PRE2022 3 Group3: Difference between revisions
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== Literature study == | ==Literature study== | ||
'''Recycling of medical plastics - ScienceDirect''' [https://www.sciencedirect.com/science/article/pii/S2542504821000348] | '''Recycling of medical plastics - ScienceDirect''' [https://www.sciencedirect.com/science/article/pii/S2542504821000348] | ||
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Findings: | Findings: | ||
* One key influence was their access to the appropriate bins. Sometimes bins were placed far away in a corner, blocked by equipment or another (less appropriate) bin would be closer. With regards to recycling, we also learned that available recycling streams in the operating suites not only differed between hospitals but also between rooms within a hospital operating suite. This was sometimes due to a lack of space, where another bin simply wouldn’t fit into an already crowded room. | *One key influence was their access to the appropriate bins. Sometimes bins were placed far away in a corner, blocked by equipment or another (less appropriate) bin would be closer. With regards to recycling, we also learned that available recycling streams in the operating suites not only differed between hospitals but also between rooms within a hospital operating suite. This was sometimes due to a lack of space, where another bin simply wouldn’t fit into an already crowded room. | ||
* We also found out that often by default large rather than small clinical waste bags were used in the operating rooms (even though exceptions exist). | *We also found out that often by default large rather than small clinical waste bags were used in the operating rooms (even though exceptions exist). | ||
* Time could work as a barrier or facilitator depending on whether nurses felt they had sufficient time to sort waste or had more pressing tasks to attend. | *Time could work as a barrier or facilitator depending on whether nurses felt they had sufficient time to sort waste or had more pressing tasks to attend. | ||
* Nurses’ self-assessed knowledge on correct waste sorting behaviour was fairly high, however, there was still room for improvement. | *Nurses’ self-assessed knowledge on correct waste sorting behaviour was fairly high, however, there was still room for improvement. | ||
* Waste support staff also played a role in nurses’ waste separation behaviour. Nurses relied on support staff to line bins appropriately, empty them when full and transport waste out of the operating suite. Unsurprisingly, nurses also identified their colleagues as another key social influence. | *Waste support staff also played a role in nurses’ waste separation behaviour. Nurses relied on support staff to line bins appropriately, empty them when full and transport waste out of the operating suite. Unsurprisingly, nurses also identified their colleagues as another key social influence. | ||
* While nurses recognised the positive outcomes of reducing landfill and materials being reused if recycled, they expressed some lack of trust in the overall recycling process, wondering if the items they placed in the recycling bin would actually get recycled once they left the operating suite or the hospital. | *While nurses recognised the positive outcomes of reducing landfill and materials being reused if recycled, they expressed some lack of trust in the overall recycling process, wondering if the items they placed in the recycling bin would actually get recycled once they left the operating suite or the hospital. | ||
| Line 106: | Line 106: | ||
Key facts | Key facts | ||
* Of the total amount of waste generated by health-care activities, about 85% is general, non-hazardous waste. | *Of the total amount of waste generated by health-care activities, about 85% is general, non-hazardous waste. | ||
* The remaining 15% is considered hazardous material that may be infectious, toxic or radioactive. | *The remaining 15% is considered hazardous material that may be infectious, toxic or radioactive. | ||
* Every year an estimated 16 billion injections are administered worldwide, but not all of the needles and syringes are properly disposed of afterwards. | *Every year an estimated 16 billion injections are administered worldwide, but not all of the needles and syringes are properly disposed of afterwards. | ||
* Open burning and incineration of health care wastes can, under some circumstances, result in the emission of dioxins, furans, and particulate matter. | *Open burning and incineration of health care wastes can, under some circumstances, result in the emission of dioxins, furans, and particulate matter. | ||
* Measures to ensure the safe and environmentally sound management of health care wastes can prevent adverse health and environmental impacts from such waste including the unintended release of chemical or biological hazards, including drug-resistant microorganisms, into the environment thus protecting the health of patients, health workers, and the general public. | *Measures to ensure the safe and environmentally sound management of health care wastes can prevent adverse health and environmental impacts from such waste including the unintended release of chemical or biological hazards, including drug-resistant microorganisms, into the environment thus protecting the health of patients, health workers, and the general public. | ||
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''Waste produced by hospitals'' and other medical facilities is a ''largely invisible contributor to environmental degradation''. However, when one considers the wide array of establishments that produce medical waste, and the use of single-use sterile equipment across these facilities, their impact quickly becomes apparent. An incredible amount of waste is produced by health clinics, nursing homes, medical research laboratories, dentists, offices, veterinary clinics, and of course hospitals. Incredibly, around 85% of hospital waste is non-hazardous and non-infectious, according to the World Health Organization. The majority of that waste is recyclable, highlighting the need for a robust hospital waste recycling initiative to prevent these safe waste materials from reaching landfills. | ''Waste produced by hospitals'' and other medical facilities is a ''largely invisible contributor to environmental degradation''. However, when one considers the wide array of establishments that produce medical waste, and the use of single-use sterile equipment across these facilities, their impact quickly becomes apparent. An incredible amount of waste is produced by health clinics, nursing homes, medical research laboratories, dentists, offices, veterinary clinics, and of course hospitals. Incredibly, around 85% of hospital waste is non-hazardous and non-infectious, according to the World Health Organization. The majority of that waste is recyclable, highlighting the need for a robust hospital waste recycling initiative to prevent these safe waste materials from reaching landfills. | ||
'''AGV Scheduling Optimization for Medical Waste Sorting System'''<ref>https://www.hindawi.com/journals/sp/2021/4313749/</ref> | |||
Key facts: | |||
* Traditional manual order picking is extremely susceptible to infection spread among workers and picking errors, while automated medical waste sorting systems can handle large volumes of medical waste efficiently and reliably. Medical waste is infectious, toxic, and hazardous, thus, the application of automated sorting systems can greatly reduce the infection rate of operators and improve the efficiency of medical waste disposal compared with traditional manual sorting. | |||
* The disposal process of medical waste mainly includes classification and collection, transportation, and recycling. | |||
* Due to the large amount of medical waste that needs to be sorted, medical waste recycling and processing centers (MWRPC) face the requirements for small orders, high volume, and strict work schedules, which are similar to e-commerce warehouses. | |||
* The recent outbreak of the novel coronavirus has stimulated the demand for medical services and protective equipment, causing the amount of medical waste to increase exponentially. | |||
* Medical waste is usually divided into five categories: infectious waste, pathological waste, injury waste, pharmaceutical waste, and chemical waste. | |||
* A vertical sorting system might be an optimal solution for sorting medical waste. | |||
'''Medical Waste-Sorting and Management Practices in Five Hospitals in Ghana'''<ref>https://www.hindawi.com/journals/jeph/2020/2934296/</ref> | |||
Hospital waste management in Ghana faces the risk of cross-contamination from the lack of thorough sorting of the waste at the points of generation. This has increased the potential for the spread of infections and chemical pollutant. | |||
Conclusion: | |||
A cross-sectional study of waste-sorting and management practices in five hospitals in Ghana has shown that even though there were attempts to segregate hospital waste, particularly in the high-risk areas, the lack of a uniform color coding and labeling system for the different categories of hospital waste affects the efficiency of collection and handling and the integrity of the final waste treatment processes. Significant differences in waste-sorting behavior among health staff were apparent only on the basis of occupation or work area. A number of incinerators for burning infectious waste are either not functioning or are operated outside their capacities or appropriate uses. Current incinerators are unable to inactivate pathogens. Chemical agents like PCDDs/Fs and PCBs are likely released in the exhausts, which calls for the need to install air pollution control devices (APCDs). It is recommended that refresher training courses are periodically organized for health workers to conscientize them on laboratory and general health safety. There is a need for an integrated approach to healthcare waste management in Ghana that will entail the coordinated efforts of the assemblies as well as the Ministry of Health and private companies contracted to collect, transport, and dispose of waste. Since 80–85% of wastes generated in health facilities are of no risk and comparable to domestic waste, they can be separated and handled together with the municipal waste streams while the infectious ones are treated specially, either on-site or sent to designated engineered incinerators. | |||
'''Machine Learning and IoT-Based Waste Management Model'''<ref>https://www.hindawi.com/journals/cin/2021/5942574/</ref> | |||
The waste-collecting trucks collect waste just once or twice in seven days. Due to improper waste collection practices, the waste in the dustbin is spread on the streets. Thus, to defeat this situation, an efficient solution for smart and effective waste management using machine learning (ML) and the Internet of Things (IoT) is proposed. In the proposed solution, there have used an Arduino UNO microcontroller, ultrasonic sensor, and moisture sensor. Using image processing, one can measure the waste index of a particular dumping ground. A hardware prototype is also developed for the proposed framework. | |||
==Appendix== | ==Appendix== | ||
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|2 | |2 | ||
|Luta Iulia Andreea | |Luta Iulia Andreea | ||
| | |3 | ||
| | |literature study | ||
|- | |- | ||
| | | | ||
Revision as of 11:29, 16 February 2023
Group members
| Name | Student id | Major |
|---|---|---|
| Luta Iulia Andreea | 1671685 | BCS |
| Sonia Roberta Maxim | 1675656 | BCS |
| Marie Spreen | 1909983 | |
| Fenna Schipper | 1625624 | BPT |
| Hakim Agni | 1430149 | |
| Lazgin Mamo | 1502506 | |
| Dhruv Manohar | 1568868 |
Brainstorming:
- Greenhouse robot
- Piano playing robot
- Drone that detect quality of snow in order to estimate risk of avalanches
- Drones that detect people stuck in places?
- Robot that helps elderly people with education
- Sorting robot for recycling
- Bed that closes in case of eg. earthquakes
Final Idea choice:
Sorting robot for recycling
- Targeting private homes (individual Trashcans with inbuilt sorting function)
-> using affordable materials
-> trash "compression"
- Targeting companys (Sorting arms, larger scale)
- ML approaches for Material classification
Paper about Material Classification with Machine Learning:
https://www.intechopen.com/chapters/75628
The literature review depicted the support vector machine (SVM) and artificial neural network (ANN) techniques as more effective than other ML techniques for material classification. The last section of this chapter includes a python-based ANN model for material classification. This ANN model has been tested for construction items (brick, wood, concrete block, and asphalt) for training and prediction. Moreover, the predictive ANN model results have been shared for the readers, along with the resources and open-source web links.
-> Maybe we can apply this to waste-materials
Game Plan:
Week 01:
- research different areas of Problem
Literature study
Recycling of medical plastics - ScienceDirect [1]
Fonclusion:
Plastics have revolutionized medical industry, especially the single use plastic. The common method adopted for disposing medical plastics is incineration that can lead to the release of toxic chemicals and gases. Many of the plastics end up in marine ecosystems detrimentally affecting their survival. Usually, medical plastics are assumed to be infectious and cannot be discarded with the common municipal waste. Moreover, lack of sufficient landfills available have persuaded mankind to think of sustainable recyclable options. Most of the medical plastics have the potential to be recycled back into the petrochemical industry as a feedstock for the production of new plastics or refined fuels. There should be better awareness about recycling possibilities among the healthcare workers and the commitment to collect and recycle the plastic wastes is essential for a sustainable future. Most importantly the plastic devices should be designed such that it is easily recyclable. The outbreak of Covid 19 has increased our dependence on plastics in an unpredictable manner. The outcome would be drastic, finally affecting our future generations. Urgent measures should be taken to properly segregate, sterilize and recycle medical plastics. Multilayer plastics can be replaced by single layer plastics wherever possible. Current recycling strategies can be scaled up and integrated with new sustainable alternatives. This can reduce the accumulation of plastic waste to a certain extend.
Improving waste separation in hospitals - insights for intervention design | Project | BehaviourWorks Australia [2]
Findings:
- One key influence was their access to the appropriate bins. Sometimes bins were placed far away in a corner, blocked by equipment or another (less appropriate) bin would be closer. With regards to recycling, we also learned that available recycling streams in the operating suites not only differed between hospitals but also between rooms within a hospital operating suite. This was sometimes due to a lack of space, where another bin simply wouldn’t fit into an already crowded room.
- We also found out that often by default large rather than small clinical waste bags were used in the operating rooms (even though exceptions exist).
- Time could work as a barrier or facilitator depending on whether nurses felt they had sufficient time to sort waste or had more pressing tasks to attend.
- Nurses’ self-assessed knowledge on correct waste sorting behaviour was fairly high, however, there was still room for improvement.
- Waste support staff also played a role in nurses’ waste separation behaviour. Nurses relied on support staff to line bins appropriately, empty them when full and transport waste out of the operating suite. Unsurprisingly, nurses also identified their colleagues as another key social influence.
- While nurses recognised the positive outcomes of reducing landfill and materials being reused if recycled, they expressed some lack of trust in the overall recycling process, wondering if the items they placed in the recycling bin would actually get recycled once they left the operating suite or the hospital.
Health-care waste (who.int)[3]
Key facts
- Of the total amount of waste generated by health-care activities, about 85% is general, non-hazardous waste.
- The remaining 15% is considered hazardous material that may be infectious, toxic or radioactive.
- Every year an estimated 16 billion injections are administered worldwide, but not all of the needles and syringes are properly disposed of afterwards.
- Open burning and incineration of health care wastes can, under some circumstances, result in the emission of dioxins, furans, and particulate matter.
- Measures to ensure the safe and environmentally sound management of health care wastes can prevent adverse health and environmental impacts from such waste including the unintended release of chemical or biological hazards, including drug-resistant microorganisms, into the environment thus protecting the health of patients, health workers, and the general public.
A Study on AI‐based Waste Management Strategies for the COVID‐19 Pandemic - PMC (nih.gov)[4]
Conclusion
Overall, it can be seen that AI/ML‐based methods can be employed to improve the performance of several different activities in the waste management process that can provide a safe and scalable setup together with the physical measures as laid out in the discussion a long‐term waste management ‐strategy.
Hospital Waste Recycling: The Great Waste Recycling Revolution (tradebe.com) [5]
Waste produced by hospitals and other medical facilities is a largely invisible contributor to environmental degradation. However, when one considers the wide array of establishments that produce medical waste, and the use of single-use sterile equipment across these facilities, their impact quickly becomes apparent. An incredible amount of waste is produced by health clinics, nursing homes, medical research laboratories, dentists, offices, veterinary clinics, and of course hospitals. Incredibly, around 85% of hospital waste is non-hazardous and non-infectious, according to the World Health Organization. The majority of that waste is recyclable, highlighting the need for a robust hospital waste recycling initiative to prevent these safe waste materials from reaching landfills.
AGV Scheduling Optimization for Medical Waste Sorting System[1]
Key facts:
- Traditional manual order picking is extremely susceptible to infection spread among workers and picking errors, while automated medical waste sorting systems can handle large volumes of medical waste efficiently and reliably. Medical waste is infectious, toxic, and hazardous, thus, the application of automated sorting systems can greatly reduce the infection rate of operators and improve the efficiency of medical waste disposal compared with traditional manual sorting.
- The disposal process of medical waste mainly includes classification and collection, transportation, and recycling.
- Due to the large amount of medical waste that needs to be sorted, medical waste recycling and processing centers (MWRPC) face the requirements for small orders, high volume, and strict work schedules, which are similar to e-commerce warehouses.
- The recent outbreak of the novel coronavirus has stimulated the demand for medical services and protective equipment, causing the amount of medical waste to increase exponentially.
- Medical waste is usually divided into five categories: infectious waste, pathological waste, injury waste, pharmaceutical waste, and chemical waste.
- A vertical sorting system might be an optimal solution for sorting medical waste.
Medical Waste-Sorting and Management Practices in Five Hospitals in Ghana[2]
Hospital waste management in Ghana faces the risk of cross-contamination from the lack of thorough sorting of the waste at the points of generation. This has increased the potential for the spread of infections and chemical pollutant.
Conclusion:
A cross-sectional study of waste-sorting and management practices in five hospitals in Ghana has shown that even though there were attempts to segregate hospital waste, particularly in the high-risk areas, the lack of a uniform color coding and labeling system for the different categories of hospital waste affects the efficiency of collection and handling and the integrity of the final waste treatment processes. Significant differences in waste-sorting behavior among health staff were apparent only on the basis of occupation or work area. A number of incinerators for burning infectious waste are either not functioning or are operated outside their capacities or appropriate uses. Current incinerators are unable to inactivate pathogens. Chemical agents like PCDDs/Fs and PCBs are likely released in the exhausts, which calls for the need to install air pollution control devices (APCDs). It is recommended that refresher training courses are periodically organized for health workers to conscientize them on laboratory and general health safety. There is a need for an integrated approach to healthcare waste management in Ghana that will entail the coordinated efforts of the assemblies as well as the Ministry of Health and private companies contracted to collect, transport, and dispose of waste. Since 80–85% of wastes generated in health facilities are of no risk and comparable to domestic waste, they can be separated and handled together with the municipal waste streams while the infectious ones are treated specially, either on-site or sent to designated engineered incinerators.
Machine Learning and IoT-Based Waste Management Model[3]
The waste-collecting trucks collect waste just once or twice in seven days. Due to improper waste collection practices, the waste in the dustbin is spread on the streets. Thus, to defeat this situation, an efficient solution for smart and effective waste management using machine learning (ML) and the Internet of Things (IoT) is proposed. In the proposed solution, there have used an Arduino UNO microcontroller, ultrasonic sensor, and moisture sensor. Using image processing, one can measure the waste index of a particular dumping ground. A hardware prototype is also developed for the proposed framework.
Appendix
Logbook
| Week | Name | Total | Breakdown of hours |
|---|---|---|---|
| 1 | Luta Iulia Andreea | ||
| Sonia Roberta Maxim | |||
| Marie Spreen | |||
| Fenna Schipper | |||
| Hakim Agni | |||
| Lazgin Mamo | |||
| Dhruv Manohar | |||
| 2 | Luta Iulia Andreea | 3 | literature study |
| Sonia Roberta Maxim | |||
| Marie Spreen | |||
| Fenna Schipper | 6 | literature study and meetings | |
| Hakim Agni | |||
| Lazgin Mamo | |||
| Dhruv Manohar |