Human-centric Computing and Information Sciences volume 12, Article number: 32 (2022)
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Improper handling of biomedical waste from a healthcare facilities and common biomedical waste treatment facilities can lead to serious implications like causing mass infections and significant environmental damage in terms of air, water, and land pollution. Every year there is an increase of about 8% of the biomedical waste generation in comparison to previous years. To effectively and efficiently manage the biomedical waste in a proper manner, several attempts have been taken to make the waste management system more improved through the implementation of an automated waste management system comprised of wireless systems. Segregation of waste helps in minimizing large loads of hazardous waste that is potentially hazardous to the environment as a whole requiring a treatment process that is costly and requires skilled manpower. It also helps in labeling and packaging of waste in a proper manner. In this paper, we will discuss how Information Technology and Internet of Things play a crucial key role in detecting and tracking of biomedical waste along with treatment and disposal of biomedical waste in best possible manner. The fuzzy system is used to categorize the waste according to four parameters. Then the fuzzy acts as feedback to Internet of Things based tracking system.
Internet of Things (IoT), Fuzzy System, Biomedical Waste, Radio Frequency Identification (RFID)
Employees working in the healthcare sector along with handlers of waste and common people usually
are frequently exposed to the injuries and toxic effects of waste management from healthcare facility
(HCF). For protecting the environment today, sound biomedical waste (BMW) practice is an important
aspect. In today’s era, a number of countries globally have very good sound and effective biomedical
waste management (BMWM) best method of practice. To bridge the gap between the countries
effectively managing BMW and the countries lacking behind the practices in managing those wastes in
a proper manner, gap need to be identified and immediately given prior attention at the earliest possible
time. Programs relating to proper management of BMWM practices where gaps are identified need to be
addressed and resolved through effective policy and best management practices at the grassroots level at
all medical units. Every day there is an increasing amount of generation of BMW across India and this
trend is rising rapidly due to the rise in the number of HCFs along with lots of patients admitting them
on a regular basis. As per the Central Pollution Control Board (CPCB) yearly report information 2017,
the number of HCFs in India were identified as 238,254 amongst which only 87,282 fell under the bedded
facilities with the total number of beds coming out to be 2,094,858 . Collection along with
transportation followed by management of the BMW from each location possesses a large challenge in
the present-day period. Guidelines issued earlier by the Ministry of Environment and Forests, in July
1998 for governing the BMW in India contain the definition categories of segregation of waste protection
along with protection and handling and treatment of waste generated in India .
Deepak et al.  says that the waste in health care facilities is very dangerous. It can cause many health hazards and plays a major role in polluting the environment. The paper points to setting up an effectiveness index for assessing the performance of biomedical waste management. In , the use of waste ash in cement is being occurred due to which its workability is decreased. Devi et al.  reveals to avoid the health risks through proper management of biomedical waste. Patil et al.  also reveals that the soil fertility can also be increased using organic biomedical wastes. The authors of  reveals that if the biomedical waste is burnt then it produces an ash which is called as incinerated biomedical waste ash. Biomedical waste is hazardous to human life in many ways. In , a technique is used in which the wastes from different hospitals are managed and the technique is an analytical hierarchy process (AHP). Kokkinos et al.  analyses that the waste management is also done by recycling different products. The recycling process can also help us to manage waste. Patil et al.  proposed that we can make fertilizers with organic biomedical waste by using plant extracts and it could be very profitable to farmers. In , the authors reveal that biomethane gas is used in various industries such as renewable resource like food manufacturing, aerospace, etc. Belhadi et al.  reveals that many of the African countries face many difficulties of waste management worldwide and this waste should be managed properly. More revisions of the BMWM rules were issued in the coming years in the year 2016, thereby easing the classification along with authorization and better handling generated daily across India . Requirements for sound BMWM clearly defining the sources of BMW along with its proper categorization and disposal were elaborated by Mathur et al. . Improper treatment and disposal of BMW directly impacts human health by spreading infection through the microbial hazards present in BMW as per Salkin . According to the study conducted by Tony et al.  in the clinics in Udupi Taluk in 2018, it was confirmed that most of the BMWM equipment’s were insufficient and were lacking proper training relating to its operation & maintenance and thereby failed to meet the standards prescribed under the BMWM guidelines. Case studies relating to the BMWM disaster occurred in Gujrat in 2009 in which approximately 240 people were reported being infected and about 70% of them were victims to the disease during this outbreak as per Seetharam . Utilization of syringes and needles that were not sterilized properly and which were stolen from medical equipment’s that were already used were identified to be the main reason for the occurrence of this outbreak. For evaluating the current status of BMWMS throughout the entire India, INCLEN Program Evaluation Network (IPEN) Study Group  conducted a study in which data collection was done from around 20 states within India and it was further found out that approximately 82% of the primary health centers along with more than 50% of the total number of secondary, tertiary HCFs are in shortfall of proper BMWM. In fact, it is quite noticeable that the majority of the workers working in HCF in India had inadequate knowledge about good BMWM practices but at the same time less injury reporting cases were found amongst them as per Matthew. The role of IoT in the effective monitoring of BMWM has been successfully demonstrated by Soni and Kandasamy  through the integration of smart sensors that gather all information from the garbage bins and transfers the data in the form of live monitoring. Several technologies relating to automatic waste management in the form of collecting and storing data through IoT based smart sensors have been discussed by Raundale et al. . These smart IoT based sensors help in improving the process of BMWM. In India, collective gaps have been observed in the collection, treatment, and disposal of BMW even though quite a number of guidelines have been issued by the government and regulatory agencies. Gaps were mainly in the form of implementation of the best BMWM practices as outlined in the statutory requirements mentioned under the government published set of guidelines. The main purpose of this pilot study is the identification of the problems along with pain points in BMWM system through exploratory surveys and finally making the BMWM system more digitalized through Internet of Things (IoT) architecture. All this is done as there is an urgent requirement to effectively manage the BMW generated daily through the implementation of proper collection, treatment, and disposal systems in place.
The upcoming section introduces the process involved in biomedical waste management, followed by the categorization of BMW, its segregation, disposal and treatment, and limitations of the previous management techniques. Finally, the methodology adapted is discussed and lastly the conclusion.
Proposing an alternative data clustering method that depends on improved RSA performance.
QM is used to enhance the searching ability of RSA to find the optimal solution.
Assess the efficiency of the developed method using a set of global optimization problems.
Evaluate the ability of the developed method as a clustering method using different datasets.
The best way to segregate the waste is to keep separate containers for different wastes, categorizing
them on the basis of solid and liquid or biodegradable and non-biodegradable. The BMWM process,
illustrated in Fig. 1, starts with the generation of waste which is basically as a by-product of healthcare
services like treatment, diagnosis, etc. Starting from the source of waste generation, the waste is firstly
identified, followed by segregation and disposed of into the right colored bin according to the color code
shown in Fig. 2. The red color code determines the disposal of waste in black color bin, yellow color
code determines the disposal in yellow color bin, and blue color code for disposal of waste in blue color bin.
Diverse classes of BMW produced at source from the HCFs that include hospitals, clinics, nursing homes, biomedical laboratories, and diagnostic centers are at first manually segregated into different bags that are color coded into yellow, red, blue, white, and black by the workers of each HCF. After that, BMW is manually separated into different categories of waste, namely, 1, 2, 3, etc. It is then transported in specialized vans with centralized facilities called CBMWTF. CBMWTF are fully centralized and integrated plants that can do everything from quantifying to record keeping to proper treatment & disposal of BMW in an effective and efficient manner. CBMWTF are monitored strictly by governing bodies like the State Pollution Control Boards to make sure they are properly operated and are in full compliance. Table 1 shows biomedical waste categorization and its disposal methods.
This paper has been presented a modified version of a new metaheuristic technique named RSA. This
modification depends on using the strength of QM to enhance the ability of RSA to enhance its ability to
balance between exploration and exploitation. This will improve the diversity of the solution and increase
the convergence rate reflected in the quality of the final solution. To assess the performance of the
developed method, a set of experiments have been conducted using standard benchmark functions which
have different characteristics. In addition, the results of the proposed QMRSA have been compared with
AO, GWO, SCA, WOA, DA, AOA, and traditional RSA. The results show the high ability of the
proposed QMRSA to find the best solution over the tested function compared with other methods. In
addition, to evaluate the applicability of QMRSA, it has been used as a clustering technique. Since the
clustering problem is considered an NP-hard problem, it has several real-world applications in IoT, cloud
computing, data mining, etc. The proposed QMRSA has been applied to eight datasets, and the results
have been compared with the same algorithms used in the first experiment. It has been observed from
clustering results and the statistical Friedman test the high ability of QMRSA to determine the number
of clusters and the central points. Moreover, the main advantage of the proposed method is that it can
find new best solutions with a high accuracy rate. According to the obtained results, the improved
QMRSA can be used for photovoltaic, task scheduling, engineering design problems, and feature
Table 1.Quantitative results on two testing datasets
|Waste category||Treatment and disposal|
|1. Human anatomical waste Human tissues, organs, body parts||Incineration, deep burial|
|2. Animal waste Animal tissues, organs, body parts, carcasses, bleeding parts, fluid, blood and experimental animals used in research, waste generated by veterinary hospital, colleges, discharge from hospitals, animal houses||Incineration, deep burial|
|3. Microbiology and biotechnology wastesste Wastes from laboratory cultures, specimens of microorganisms live or attenuated vaccines, human and animal cell culture and infectious agents from research and industrial laboratories, wastes from production of biological, toxins, dishes and devices used for transfer of cultures||Local autoclaving, micro-waving, incineration|
|4. Waste sharps Needles, syringes, scalpels, blades, glass, etc. that may cause puncture and cuts. This includes both used and unused sharps||Disinfection by chemical treatment, auto clave, microwaving, and mutilation or shredding|
|5. Discarded medicines and cytotoxic drugs Wastes comprising of outdated, contaminated, and discarded medicines||Incineration, destruction, and drug disposal in secured landfills|
|6. Soiled waste Items contaminated with blood, and body fluids including cotton, dressings, soiled plaster casts, lines, beddings, other material contaminated with blood||Incineration, autoclaving, microwaving|
|7. Solid waste Wastes generated from disposable items other than the waste (sharps) such as tubing, catheters, intravenous sets, etc.||Disinfection by chemical treatment, autoclaving, microwaving, mutilation, shredding|
|8. Liquid waste Wastes comprising of outdated, contaminated, and discarded medicines||Incineration, destruction, and drug disposal in secured landfills|
|9. Incineration ash Ash from incineration of any biomedical waste||Disposal in municipal landfill|
|10. Chemical waste Chemicals used in production of biological chemicals used in disinfection, such as insecticides, etc.||Chemical treatment and discharging into drains (liquids), secured landfill (solids)|
|Color coding||Type of container||Waste category|
|Yellow||Plastic bags||Waste comprising of human along with animal wastes, microbial, biological waste, and soiled waste|
|Red||Container/plastic bags that is disinfected||Microbiological along with waste of biological composition, waste that is soiled and solid wastes|
|Blue||Plastic bag, Puncture proof containers||Infected plastic waste like syringes, gloves, and plastic waste|
|Black||Plastic bag||Waste comprising of disposed medicines, drugs that are cytotoxic along with ashes from incineration and chemical waste|
|Green||Plastic container||Waste from office , along with kitchen waste and waste from gardens|
|White||Plastic bags or containers that are puncture proof||Sharp waste consisting of needles and cut glasses|
Although the existing system of BMWM has been in place and is working well for years, there are quite a number of defects that pose a potential hazard to the environment as a whole and lives of living organisms like human beings and animals. Some of the defect area is as follows:
1) Occurrence of unnecessary expenses in transportation contribute to about 43%.
2) Presence of limited decision-making capabilities and along with mechanisms to transport the waste.
3) Human error: Current practice of quantification and separation are completely manual in nature; hence higher chances of error occur.
4) Fraud: Sources like hospitals sometimes don’t reveal the actual facts and often mislead the authorities through false information to acquire the license.
5) Delay: There is often a delay in terms of more time consuming as the mechanisms are mostly manually oriented, thereby taking more time for segregating and measurement of the data.
6) Bureaucracy: The system of government hierarchy in India as with any other government authorities, is often slow and time consuming.
7) Corruption: The BMWM can be further hampered through the presence of employees in the HCFs that are corrupt and often take bribes. Non real time: Since data is collected on a yearly basis, it is not considered real time means not providing the authorities an instant plan of action.
At present, most of the HCFs are facing difficulties in controlling the costs associated with the BMWM along with providing sound services to its customers and resolving the issue of waste management properly. Therefore, monitoring of the proper disposal of waste is utmost essential for the HCF for ensuring the safety patients along with staff members. Existing systems available in most of the HCFs require a lot of paperwork along with hours of manpower to manage the biomedical waste on a day-to-day basis. Often this existing system is unable to effectively and efficiently manage the BMW in many instances. The newly introduced proposed system aims to solve this problem by introducing a fuzzy-based system to classify the waste and then tracking the waste through IoT server.
The type of waste category according to the color coding of the bag as explained in Table 2. Then it categorizes in terms of four parameters as described below:
P1 (Cost generator): Any waste which can be used for cost recovery
P2 (Health risk): Waste having high health risk
P3 (Bio/Non-bio-degradable): Is the waste is bio-degradable or not
P4 (Environmental effect): Is any harm to environment
|RFID & GPS based BMWMS||Existing BMWM practices|
|High speed||Slow and time consuming as it has manually based|
|Multipurpose and many format||Not multipurpose and multi format since manual log books and registers are used instead of digitally storing and sending data via computers and mobile devices|
|Reduce man-power due to automatic processing of data||Hours of manpower required due to increasing loads of waste generated in HCFs on a daily basis|
|High accuracy due to full automation||Prone to lot of errors as manually operated by human beings|
|Complex duplication||No such feature exists|
|Multiple reading||Often the readings cannot be done as accurate facts and figures of BMWM is hard to obtain since the process is manually done|
Inadequate biological waste management generates major environmental issues such as air, water, and land contamination. As a result, efficient biomedical waste management is critical to minimize the transmission of potentially hazardous illnesses and infections to the general population. The most frequent problems relating to healthcare waste [9, 10] are due to the lack of knowledge and awareness of the harmful effects of medical waste, inadequate training of staff for waste treatment and management, absence of smart or proper systems to detect and dispose the medical waste, inefficient financial and human resources to manage the waste as well as the least importance and attention given to the topic. Many countries are lacking proper regulations and are not concerned about enforcing them [11, 13]. The main and most important issue is taking in charge of the responsibility for handling and disposing BMW. According to the “polluter pay” principle, the responsibility lie within the waste producer, mostly the medical staff of any healthcare center or unit involved with such related activities. To achieve proper disposal and treatment of the medical waste, the financial cost estimation of the same must be taken into consideration. Improvements in healthcare waste management mostly rely on building a comprehensive system that addresses the responsibilities, allocation of resources, handling and disposal. The proposed system provides services like RFID tags, RFID reader, GPS, database management, third party integration, user permission, etc. This guarantees the robust performance of the architecture. Moreover, this system is quite scalable, evolving user’s requirements. The proposed system can be used in small Inadequate biological waste management generates major environmental issues such as air, water, and land contamination. As a result, efficient biomedical waste management is critical to minimize the transmission of potentially hazardous illnesses and infections to the general population. The most frequent problems relating to healthcare waste [9, 10] are due to the lack of knowledge and awareness of the harmful effects of medical waste, inadequate training of staff for waste treatment and management, absence of smart or proper systems to detect and dispose the medical waste, inefficient financial and human resources to manage the waste as well as the least importance and attention given to the topic. Many countries are lacking proper regulations and are not concerned about enforcing them [11, 13]. The main and most important issue is taking in charge of the responsibility for handling and disposing BMW. According to the “polluter pay” principle, the responsibility lie within the waste producer, mostly the medical staff of any healthcare center or unit involved with such related activities. To achieve proper disposal and treatment of the medical waste, the financial cost estimation of the same must be taken into consideration. Improvements in healthcare waste management mostly rely on building a comprehensive system that addresses the responsibilities, allocation of resources, handling and disposal. The proposed system provides services like RFID tags, RFID reader, GPS, database management, third party integration, user permission, etc. This guarantees the robust performance of the architecture. Moreover, this system is quite scalable, evolving user’s requirements. The proposed system can be used in small scale as well as large-scale facilities. The system is basically an open system consisting of exhaustive APIs which easily integrates itself with the presently running system of the center. This is an innovative, new developed approach for the management of medical waste. It reduces the headache of unnecessary paperwork, its harmful effect on the staff and patients as well as the whole environment surrounding it. The system is also highly cost-effective, thereby providing an end-to-end solution for effective and efficient waste management. The comparison with the traditional system is shown in Fig. 6.
For optimizing the biomedical waste management, the new information and communication technology system that is proposed has various advantages. Tracking different types of waste, even hazardous ones in real-time, tracking and locating more thousands of waste items, separation of waste in real-time can be done through this system. At the same time, this system further ensures that proper separation of wastes occurs and is collected into different colored bags based on their categories before processing and treatment in CBMWTF. In addition, this system has real-time rule-based alerts to notify the staff of any radioactive and hazardous waste, thereby ensuring that the waste is stored far away from the populated areas within the healthcare center for avoiding the storage areas. This system also provides a properly engineered design plan and at the same time ensures real-time checking of the temperature of the waste produced, along with producing regular reports. Moreover, this system enhances the productivity and efficiency of the waste management staff, thereby reducing the manual work, so that the staff can concentrate on providing proper services to the patients and give more attention to the customer problems. This system has an alert system to alert the staff if there is any problem with the hardware or software of the system. This system works daily 24-hour continuous cycle. It locates, tracks, and maintains the statistical data of the same. Lastly, the proposed system also ensures that the BMWM leads to hazard-free environment of the healthcare facilities. It also ensures that an automation of the system proves to be a boon to the facility, to the general public and the environment as a whole. The proposed model can be further improved in the future by introducing a more efficient and accurate models to identify and segregate the BMW.
Conceptualization, MZ. Funding acquisition, MZ. Investigation and methodology, MZ. Project administration, MS. Resources, AM. Supervision, AM. Writing of the original draft, SGW. Writing of the review and editing, ND, MAE, YDD. Software, ND, MAE, YDD. Validation, ND, MAE, YDD. Formal analysis, MS. Data curation, MN. Visualization, MN.
The authors declare that they have no competing interests.
Name : Surinder Gopalrao Wawale
Affiliation : Agasti Arts, Commerce and Dadasaheb Rupwate Science College, Akole, Maharashtra, India.
Biography : Surinder Gopalrao Wawale is working as Assistant Professor at Agasti Arts, Commerce and Dadasaheb Rupwate Science College, Akole, Maharashtra, India.
Name : Dr. Mohammad Shabaz
Affiliation : Model Institute of Engineering and Technology, Jammu, J&K, India.
Biography : Mohammad Shabaz has completed his B.Tech in Information Technology and Telecommunication Engineering from Baba Ghulam Shah Badshah University, J&K, M.E and Ph.D in Computer Science Engineering from Chandigarh University, Mohali. He is working as Assistant Professor at Model Institute of Engineering and Technology, Jammu, India. He is Currently holding the positions of Managing Editor and Publisher at Journal of Engineering, Science and Mathematics (JESM), Managing Guest Editor at Informatics in Medicine Unlocked (Elsevier) and Editor at Neuroscience Informatics (Elsevier). His area of interest is application of computer science in interdisciplinary domains. He has Published over 100+ research papers in various journals indexed in Scopus/Web of Science, 4 Indian Patents and 3 Australian Patents. His major work is on healthcare domain. His major contributions include the creation of novel algorithms like SA Sorting, Shabaz-Urvashi Link Prediction.
Name : Abolfazl Mehbodniya
Affiliation : Department of Electronics and Communication Engineering, Kuwait College of Science and Technology (KCST), Doha Area, 7th Ring Road, Kuwait.
Biography : Dr. Mehbodniya is an associate professor and head of ECE department at Kuwait College of Science and Technology (KCST). Before coming to KCST, he worked as a Marie-Curie senior research Fellow at university college Dublin, Ireland and prior to that he worked as an assistant professor at Tohoku University, Japan and as a research scientist in advanced telecommunication research (ATR) international, Kyoto, Japan. DrMehbodniya received her PhD from INRS-EMT University of Quebec, Montreal, Canada in 2010.
Name : Mukesh Soni
Affiliation : Department of CSE, University Centre for Research & Development Chandigarh University, Mohali, Punjab-140413, India
Biography :r. Mukesh Soni is Assistant Professor at Department of CSE, University Centre for Research & Development Chandigarh University, Mohali, Punjab-140413, India His research interests include Applied Cryptography, Information Security, and Network Security. He has published a total of 15 research papers in IEEE/Springer Conferences, Scopus/SCIE Journals, and 20 papers in National and International Journals. He has published 15 Indian Patents and 15 International Patents. He has received a total of 12 Awards.
Name : Nabamita Deb
Affiliation : Department of Information Technology, Gauhati University, India.
Biography : Assistant Professor, Department of Information Technology, Gauhati University, India. Her area of interest includes AI, ML and WSN.
Name : Mohamed A. Elashiri
Affiliation : Computer Science Department, Faculty of Computers & Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypt.
Biography : Lecturer in Computer Science Department, Faculty of Computers & Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypt. His area of interest includes AI, ML.
Name : Y.D. Dwivedi
Affiliation : Institute of Aeronautical Engineering, Department of Aeronautical Engineering, Hyderabad, India.
Biography : Prof. Y.D. Dwivedi is working as Professor at Institute of Aeronautical Engineering, Department of Aeronautical Engineering, Hyderabad, India.
Name : Mohd Naved
Affiliation : AIBS, Amity University, Noida, UP, India.
Biography : Mohd Naved is a machine learning consultant and researcher, currently teaching in Jagannath University in collaboration with Xcelerator Ninja for various degree programs in Analytics and Machine Learning. He is actively engaged in academic research on various topics in management as well as on 21st century technologies. He has published 30+ research papers in reputed journals (SCI/Scopus Indexed). He has 10 patents in AI/ML and actively engage in commercialization of innovative products developed at university level.
Surinder Gopalrao Wawale1 , Mohammad Shabaz2,*, Abolfazl Mehbodniya3 , Mukesh Soni4 , Nabamita Deb5 , Mohamed A. Elashiri6 , Y. D. Dwivedi7 , and Mohd Naved8, Biomedical Waste Management Using IoT Tracked and Fuzzy Classified Integrated Technique, Article number: 12:32 (2022) Cite this article 1 AccessesDownload citation
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