A review on digital transformation in healthcare waste management: Applications, research trends and implications
Abstract
At present, both emerging and developed economies have faced the challenge of higher healthcare waste generation. Developed countries are using these technologies to manage healthcare waste and cope with the challenge. Emerging economies are still struggling to understand and implement digital technologies in healthcare waste management, posing a danger to partners handling toxic and hazardous waste. The proper handling of healthcare waste is essential for social and environmental sustainability. Digital technologies that drive digital transformation in the healthcare sector impact the traditional way of managing healthcare waste. Digital technologies include artificial intelligence, blockchain, the Internet of Things, sensors, data analytics and radio frequency identification. These technologies can potentially address vehicle route planning and scheduling problems, resource optimisation, real-time tracking and the visibility of healthcare waste management. Apart from economic and environmental concerns, the operational workforce also takes care of societal well-being and implements waste management strategies and policies. Past research has focused on integrating blockchain technology to enhance traceability and transparency in waste collection and disposal activities. However, the application and impact of these technologies for managing different operations of healthcare management with sustainability is a gap bridged by the present study. This study adopts a systematic literature review to identify research trends, applications and implications of digital transformation. It proposes a digital technology-driven framework for healthcare waste management for further research.
Get full access to this article
View all access and purchase options for this article.
References
Abul Hasan M, Raghuveer K, Pandey PS, et al. (2021) Internet of things and its application in Industry 4.0 for smart waste management. Journal of Environmental Protection and Ecology 22: 2368–2378.
Aceto G, Persico V, Pescapé A (2020) Industry 4.0 and health: Internet of things, big data, and cloud computing for healthcare 4.0. Journal of Industrial Information Integration 18: 100129.
Adiningrat R, Sukma SJ, Sagala FF, et al. (2020) Medical waste management system using IoT sensors (Internet of things). Solid State Technology 63: 4792–4796.
Agbo CC, Mahmoud QH, Eklund JM (2019) Blockchain technology in healthcare: A systematic review. Healthcare (Basel) 7: 56.
Ahlaqqach M, Benhra J, Mouatassim S, et al. (2019) Modeling and optimization of a multi-objective ridesharing problem in the case of medical waste. International Journal of Recent Technology and Engineering 8: 1911–1918.
Ahlaqqach M, Benhra J, Mouatassim S, et al. (2020) Multi-objective optimization of heterogeneous vehicles routing in the case of medical waste using genetic algorithm. In: Hamlich M, Bellatreche L, Mondal A, et al. (eds.) Communications in Computer and Information Science. Berlin: Springer, pp.256–269.
Ahmad RW, Salah K, Jayaraman R, et al. (2021) Blockchain-based forward supply chain and waste management for COVID-19 medical equipment and supplies. IEEE Access 9: 44905–44927.
Al-Issa Y, Ottom MA, Tamrawi A (2019) eHealth cloud security challenges: A survey. Journal of Healthcare Engineering 2019: 7516035.
Al-Shayea Q, El-Refea G (2013) Predicting the effects of medical waste in the environment using artificial neural networks: A case study. International Journal of Computer Science Issues (IJCSI) 10: 258.
Alharbi MF (2022) Impact of green supply chain management practices on sustainability of healthcare organizations: Mediating role of environmental responsibility. Gomal University Journal of Research 38: 145–159.
Ali M, Kuroiwa C (2009) Status and challenges of hospital solid waste management: Case studies from Thailand, Pakistan, and Mongolia. Journal of Material Cycles and Waste Management 11: 251–257.
Alves L, Ferreira Cruz E, Lopes SI, et al. (2022) Towards circular economy in the textiles and clothing value chain through blockchain technology and IoT: A review. Waste Management & Research 40: 3–23.
Amy Roselin C, Arun Prasath M, Rumesh Krishna C, et al. (2023) Clinical waste storage system with contamination prevention mechanism using UV and Arduino microcontroller. In: 6th International Conference on Inventive Computation Technologies, ICICT 2023 – Proceedings, 26–28 April 2023 held in Nepal, Lalitpur, India. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.1585–1591.
Ananth AP, Prashanthini V, Visvanathan C (2010) Healthcare waste management in Asia. Waste Management 30: 154–161.
Arabgol S, Sang Ko H (2013) Application of artificial neural network and genetic algorithm to healthcarewaste prediction. Journal of Artificial Intelligence and Soft Computing Research 3: 243–250.
Aung TS, Luan S, Xu Q (2019) Application of multi-criteria-decision approach for the analysis of medical waste management systems in Myanmar. Journal of Cleaner Production 222: 733–745.
Aydın N (2021) A comprehensive waste management simulation model for the assessment of waste segregation in the health sector. Environmental Engineering and Management Journal 20: 1731–1738.
Bano A, Ud Din I, Al-Huqail AA (2020) AIoT-based smart bin for real-time monitoring and management of solid waste. Scientific Programming 2020: 1–13.
Behera RK, Bala PK, Dhir A (2019) The emerging role of cognitive computing in healthcare: A systematic literature review. International Journal of Medical Informatics 129: 154–166.
Belsare K, Singh M (2022) An intelligent Internet of things (IoT) based automatic dry and wet medical waste segregation and management system. In: Proceedings – International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2022, 24–26 November 2022 held in Trichy, Tamilnadu, India. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.1113–1119.
Ben Youssef A, Zeqiri A (2022) Hospitality Industry 4.0 and climate change. Circular Economy and Sustainability 2: 1043–1063.
Bhatia M, Sood SK (2017) A comprehensive health assessment framework to facilitate IoT-assisted smart workouts: A predictive healthcare perspective. Computers in Industry 92: 50–66.
Boudanga Z, Benhadou S, Leroy JP (2021) IoT-and XAI-based smart medical waste management. In: Lahby M, Kose U and Bhoi AK (eds) Explainable Artificial Intelligence for Smart Cities. Boca Raton: CRC Press, pp.31–46.
Brent AC, Rogers DEC, Ramabitsa-Siimane TSM, et al. (2007) Application of the analytical hierarchy process to establish health care waste management systems that minimise infection risks in developing countries. European Journal of Operational Research 181: 403–424.
Brindha S, Praveen V, Rajkumar S, et al. (2020) Automatic medical waste segregation system by using sensors. EasyChair.
Cakir E, Tas MA, Ulukan Z (2021) A new circular intuitionistic fuzzy MCDM: A case of Covid-19 medical waste landfill site evaluation. In: 21st IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2021 – Proceedings, 18–20 November 2021 held in Budapest, Hungary. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.143–148.
Chauhan A, Jakhar SK, Chauhan C (2021) The interplay of circular economy with industry 4.0 enabled smart city drivers of healthcare waste disposal. Journal of Cleaner Production 279: 123854.
Chauhan A, Singh A (2016) A hybrid multi-criteria decision making method approach for selecting a sustainable location of healthcare waste disposal facility. Journal of Cleaner Production 139: 1001–1010.
Chauhan C, Parida V, Dhir A (2022) Linking circular economy and digitalisation technologies: A systematic literature review of past achievements and future promises. Technological Forecasting and Social Change 177: 121508.
Chen W, Zeng S, Zhang E (2023) Fermatean fuzzy IWP-TOPSIS-GRA multi-criteria group analysis and its application to healthcare waste treatment technology evaluation. Sustainability (Switzerland) 15: 6056.
Chen Y, Luo Y, Yerebakan MO, et al. (2022) Human workload and ergonomics during human-robot collaborative electronic waste disassembly. In: 2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS), 17–19 December 2022 held in Orlando, FL, USA. Danvers, MA: IEEE, pp.1–6.
Chew XY, Khaw KW, Alnoor A, et al. (2023) Circular economy of medical waste: novel intelligent medical waste management framework based on extension linear Diophantine fuzzy FDOSM and neural network approach. Environmental Science and Pollution Research 30: 60473–60499.
Chowdhury T, Chowdhury H, Rahman MS, et al. (2022) Estimation of the healthcare waste generation during COVID-19 pandemic in Bangladesh. Science of the Total Environment 811: 152295.
Ciplak N (2015) Assessing future scenarios for health care waste management using a multi-criteria decision analysis tool: A case study in the Turkish West Black Sea Region. Journal of the Air and Waste Management Association 65: 919–929.
Cozzoli N, Salvatore FP, Faccilongo N, et al. (2022) How can big data analytics be used for healthcare organization management? Literary framework and future research from a systematic review. BMC Health Services Research 22: 809.
Csorba LM, Crăciun M (2018) An application of the multi period decision trees in the sustainable medical waste investments. In: Balas VE, Balas MM, Jain LC (eds.) Advances in Intelligent Systems and Computing. Heidelberg: Springer Verlag, pp.540–556.
Dewi O, Sari NP, Raviola R, et al. (2022) Simulation design of dental practice medical waste management using dynamic system model approach. Jurnal Penelitian Pendidikan IPA 8: 2483–2492.
Diaz LF, Eggerth LL, Enkhtsetseg SH, et al. (2008) Characteristics of healthcare wastes. Waste Management 28: 1219–1226.
Dursun M, Karsak EE, Karadayi MA (2011) A fuzzy multi-criteria group decision making framework for evaluating health-care waste disposal alternatives. Expert Systems with Applications 38: 11453–11462.
Dutta P, Borah G (2023) Multicriteria group decision making via generalized trapezoidal intuitionistic fuzzy number-based novel similarity measure and its application to diverse COVID-19 scenarios. Artificial Intelligence Review 56: 3543–3617.
Elmustafa SAA, Mujtaba EY (2019) Internet of things in smart environment: Concept, applications, challenges, and future directions. World Scientific News 134: 1–51.
Erdebilli B, Devrim-İçtenbaş B (2022) Ensemble voting regression based on machine learning for predicting medical Waste: A case from Turkey. Mathematics 10: 2466.
Fang B, Yu J, Chen Z, et al. (2023) Artificial intelligence for waste management in smart cities: A review. Environmental Chemistry Letters 21: 1959–1989.
Faria TH, Shamim Kaiser M, Hossian CA, et al. (2021) Smart city technologies for next generation healthcare. Advanced Sciences and Technologies for Security Applications 2021: 253–274.
Fatimah YA, Govindan K, Murniningsih R, et al. (2020) Industry 4.0 based sustainable circular economy approach for smart waste management system to achieve sustainable development goals: A case study of Indonesia. Journal of Cleaner Production 269: 122263.
Geetha S, Narayanamoorthy S, Kang D, et al. (2019) A novel assessment of healthcare waste disposal methods: Intuitionistic hesitant fuzzy MULTIMOORA decision making approach. IEEE Access 7: 130283–130299.
Ghannadpour SF, Zandieh F, Esmaeili F (2021) Optimizing triple bottom-line objectives for sustainable health-care waste collection and routing by a self-adaptive evolutionary algorithm: A case study from tehran province in Iran. Journal of Cleaner Production 287: 125010.
Ghoushchi SJ, Bonab SR, Ghiaci AM, et al. (2021) Landfill site selection for medical waste using an integrated SWARA-WASPAS framework based on spherical fuzzy set. Sustainability (Switzerland) 13: 13950.
Görçün ÖF, Aytekin A, Tirkolaee EB (2023) Evaluating and selecting sustainable logistics service providers for medical waste disposal treatment in the healthcare industry. Journal of Cleaner Production 408: 137194.
Goswami M, Goswami PJ, Nautiyal S, et al. (2021) Challenges and actions to the environmental management of Bio-Medical Waste during COVID-19 pandemic in India. Heliyon 7: e06313.
Goyal R, Khosla C, Goyal K, et al. (2022) Review on deep learning driven analysis of biomedical waste incinerator corrosion. In: 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, 28–29 April 2022 held in Greater Noida, India. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.1709–1713.
Grace CS, Sreeja M, Deepika M (2023) Non-human intervention robot in biomedical waste management. International Journal of Health Technology and Innovation 2: 2–4.
Guleryuz D (2020) Evaluation of waste management using clustering algorithm in megacity Istanbul. Environmental Research and Technology 3: 102–112.
Haleem A, Javaid M, Singh RP, et al. (2022) Medical 4.0 technologies for healthcare: Features, capabilities, and applications. Internet of Things and Cyber-Physical Systems 2: 12–30.
Hawashin D, Salah K, Jayaraman R, et al. (2022) A blockchain-based solution for mitigating overproduction and underconsumption of medical supplies. IEEE Access 10: 71669–71682.
He Z, Liu S (2015) Application of an improved genetic algorithm to the path optimization of urban medical waste recovery. In: Peng Q, Chen B, Wang KCP, et al. (eds.) ICTE 2015 – Proceedings of the 5th International Conference on Transportation Engineering on 26 September 2015 held in Dailan, China. American Society of Civil Engineers (ASCE), pp.724–730.
Heacock M, Kelly CB, Asante KA, et al. (2016) E-waste and harm to vulnerable populations: A growing global problem. Environmental Health Perspectives 124: 550–555.
Henry RK, Yongsheng Z, Jun D (2006) Municipal solid waste management challenges in developing countries – Kenyan case study. Waste Management 26: 92–100.
Huo Q, Guo J (2020) Optimization of a multi-objective and multi-period sustainable recycling network for medical waste. Shanghai Ligong Daxue Xuebao/Journal of University of Shanghai for Science and Technology 42: 479–487.
Iris Ç, Lam JSL (2019) A review of energy efficiency in ports: Operational strategies, technologies and energy management systems. Renewable and Sustainable Energy Reviews 112: 170–182.
Irizarry J, Gheisari M, Williams G, et al. (2014) Ambient intelligence environments for accessing building information: A healthcare facility management scenario. Facilities 32: 120–138.
Jacob S, Nithianandam S, Rastogi S, et al. (2021) Handling and treatment strategies of biomedical wastes and biosolids contaminated with SARS-CoV-2 in waste environment. Environmental and Health Management of Novel Coronavirus Disease (COVID-19) 2021: 207–232.
Jagan J, Dalkiliç Y, Samui P (2019) Utilization of SVM, LSSVM and GP for predicting the medical waste generation. Waste Management 2019: 990–1012.
Jaisankar R, Murugesan V, Narayanamoorthy S, et al. (2023) Integrated MCDM approaches for exploring the ideal therapeutic plastic disposal technology: Probabilistic hesitant fuzzy domain. Water, Air, and Soil Pollution 234: 71.
Jamwal A, Agrawal R, Sharma M, et al. (2021) Industry 4.0 technologies for manufacturing sustainability: A systematic review and future research directions. Applied Sciences 11: 5725.
Javaid M, Haleem A (2019) Industry 4.0 applications in medical field: A brief review. Current Medicine Research and Practice 9: 102–109.
Javaid M, Khan IH (2021) Internet of things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic. Journal of Oral Biology and Craniofacial Research 11: 209–214.
Jin S, Yang G, Li C (2022) Medical waste traceability management system based on RFID technology. In: Li Z, Sun J (eds.) Chinese Control Conference, CCC, 25–27 July 2022 held in Hefei, China. Washington: IEEE Computer Society, pp.5106–5110.
Karadimas D, Papalambrou A, Gialelis J, et al. (2016) An integrated node for Smart-City applications based on active RFID tags; Use case on waste-bins. In: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), 6–9 September 2016 held in Berlin, Germany. Danvers, MA: IEEE, pp.1–7.
Kazançoğlu Y, Sağnak M, Lafcı Ç, et al. (2021) Big data-enabled solutions framework to overcoming the barriers to circular economy initiatives in healthcare sector. International Journal of Environmental Research and Public Health 18: 7513.
Khan SAR, Razzaq A, Yu Z, et al. (2021) Industry 4.0 and circular economy practices: A new era business strategies for environmental sustainability. Business Strategy and the Environment 30: 4001–4014.
Khanra S, Dhir A, Islam AKMN, et al. (2020) Big data analytics in healthcare: a systematic literature review. Enterprise Information Systems 14: 878–912.
Khoshsepehr Z, Alinejad S, Alimohammadlou M (2023) Exploring industrial waste management challenges and smart solutions: An integrated hesitant fuzzy multi-criteria decision-making approach. Journal of Cleaner Production 420: 138327.
Kumar NM, Mohammed MA, Abdulkareem KH, et al. (2021) Artificial intelligence-based solution for sorting COVID related medical waste streams and supporting data-driven decisions for smart circular economy practice. Process Safety and Environmental Protection 152: 482–494.
Kurniawan TA, Meidiana C, Othman MHD, et al. (2023) Strengthening waste recycling industry in Malang (Indonesia): Lessons from waste management in the era of Industry 4.0. Journal of Cleaner Production 382: 135296.
Kurniawan TA, Othman MHD, Hwang GH, et al. (2022) Unlocking digital technologies for waste recycling in Industry 4.0 era: A transformation towards a digitalization-based circular economy in Indonesia. Journal of Cleaner Production 357: 131911.
Land KJ, Nizzi F, Lenes B, et al. (2014) DEmonstrating value: A simple, low cost proof of concept that quickly captures strategic physician interactions. Vox Sanguinis 107: 57–248.
Le HT, Quoc KL, Nguyen TA, et al. (2022) Medical-waste chain: A medical waste collection, classification and treatment management by blockchain technology. Computers 11: 113.
Lee CH, Yoon H-J (2017) Medical big data: promise and challenges. Kidney Research and Clinical Practice 36: 3.
Leo LM, Yogalakshmi S, Simla AJ, et al. (2022) An IoT based automatic waste segregation and monitoring system. In: 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS), 23–25 February 2022 held in Coimbatore, India. Bengaluru: IEEE. pp.1262–1267.
Li J-PO, Liu H, Ting DSJ, et al. (2021) Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective. Progress in Retinal and Eye Research 82: 100900.
Liu H, Yao Z (2017) Research on the reverse logistics management of medical waste based on the RFID technology. Fresenius Environmental Bulletin 25: 8084–8092.
Liu S, Zhang J, Niu B, et al. (2022) A novel hybrid multi-criteria group decision-making approach with intuitionistic fuzzy sets to design reverse supply chains for COVID-19 medical waste recycling channels. Computers and Industrial Engineering 169: 108228.
Liu Z, Li Z, Chen W, et al. (2020) Path optimization of medical waste transport routes in the emergent public health event of covid-19: A hybrid optimization algorithm based on the immune–ant colony algorithm. International Journal of Environmental Research and Public Health 17: 1–18.
Lotfi R, Hazrati H, Ali SS, et al. (2023) Antifragile, sustainable and agile healthcare waste chain network design by considering blockchain, resiliency, robustness and risk. Central European Journal of Operations Research. Epub ahead of print.
Maluleke K, Musekiwa A, Kgarosi K, et al. (2021) A scoping review of supply chain management systems for point of care diagnostic services: Optimising COVID-19 testing capacity in resource-limited settings. Diagnostics 11: 2299.
Manegdeg F, Rollon A, Sales-Papa DL, et al. (2021) Waste profile and waste-to-energy conversion potential of medical, hazardous industrial, and electronic residual wastes in Metro Manila, Philippines. Philippine Journal of Science 150: 611–623.
Mantzaras G, Voudrias EA (2017) An optimization model for collection, haul, transfer, treatment and disposal of infectious medical waste: Application to a Greek region. Waste Management 69: 518–534.
Manupati VK, Ramkumar M, Baba V, et al. (2021) Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era. Journal of Cleaner Production 281: 125175.
Masih AK, Stanley PK (2022) Covid medical waste segregation robot using Yolov5. In: Rajalakshmy P, Mary XA, Mahanta GB (eds.) International Conferecne on Robotics, Automation and Intelligent Systems (ICRAINS 21), AIP Conference Proceedings, 12–13 November 2021 held in Coimbatore, India. New York: American Institute of Physics, Inc.
Mathur P, Patan S, Shobhawat AS (2012) Need of biomedical waste management system in hospitals – An emerging issue – A review. Current World Environment 7: 117.
Menekşe A, Camgöz Akdağ H (2023) Medical waste disposal planning for healthcare units using spherical fuzzy CRITIC-WASPAS. Applied Soft Computing 144: 110480.
Mishra AR, Mardani A, Rani P, et al. (2020) A novel EDAS approach on intuitionistic fuzzy set for assessment of health-care waste disposal technology using new parametric divergence measures. Journal of Cleaner Production 272: 122807.
Mishra AR, Rani P (2021) Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method. Complex & Intelligent Systems 7: 2469–2484.
Mohamed NH, Khan S, Jagtap S (2023) Modernizing medical waste management: Unleashing the power of the Internet of things (IoT). Sustainability (Switzerland) 15: 9909.
Mohammed MN, Alfiras M, Al-Zubaidi S, et al. (2022) 2019 Novel Coronavirus Disease (Covid-19): Toward a novel design for smart waste management robot. In: 2022 IEEE 18th International Colloquium on Signal Processing and Applications, CSPA 2022 – Proceeding, 12 May 2022 in Selangor, Malaysia. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.74–78.
Moher D, Liberati A, Tetzlaff J, et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (Chinese edition). Journal of Chinese Integrative Medicine 7: 889–896.
Mol MPG, Zolnikov TR, Neves AC, et al. (2022) Healthcare waste generation in hospitals per continent: a systematic review. Environmental Science and Pollution Research 29: 42466–42475.
Mulyadi A, Arvitrida NI (2021) Managing medical waste during COVID-19 outbreak: A simulation approach. In: Ali A, Linton AL (eds.) Proceedings of the International Conference on Industrial Engineering and Operations Management, 9–11 July 2021 held in Harbin, China. Michigan: IEOM Society, pp.379–390.
Nambiar R, Bhardwaj R, Sethi A, et al. (2013) A look at challenges and opportunities of big data analytics in healthcare. In: Hu X, Lin TY, Raghavan V, et al. (eds) 2013 IEEE International Conference on Big Data, 6-9 October 2013 held in Silicon Valley, CA, USA. Danvers, MA: IEEE, pp.17–22.
Navaneeth M, Potu S, Babu A, et al. (2023) Transforming medical plastic waste into high-performance triboelectric nanogenerators for sustainable energy, health monitoring, and sensing applications. ACS Sustainable Chemistry & Engineering 11: 12145–12154.
Nema SK, Ganeshprasad KS (2002) Plasma pyrolysis of medical waste. Current Science 83: 271–278.
Nnorom IC, Osibanjo O (2008) Overview of electronic waste (e-waste) management practices and legislations, and their poor applications in the developing countries. Resources, Conservation and Recycling 52: 843–858.
Nolz PC, Absi N, Feillet D (2011) Optimization of infectious medical waste collection using RFID. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Berlin: Springer, pp.86–100.
Patel A, Jana S, Mahanta J (2023) Intuitionistic fuzzy EM-SWARA-TOPSIS approach based on new distance measure to assess the medical waste treatment techniques. Applied Soft Computing 144: 110521.
Purnomo CW, Kurniawan W, Aziz M (2021) Technological review on thermochemical conversion of COVID-19-related medical wastes. Resources, Conservation and Recycling 167: 105429.
Qi Q, Tao F, Cheng Y, et al. (2021) New IT driven rapid manufacturing for emergency response. Journal of Manufacturing Systems 60: 928–935.
Rahayu P, Rohajawati S, Fairus S, et al. (2021) Challenges and recommendation of the information technologies application in hazardous medical waste management amidst pandemic Covid-19. Journal of Physics: Conference Series 1844: 012029.
Ranjbari M, Saidani M, Esfandabadi ZS, et al. (2021) Two decades of research on waste management in the circular economy: Insights from bibliometric, text mining, and content analyses. Journal of Cleaner Production 314: 128009.
Riek LD (2017) Healthcare robotics. Communications of the ACM 60: 68–78.
Ruparel M (2023) MEDIIAGV™ (Minimal Contact Medical Waste Management from Source Collection to Disposition Point). In: Babu SA (eds) 5th World Congress on Disaster Management: Volume III. Oxfordshire: Taylor and Francis, pp.308–317.
Saeidi-Mobarakeh Z, Tavakkoli-Moghaddam R, Navabakhsh M, et al. (2020) A bi-level meta-heuristic approach for a hazardous waste management problem. International Journal of Engineering, Transactions A: Basics 33: 1304–1310.
Sahni P, Arora G, Dubey AK (2018) Healthcare waste management and application through big data analytics. In: Panda B, Roy NR, Sharma S (eds.) Communications in Computer and Information Science. Heidelberg: Springer Verlag, pp.72–79.
Salehi-Amiri A, Akbapour N, Hajiaghaei-Keshteli M, et al. (2022) Designing an effective two-stage, sustainable, and IoT based waste management system. Renewable and Sustainable Energy Reviews 157: 112031.
Sarwar M (2023) Improved assessment model for health-care waste management based on dual 2-tuple linguistic rough number clouds. Engineering Applications of Artificial Intelligence 123: 106255.
Seikh MR, Mandal U (2023) Interval-valued Fermatean fuzzy Dombi aggregation operators and SWARA based PROMETHEE II method to bio-medical waste management. Expert Systems with Applications 226: 120082.
Seilkassymova R, Nurmukhankyzy D, Rzabay A, et al. (2022) Environmental safety and legal regulation of medical waste management: International experience. Journal of Environmental Management & Tourism 13: 1817–1824.
Sengeni D, Padmapriya G, Imambi SS, et al. (2023) Biomedical waste handling method using artificial intelligence techniques. In: Srivastava P, Ramteke D, Bedyal AK et al. (eds) Handbook of Research on Safe Disposal Methods of Municipal Solid Wastes for a Sustainable Environment. Hershey: IGI Global, pp.306–323.
Shadkam E (2022) Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management. Waste Management and Research 40: 458–469.
Shaju S, Thomas G, Francis JK, et al. (2023) Conceptual design and simulation study of an autonomous indoor medical waste collection robot. IAES International Journal of Robotics and Automation 12: 29.
Shammi M, Behal A, Tareq SM (2021) The escalating biomedical waste management to control the environmental transmission of COVID-19 pandemic: A perspective from two South Asian countries. Environmental Science & Technology 55: 4087–4093.
Shi H, Liu HC, Li P, et al. (2017) An integrated decision making approach for assessing healthcare waste treatment technologies from a multiple stakeholder. Waste Management 59: 508–517.
Simic V, Ebadi Torkayesh A, Ijadi Maghsoodi A (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 328: 1105–1150.
Simões AS, Carrion R, Martins ACG, et al. (2006) Autonomous mobile robots designing for the medical trash collector task. In: 2006 IEEE 3rd Latin American Robotics Symposium, 26–27 October 2006 held in Santiago, Chile. Danvers, MA: IEEE, pp.234–239.
Singh N, Ogunseitan OA, Tang Y (2022) Medical waste: Current challenges and future opportunities for sustainable management. Critical Reviews in Environmental Science and Technology 52: 2000–2022.
Srinivasan U, Arunasalam B (2013) Leveraging big data analytics to reduce healthcare costs. IT Professional 15: 21–28.
Stanmore BR, Clunies-Ross G (2000) An empirical model for the de novo formation of PCDD/F in medical waste incinerators. Environmental Science and Technology 34(21): 4538–4544.
Sun S, Hu J, Cao Y, et al. (2019) Discussion on the application of RFID technology in medical waste management. In: Proceedings – 10th International Conference on Information Technology in Medicine and Education, ITME 2019, 23–25 August 2019 held in Qingdao, China. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.120–124.
Tandon A, Dhir A, Islam AKMN, et al. (2020) Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda. Computers in Industry 122: 103290.
Tasnim S, Hasan MZ, Ahmed T, et al. (2022) A ROS-based voice controlled robotic arm for automatic segregation of medical waste using YOLOv3. In: 2022 2nd International Conference on Computer, Control and Robotics, ICCCR 2022, 18–20 March 2022 held in Shanghai, China. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.81–85.
Teh D, Rana T (2023) The use of Internet of things, big data analytics and artificial intelligence for attaining UN’s SDGs. In: Rana T, Svanberg J, Ohman P et al. (eds) Handbook of Big Data and Analytics in Accounting and Auditing. Berlin: Springer, pp.235–253.
Tirkolaee EB, Torkayesh AE (2022) A cluster-based stratified hybrid decision support model under uncertainty: Sustainable healthcare landfill location selection. Applied Intelligence 52: 13614–13633.
Torkayesh AE, Deveci M, Torkayesh SE, et al. (2022) Analyzing failures in adoption of smart technologies for medical waste management systems: a type-2 neutrosophic-based approach. Environmental Science and Pollution Research 29: 79688–79701.
Tyagi S, Agarwal A, Maheshwari P (2016) A conceptual framework for IoT-based healthcare system using cloud computing. In: Bansal A (eds) 2016 6th International Conference-Cloud System and Big Data Engineering (Confluence), 14–15 January 2016 held in Noida, India. Danvers, MA: IEEE, pp.503–507.
Varadharajan RB, Gopinath K, Salim MRB, et al. (2022) Segregation of medical wastes using feedforward neural networks and image processing for a new classification. Suranaree Journal of Science and Technology 29.
Wang C, Ma Y, Zhong G (2021) IOT monitoring system of medical waste based on artificial intelligence. In: 2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC), 23–25 July 2021 held in Gulyang, China. Danvers, MA: IEEE, pp.139–143.
Wang H, Zheng L, Xue Q, et al. (2022) Research on medical waste supervision model and implementation method based on blockchain. Security and Communication Networks 2022: 5630960.
Wang K, Nai W (2021) Application of 5G wireless communication technology in hazardous medical waste treatment. In: 2021 IEEE International Conference on Software Engineering and Artificial Intelligence, SEAI 2021, 11–13 June 2021 held in Xiamen, China. Danvers, MA: Institute of Electrical and Electronics Engineers, Inc., pp.87–90.
Wawale SG, Shabaz M, Mehbodniya A, et al. (2022) Biomedical waste management using iot tracked and fuzzy classified integrated technique. Human-centric Computing and Information Sciences 12: 32.
Wei Y, Cui M, Ye Z, et al. (2021) Environmental challenges from the increasing medical waste since SARS outbreak. Journal of Cleaner Production 291: 125246.
Windfeld ES, Brooks MS-L (2015) Medical waste management – A review. Journal of Environmental Management 163: 98–108.
Yao L, Xu Z, Zeng Z (2020) A soft-path solution to risk reduction by modeling medical waste disposal center location-allocation optimization. Risk Analysis 40: 1863–1886.
Zhang L, Wu L, Tian F, et al. (2016) Retrospection-simulation-Revision: Approach to the analysis of the composition and characteristics of medical waste at a disaster relief site. PLoS One 11: e0159261.
Zhao Y, Wang Y, Jiang H (2022) Wasted mask collection robot. Cobot 1: 14.
Zhou H, Yu X, Alhaskawi A, et al. (2022) A deep learning approach for medical waste classification. Scientific Reports 12: 2159.
Zimmerling A, Chen X (2021) Innovation and possible long-term impact driven by COVID-19: Manufacturing, personal protective equipment and digital technologies. Technology in Society 65: 101541.
Cite article
Cite article
Cite article
OR
Download to reference manager
If you have citation software installed, you can download article citation data to the citation manager of your choice
Information, rights and permissions
Information
Published In
Article first published online: October 1, 2024
Keywords
Authors
Metrics and citations
Metrics
Journals metrics
This article was published in Waste Management & Research: The Journal for a Sustainable Circular Economy.
View All Journal MetricsArticle usage*
Total views and downloads: 0
*Article usage tracking started in December 2016
Articles citing this one
Receive email alerts when this article is cited
Web of Science: 0
Crossref: 0
There are no citing articles to show.
Figures and tables
Figures & Media
Tables
Get access
Get access
Get access
Access options
If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:
I am signed in as:
View my profileSign out
I can access personal subscriptions, purchases, paired institutional access and free tools such as favourite journals, email alerts and saved searches.
Access journal content via a university, library or employer subscription.
ISWA members can access this journal content using society membership credentials.
Alternatively, view purchase options below:
Purchase 24 hour online access to view and download content.
Access journal content via a DeepDyve subscription or find out more about this option.
