT is the network of these connected devices. Smart, connected devices generate data that IoT applications use to aggregate, analyze and deliver insight, which helps drive more informed decisions and actions. Indeed, IoT is a critical part of business strategies going forward. Based on an IDC study of 2,300 executives in 15 countries, 48 percent of those surveyed have already deployed IoT solutions, and 58 percent said that the IoT is strategic to their business strategy.1

IoT, Smart Cities and Waste Management IoT is fundamental to “Smart Cities”. A smart city is one that has digital technology embedded across all city functions. As world urbanization continues to grow, and the total population is expected to double by 2050, there exists an increased demand for intelligent, sustainable environments that reduce environmental impact and offer citizens a high-quality life. A smart city, therefore, is defined as bringing together technology, government and society to enable the following characteristics: • A smart economy • A smart environment • Smart mobility • Smart people • Smart living • Smart governance2

Included within a smart city’s mandate is waste management and the fleets that collect and dispose of this waste. Consider that the U.S. generates nearly 230 million tons of trash every year—that is 4.6 pounds of waste per person, per day.3 With strained budgets and growing populations, being smarter about all aspects of waste management is becoming a growing priority.

A 21st-century solution to waste management and collection is a key part of what makes up a “smart city”. As a result, the waste sector is increasingly embracing IoT thinking. The use of smart technologies is already employing asset scanning, such as waste collection data gathering, the use of cart chip/sensor technology, camera-based real-time monitoring and the optimization of vehicle fleet logistics. Waste management organizations globally are now progressively deploying industrial IoT systems to monitor trash, vehicles, drivers and customers to optimize many elements of the essential services offered.

The IoT Advantage A city’s waste removal program is crucial to its overall operations. From routes to carts to safety and resource management, effective waste collection can have a huge impact on budgets. IoT offers municipalities a connected solution to better manage the waste removal process. More efficient waste collection can impact: 1. City administrators who need control over budgets, service quality and refuse collection service providers. 2. Municipal fleet and dispatch managers who need to better manage fleet logistics and service accountability. 3. Private haulers who need to better organize and optimize business processes. 4. Customers who expect timely a consistent customer service.

IoT Sensors on Waste Collection Vehicles A variety of strategically located sensors in and around the waste collection vehicle include: 1. Sensors to Manage Lifts—For increased efficiencies, many waste collection fleets now use automated loaders to lift garbage containers and dump the garbage into the vehicle. These automated loaders can service a much higher number of customers as compared to manual lifting, which significantly reduces both collection time and costs. However, due to the speed and force of automatic lifts, they need to be controlled to avoid stresses within mechanical components that can lead to breakage, failure or accelerated wear of components. To mitigate these risks, lift sensors can control the range of motion of a hydraulic actuator by signaling that the actuator is near a specified range of motion. This enables smoother mechanical operation and greater visibility into vehicle operation.

2. RFID Sensors for Cart/Container Management—Cart and container management systems provide waste and recycling firms with advanced solutions for automated garbage collection and the management of carts and customers. Using RFID tags and sensors, each garbage can or cart can be associated with a specific customer address. Drivers can quickly verify cart specifics by scanning these with handheld or other devices. Inventory management capabilities can update backend databases in real-time on service or replacement and repair requirements. With added GPS capabilities, fleet operations personnel now have real-time visibility into truck location and activity, can verify service accuracy, and can quickly identify carts that have been moved or stolen, or require servicing. Individual customer information—from damaged carts to insufficient cart capacity—is easily captured into a centralized database. This further ensures immediate and accurate information for billing processes. Smart benefits include: • Updates to delivery and associated billing information in real-time • Process improvements and cost savings through automatic asset tracking • 100 percent visibility into cart or container usage • Zero operator intervention

3. Connected Camera Systems—Smart fleet management systems now come with multiple cameras for unprecedented insights into and all around a vehicle. Typically integrated with in-cab smart displays and mobile DVR devices, these cameras take pictures and capture real-time video footage for unprecedented remote monitoring. Fleet managers can capture video of all internal and external activities from every angle, identify any driver-related safety issues for rapid remediation, capture evidence for accident and dispute resolution, and eliminate blind spot areas for a complete round-the-truck view. Additionally, these cameras can vastly improve operations by tracking bins, monitoring the lift’s safe use and recording any contamination status.

4. Sensors for Weight Management—Smart trucks can now come with calibrated mobile scales that record the weight of each cart/container lifted. These vehicles are equipped with load cells, which include corresponding scale sensors to record precise weights. These can easily be integrated with order processing systems, and onboard computing systems for route management, bin identification, tracking and navigation. Benefits include less cost-intensive weighing processes, real-time weight data collection, accurate billing and zero manual intervention requirements. Weight sensors also support weight-based Pay-As-

You-Throw (PAYT) programs that encourage more recycling by tying the cost of waste services directly to the amount of trash generated per household. The data from the weight sensors is typically fed into an onboard computing device via telemetry to identify every load by location, date and time while also calculating accurate weights of each bin collected. The result is reduced waste and increased recycling rates.

Benefits of IoT to Waste Fleets The benefits of smarter waste collection fleets with IoT connected systems are immense: • Measure accuracy and efficiency in meeting pickup and delivery commitments • Decrease administrative time wasted on data entry—go paperless • Improve the driver experience and efficiencies • Ensure accurate billing • Improve fuel consumption and mileage management • Heighten accountability and visibility • Improve customer service • Be greener and operate safely at peak performance • Significantly reduce resource requirements • Lower communications costs • Ensure integrated activity management • View servicing problems in real-time to improve customer satisfaction • Improve maintenance and safety initiatives • Help reduce amounts of household waste

Creating More Efficient, Sustainable Operations More efficient and sustainable waste collection is now considered a fundamental service for smart cities. IoT can be applied to optimize waste collection with RFID tracking, sensors and cameras. Smart fleet systems now incorporate a model for connected data sharing between the back-office, trucks and and drivers to enable route optimization, full management of container assets, safety and more efficient, sustainable operations. | WA

Don Diego Padilla II is Vice President of Safe Fleet Waste and Recycling. FleetMind Solutions is the award-winning technology leader for connected “smart truck” solutions for waste management fleets. FleetMind’s technology is derived from more than 20 years of developing the most advanced fleet management mobile and software solutions specifically designed for waste and recycling collection environments. FleetMind is a member of the Safe Fleet family. Don Diego can be reached at [email protected] .

For more information, call (888) 639-1666, e-mail [email protected] or visit www.fleetmind.com or www.safefleet.net .

Notes Cisco, “Connecting everything drives positive business results”. IDC 2015 Report. IEEE Smart Cities, 2016. Annenberg Foundation, “Garbage – How can my community reduce waste?”, 2016.

Related News

Biogenic content testing for co2 emissions and waste applications, the pfas point report: navigating new pfas regulations: what landfill operators and engineers need to know, heritage environmental services to acquire ebv from general dynamics, anchorage, ak’s solid waste services new pilot program aims to keep plastics and organics out of the landfill, how lawmakers, officials plan to overhaul recycling in minnesota, a fight over the future of recycling brews as plastics legislation gains traction, government & regulations, south dakota department of agriculture and natural resources approved nearly $65 million for sd environmental projects, senator jason lewis champions passage of the massachusetts plastics reduction act, department of labor announces $12.7m funding opportunity to support delivery of employee safety, health training, education.

• På svenska
•   Ammattikorkeakoulut
• Tampereen ammattikorkeakoulu
• Opinnäytetyöt (Avoin kokoelma)
• Näytä viite

Waste management system using the internet of things : case study of Kathmandu Valley

Subedi, santosh (2019).

Avaa tiedosto

Tiivistelmä, selaa kokoelmaa, henkilökunnalle.

• Venture Studio
• Forging the Future
• Company News
• Video Gallery
• Frequent queries
• IoT Development
• Digital Transformation
• Embedded Development
• Hardware Design
• Contact form
• ADAS Solution for Electric Vehicles
• Mobile App, Web, and Firmware for a Smart Bassinet
• PCB Design Verification for an Automotive Radar Sensor System

How Smart Cities are Leveraging IoT for Waste Management

The Smart City concept revolves around collecting real-time data from citizens, personal vehicles, public transport, buildings, and other urban infrastructure components, such as power grids and waste disposal systems. The insights gained from this data help municipal authorities manage assets and services more efficiently.

According to a recent survey published by IoT Analytics, over 70% of cities have already deployed IoT systems for traffic, security, and water level monitoring.

Smart waste management is a new frontier for local authorities looking to reduce municipal solid waste and boost community recycling rates.

How IoT Improves Waste Management in Smart Cities

The United States comprises only 4% of the global population but generates 12% of all municipal solid waste (MSW) filling our planet. Every day, Americans produce 700 thousand tons of trash. Even though recycling, commercial composting, and waste-to-energy plants have been around since the 1960s, 65% of US municipal solid waste still ends up in landfills.

New York residents, for example, recycle just 17% of their total waste . Chicago’s recycling rates barely top 8.8% .

Connected cities like San Francisco provide a much different narrative.

The city diverts about 80% of its waste from landfills and hopes to go “zero waste” by the end of 2020. Besides strict regulations and high waste management fees for end consumers and businesses, San Francisco has added technology to its recycling and composting operations. First, the city partnered with Recology, a company that spent $20 million to revamp its materials recovery facilities (MRFs) . Recology leverages optical sorters, robots, and a machine vision system to evaluate the sorting equipment's effectiveness and recover plastic that would otherwise get lost. San Francisco went on to install Nordsense garbage level sensors in trash bins along major commercial corridors. The solution helped municipal authorities reduce the number of overflowing containers by 80% while optimizing operational expenses.

Across the globe, Smart Cities are popping up in South Korea, Spain, and the Netherlands among others.

Songdo International Business District, which was constructed on 600 hectares of reclaimed land near the Yellow Sea, is connected by a truck-free waste management system. The solution features sensor-equipped garbage bins and pneumatic pipes that suck waste directly from premises, separate organic and non-organic waste, and push it further into an underground network of pipes and tunnels straight to a fully automated waste collection plant.

Another example comes from Amsterdam, Europe’s smartest city. In 2014, Amsterdam equipped waste collection trucks with a weighing mechanism that instantly knows how much a container weighs and helps predict fill levels based on historical data with 80-90% accuracy. The city further installed 12,500 Enevo fill-level sensors in waste containers and tested the system on plastic waste. By scaling the IoT solution from trial to city-wide deployment, Amsterdam is aiming to achieve a €3 million reduction in annual waste collection costs.

A similar solution is deployed in Santander, a Spanish tourist hotspot. The city leverages 6,000 sensors and RFID and NFC tags to collect real-time data on waste levels in rubbish bins and containers.

Smart Waste Management with IoT: from Waste Bin Fill-level Sensors to Next-gen Recycling Technologies

IoT-driven waste management solutions implemented in Smart Cities typically consist of endpoint devices (sensors), gateways, cloud platforms, and web and mobile applications.

How IoT-based Waste Management Systems Work under the Hood

• Wireless solar or battery-powered ultrasonic sensors are attached to waste bins and dumpsters
• The sensors measure waste levels by emitting ultrasonic sound waves
• As a next step, they transmit the data to the gateway using low-power or cellular connectivity. The sensing devices may communicate directly with the gateway (star networks) or pass the data to neighboring nodes (mesh networks)
• The gateway relays sensor readings to the cloud. Advanced waste management systems may also incorporate edge devices that process critical data locally
• The cloud platform transforms raw sensor data into actionable insights and visualizes the information using dashboards
• Plant dispatchers and waste truck drivers access the data on PCs and mobile devices to detect bins and containers that need emptying and adjust their routes accordingly

Such systems help cities reduce traffic congestion, cut CO2 emissions, and decrease waste management costs, which comprise up to 50% of municipal budgets in most developing countries.

But Smart Cities’ journey to “zero waste” does not end here.

Solutions like the SAGE Automation Bulk Redemption Terminal take over waste sorting operations at recycling depots. Computer vision systems like AMP Robotics’ Neuron spot recyclable materials on conveyor belts and promptly notify MRF staff. And self-service kiosks for consumer electronics help citizens dispose of old devices in an eco-friendly manner.

Why Cities Should Invest in IoT-based Waste Management Systems

By 2030, almost two-thirds of the world’s population will be living in cities . The amount of garbage produced by city dwellers is on track to reach six million tons by 2025. Waste disposal costs are rising too: the World Bank predicts global garbage collection expenses could top $375 billion in five years.

Most high-income cities, however, cover only a fraction of their waste management expenses by charging fees. The rest comes in the form of tax breaks, which takes a toll on local government budgets.

There’s strong evidence that IoT helps reduce the frequency of bin collections, minimizes overall waste collection costs, and lowers carbon emissions in cities. And while some cities are better equipped to deploy smart waste management systems at scale (think Amsterdam with its ubiquitous wireless connectivity, open city data, and startup hubs), the long-awaited 5G rollout and diminishing price of sensor devices could give a much-needed boost to Smart City initiatives across the globe.

More articles on the topic

• Web Systems
• Mobile Apps
• Cloud Systems
• AWS Software
• Desktop Apps
• QT Development ‌
• Embedded Apps
• Thunderbolt Solutions
• Human-Machine Interfaces (HMIs)
• Connectivity Solutions
• Proximity Solutions
• Electronic System Design
• Electronic Circuit Design
• PCB Design and Layout Services
• PCB Design Simulations
• FPGA Design
• Enclosure Design
• Business Analysis
• Hardware and Software for Startups
• UX/UI Design
• Venture Studio for Startups
• Cyber Security
• Quality Assurance
• Maintenance and Support
• Early Stage Innovation
• IoT Consulting
• Consumer IoT
• Industrial IoT (IIoT)
• Healthcare IoT
• AI/Machine Learning
• Industrial Automation and Robotics
• Computer Vision
• Content Processing and Distribution
• Consumer Electronics
• Energy and Sustainability
• Oil and Gas
• Media and Entertainment
• Software and Technology
• Industrial Manufacturing
• Transportation
• Data Storage
• Climate Tech
• Construction
• Smart Utilities
• About Softeq
• 27 Years of Innovation
• What Our Customers Say
• Our Proven Process
• Our Tech Skills
• Our Vision, Mission, and Values
• Collaboration Models
• Partnerships
• ISO Certificates

Provide details on what you need help with along with a budget and time limit. Questions are posted anonymously and can be made 100% private.

Studypool matches you to the best tutor to help you with your question. Our tutors are highly qualified and vetted.

Your matched tutor provides personalized help according to your question details. Payment is made only after you have completed your 1-on-1 session and are satisfied with your session.

• Homework Q&A
• Become a Tutor

All Subjects

Mathematics

Programming

Health & Medical

Engineering

Computer Science

Foreign Languages

Access over 35 million academic & study documents

Case study 5.

Sign up to view the full document!

24/7 Study Help

Stuck on a study question? Our verified tutors can answer all questions, from basic  math  to advanced rocket science !

Similar Documents

Most Popular Study Documents

working on a study question?

Studypool is powered by Microtutoring TM

Copyright © 2024. Studypool Inc.

Studypool is not sponsored or endorsed by any college or university.

Ongoing Conversations

Access over 35 million study documents through the notebank

Get on-demand Q&A study help from verified tutors

Read 1000s of rich book guides covering popular titles

Sign up with Google

Sign up with Facebook

Already have an account? Login

Login with Google

Login with Facebook

Don't have an account? Sign Up