IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i15p3930-d393104.html
   My bibliography  Save this article

Waste Management and Prediction of Air Pollutants Using IoT and Machine Learning Approach

Author

Listed:
  • Ayaz Hussain

    (Department of Computer Science, University of Management and Technology Sialkot, Sialkot 51310, Pakistan)

  • Umar Draz

    (Department of Computer Science, University of Sahiwal, Sahiwal 57000, Pakistan
    CS Department COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan)

  • Tariq Ali

    (Electrical Engineering Department, College of Engineering, Najran University, Najran 61441, Saudi Arabia)

  • Saman Tariq

    (Department of Computer Science, University of Management and Technology Sialkot, Sialkot 51310, Pakistan)

  • Muhammad Irfan

    (Electrical Engineering Department, College of Engineering, Najran University, Najran 61441, Saudi Arabia)

  • Adam Glowacz

    (Department of Automatic Control and Robotics, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland)

  • Jose Alfonso Antonino Daviu

    (Department Electrical Engineering, Universitat Politecnica de Valencia, Instituto Tecnologico de la Energía Camino de Vera s/n, 46022 Valencia, Spain)

  • Sana Yasin

    (Department of Computer Science and Information Technology, Superior University, Gold Campus, Lahore 54000, Pakistan
    Computer Science Department, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan)

  • Saifur Rahman

    (Electrical Engineering Department, College of Engineering, Najran University, Najran 61441, Saudi Arabia)

Abstract

Increasing waste generation has become a significant issue over the globe due to the rapid increase in urbanization and industrialization. In the literature, many issues that have a direct impact on the increase of waste and the improper disposal of waste have been investigated. Most of the existing work in the literature has focused on providing a cost-efficient solution for the monitoring of garbage collection system using the Internet of Things (IoT). Though an IoT-based solution provides the real-time monitoring of a garbage collection system, it is limited to control the spreading of overspill and bad odor blowout gasses. The poor and inadequate disposal of waste produces toxic gases, and radiation in the environment has adverse effects on human health, the greenhouse system, and global warming. While considering the importance of air pollutants, it is imperative to monitor and forecast the concentration of air pollutants in addition to the management of the waste. In this paper, we present and IoT-based smart bin using a machine and deep learning model to manage the disposal of garbage and to forecast the air pollutant present in the surrounding bin environment. The smart bin is connected to an IoT-based server, the Google Cloud Server (GCP), which performs the computation necessary for predicting the status of the bin and for forecasting air quality based on real-time data. We experimented with a traditional model (k-nearest neighbors algorithm (k-NN) and logistic reg) and a non-traditional (long short term memory (LSTM) network-based deep learning) algorithm for the creation of alert messages regarding bin status and forecasting the amount of air pollutant carbon monoxide (CO) present in the air at a specific instance. The recalls of logistic regression and k-NN algorithm is 79% and 83%, respectively, in a real-time testing environment for predicting the status of the bin. The accuracy of modified LSTM and simple LSTM models is 90% and 88%, respectively, to predict the future concentration of gases present in the air. The system resulted in a delay of 4 s in the creation and transmission of the alert message to a sanitary worker. The system provided the real-time monitoring of garbage levels along with notifications from the alert mechanism. The proposed works provide improved accuracy by utilizing machine learning as compared to existing solutions based on simple approaches.

Suggested Citation

  • Ayaz Hussain & Umar Draz & Tariq Ali & Saman Tariq & Muhammad Irfan & Adam Glowacz & Jose Alfonso Antonino Daviu & Sana Yasin & Saifur Rahman, 2020. "Waste Management and Prediction of Air Pollutants Using IoT and Machine Learning Approach," Energies, MDPI, vol. 13(15), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3930-:d:393104
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/15/3930/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/15/3930/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. World Bank, 2012. "The World Bank Annual Report 2012," World Bank Publications - Books, The World Bank Group, number 11846, December.
    2. World Bank, 2012. "The World Bank Annual Report 2012," World Bank Publications - Books, The World Bank Group, number 11845, December.
    3. Kraay,Aart C., 2018. "Methodology for a World Bank Human Capital Index," Policy Research Working Paper Series 8593, The World Bank.
    4. World Bank, 2012. "The World Bank Annual Report 2012," World Bank Publications - Books, The World Bank Group, number 11844, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abdul Rehman & Muhammad Ahmed Qureshi & Tariq Ali & Muhammad Irfan & Saima Abdullah & Sana Yasin & Umar Draz & Adam Glowacz & Grzegorz Nowakowski & Abdullah Alghamdi & Abdulaziz A. Alsulami & Mariusz , 2021. "Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)," Energies, MDPI, vol. 14(17), pages 1-30, September.
    2. Nurul Hamizah Mohamed & Samir Khan & Sandeep Jagtap, 2023. "Modernizing Medical Waste Management: Unleashing the Power of the Internet of Things (IoT)," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    3. Sehrish Munawar Cheema & Abdul Hannan & Ivan Miguel Pires, 2022. "Smart Waste Management and Classification Systems Using Cutting Edge Approach," Sustainability, MDPI, vol. 14(16), pages 1-21, August.
    4. Shaik Vaseem Akram & Rajesh Singh & Anita Gehlot & Mamoon Rashid & Ahmed Saeed AlGhamdi & Sultan S. Alshamrani & Deepak Prashar, 2021. "Role of Wireless Aided Technologies in the Solid Waste Management: A Comprehensive Review," Sustainability, MDPI, vol. 13(23), pages 1-31, November.
    5. Abdallah Namoun & Ali Tufail & Muhammad Yasar Khan & Ahmed Alrehaili & Toqeer Ali Syed & Oussama BenRhouma, 2022. "Solid Waste Generation and Disposal Using Machine Learning Approaches: A Survey of Solutions and Challenges," Sustainability, MDPI, vol. 14(20), pages 1-32, October.
    6. Mesfer Al Duhayyim & Heba G. Mohamed & Mohammed Aljebreen & Mohamed K. Nour & Abdullah Mohamed & Amgad Atta Abdelmageed & Ishfaq Yaseen & Gouse Pasha Mohammed, 2022. "Artificial Ecosystem-Based Optimization with an Improved Deep Learning Model for IoT-Assisted Sustainable Waste Management," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    7. Jae Hong Park & Phil Goo Kang & Eunseok Kim & Tae Woo Kim & Gahee Kim & Heejeong Seok & Jinwon Seo, 2021. "Introduction of IoT-Based Surrogate Parameters in the Ex-Post Countermeasure of Industrial Sectors in Integrated Permit Policy," Sustainability, MDPI, vol. 13(23), pages 1-22, December.
    8. Vladimir Simic & Ali Ebadi Torkayesh & Abtin Ijadi Maghsoodi, 2023. "Locating a disinfection facility for hazardous healthcare waste in the COVID-19 era: a novel approach based on Fermatean fuzzy ITARA-MARCOS and random forest recursive feature elimination algorithm," Annals of Operations Research, Springer, vol. 328(1), pages 1105-1150, September.
    9. Sabbir Ahmed & Sameera Mubarak & Jia Tina Du & Santoso Wibowo, 2022. "Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning," IJERPH, MDPI, vol. 19(24), pages 1-15, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Charyulu, Kumara D. & Singh, N.P. & Shyam, Moses D. & Bantilan, C., 2014. "Development and Diffusion of Dryland Cereals in Semi-Arid Tropics of India — Role of Partnerships," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 27(Conferenc).
    2. Surabhi Singh & Moushumi Basu, 2014. "A Subaltern Reading of International Organisations and Issues of Order, Disorder and Marginality," South Asian Survey, , vol. 21(1-2), pages 164-179, March.
    3. Mukherjee, Swayambhu & Kar, Saibal, 2020. "Leveraging Non-Farm Income: Micro-evidence of Occupational Choice for Rural Households in India," MPRA Paper 109940, University Library of Munich, Germany.
    4. Legovini, Arianna & Di Maro, Vincenzo & Piza, Caio, 2015. "Impact evaluation helps deliver development projects," Policy Research Working Paper Series 7157, The World Bank.
    5. Ochia, Stevenson Enemuwa (Doctorial Student) & Bobmanuel, Karibi Benson PhD & Umunnah, Blessing Onyinyechukwu PhD, 2022. "Port Harcourt Residents’ Perception of Energyplatform Programme on Nigeria Info 92.3FM," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 6(12), pages 794-802, December.
    6. Robert G. Blanton & Shannon Lindsey Blanton, 2015. "Is Foreign Direct Investment "Gender Blind"? Women's Rights as a Determinant of US FDI," Feminist Economics, Taylor & Francis Journals, vol. 21(4), pages 61-88, October.
    7. Xhoxhi, Orjon & Pedersen, Søren Marcus & Lind, Kim Martin & Yazar, Attila, 2014. "The Determinants of Intermediaries’ Power over Farmers’ Margin-Related Activities: Evidence from Adana, Turkey," World Development, Elsevier, vol. 64(C), pages 815-827.
    8. Jaber, J.O. & Elkarmi, Fawwaz & Alasis, Emil & Kostas, Anagnostopoulos, 2015. "Employment of renewable energy in Jordan: Current status, SWOT and problem analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 490-499.
    9. Rachel Wolfgramm & Sian Flynn-Coleman & Denise Conroy, 2015. "Dynamic Interactions of Agency in Leadership (DIAL): An Integrative Framework for Analysing Agency in Sustainability Leadership," Journal of Business Ethics, Springer, vol. 126(4), pages 649-662, February.
    10. Kent Matthews, 2014. "Cost Inefficiency in the Pakistan Banking Sector 2002-2009," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 10, pages 1-20.
    11. Lee, Chien-Chiang & Lin, Chun-Wei & Zeng, Jhih-Hong, 2016. "Financial liberalization, insurance market, and the likelihood of financial crises," Journal of International Money and Finance, Elsevier, vol. 62(C), pages 25-51.
    12. Chileshe Ng’andu Musaba & Emmanuel C. Musaba & Simon I.R. Hoabeb, 2014. "Employee Perceptions of Service Quality in the Namibian Hotel Industry: A SERVQUAL Approach," International Journal of Asian Social Science, Asian Economic and Social Society, vol. 4(4), pages 533-543, April.
    13. Samuel Egyakwa Ankomah & Adam Fusheini & Christy Ballard & Emmanuel Kumah & Gagan Gurung & Sarah Derrett, 2021. "Patient–public engagement interventions for health system improvement in Sub‐Saharan Africa: A systematic scoping review protocol," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(2), pages 273-281, March.
    14. Guido de Blasio & Stefania De Mitri & Alessio D'Ignazio & Paolo Finaldi Russo & Lavina Stoppani, 2017. "Public guarantees on loans to SMEs: an RDD evaluation," Temi di discussione (Economic working papers) 1111, Bank of Italy, Economic Research and International Relations Area.
    15. Josef Brechler & Vaclav Hausenblas & Zlatuse Komarkova & Miroslav Plasil, 2014. "Similarity and Clustering of Banks: Application to the Credit Exposures of the Czech Banking Sector," Research and Policy Notes 2014/04, Czech National Bank.
    16. Stephen P. D’Alessandro & Jorge Caballero & John Lichte & Simon Simpkin, 2015. "Kenya," World Bank Publications - Reports 23350, The World Bank Group.
    17. Karimo, Tamarauntari M., 2015. "The Impact of Economic Liberalization Policy on Performance of the Nigerian Industrial Sector - L’impatto della politica di liberalizzazione economica sulla performance del settore industriale in Nige," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 68(2), pages 229-257.
    18. Muliadi Muliadi & Dio Caisar Darma & Jati Kasuma, 2020. "MSMEs as mediation in the effects of investment credit, interest rates, and labor on economic growth: Evidence from Indonesia," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 9(2), pages 01-12, April.
    19. Stelios Grafakos & Alberto Gianoli & Alexandra Tsatsou, 2016. "Towards the Development of an Integrated Sustainability and Resilience Benefits Assessment Framework of Urban Green Growth Interventions," Sustainability, MDPI, vol. 8(5), pages 1-33, May.
    20. Da Mata, Daniel & Resende, Guilherme, 2020. "Changing the climate for banking: The economic effects of credit in a climate-vulnerable area," Journal of Development Economics, Elsevier, vol. 146(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3930-:d:393104. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.