QR/IoT-Assisted Trash Collection System: Comparison
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Please note this is a comparison between Version 2 by Lindsay Dong and Version 1 by Matasem Saleh.

Effective waste management is of paramount importance as it contributes significantly to environmental preservation, mitigates health hazards, and aids in the preservation of precious resources. Conversely, mishandling waste not only presents severe environmental risks but can also disrupt the balance of ecosystems and pose threats to biodiversity. The emission of carbon dioxide, methane, and greenhouse gases (GHGs) can constitute a significant factor in the progression of global warming and climate change, consequently giving rise to atmospheric pollution. This pollution, in turn, has the potential to exacerbate respiratory ailments, elevate the likelihood of cardiovascular disorders, and negatively impact overall public health. Hence, efficient management of trash is extremely crucial in any society. It requires integrating technology and innovative solutions, which can help eradicate this global issue. The internet of things (IoT) is a revolutionary communication paradigm with significant contributions to remote monitoring and control. IoT-based trash management aids remote garbage level monitoring but entails drawbacks like high installation and maintenance costs, increased electronic waste production (53 million metric tons in 2013), and substantial energy consumption for always-vigilant IoT devices. 

  • trash collection system
  • internet of things
  • integrating technology in the waste collection
  • optimized garbage collection procedures
  • waste collection teams
  • remote garbage level monitoring

1. Introduction

In the present era, waste production has significantly increased, leading to overflowing garbage bins throughout the city. This creates unhygienic conditions, affecting the aesthetics of the surroundings and posing risks of disease transmission [1]. Wastes accumulated over long periods of time in the dump yards can be even more devastating. It can cause the contamination of land and water bodies. Harmful chemicals released from these wastes can seep into the land and adversely affect the groundwater [2]. Effective waste management can readily mitigate land and water pollution while also curbing the proliferation of diseases [3]. In urban areas, daily waste collection is a labor-intensive task with significant implications for the environment and society. This necessitates the adept management of waste truck routes, coupled with a diligent assessment of environmental, economic, and social factors [4].
A comprehensive trash collection system holds significant relevance and value in society, particularly with the growing urban populations and the accompanying rise in daily trash quantities [5,6][5][6]. This presents a significant dilemma for many nations that lack the financial means to engage sufficient manpower to tackle this problem. Hence, to address this issue, a smart and intelligent system is needed to minimize the need for manual labor while maximizing efficiency and delivering superior results. In order to develop such a system, data plays a pivotal role. Firstly, it encompasses information about the types of locations requiring garbage collection, such as residential areas, industrial sites, or marketplaces. Secondly, it includes data on the quantity of waste generated by these locations, enabling the system to target areas with greater precision. Lastly, it considers whether the waste is recyclable or non-recyclable [7].

2. IoT-Assisted Trash Collection System 

The previous efforts mostly discuss IoT-assisted waste collection, IoT-enabled smart bins [10[8][9],11], or the specific issues related to the waste-management cycle. Sheng et al. [12][10] proposed an IoT-based system utilizing deep learning models and LoRa (long-range) communication technology. Rogoff et al. [13][11] discussed automated waste collection systems that utilize underground vacuum pipes and automated collection vehicles for efficient and hygienic waste disposal. Glouche et al. [14,15][12][13] explored smart waste management using self-describing complex objects, where waste items are equipped with RFID tags and other sensors to enable automated identification, sorting, and disposal processes. Aparna et al. [3] discussed an IoT-assisted waste collection and management system using QR codes. This is a thoughtful and innovative study that explores the potential of using internet of things (IoT) technology and QR codes to improve waste collection and management. The authors propose a system in which waste bins are equipped with IoT devices and QR codes, allowing for the real-time monitoring of waste levels and efficient collection. The study provides a detailed description of the system’s architecture and demonstrates its potential through simulation results. Using QR codes for waste classification also adds an interesting feature to the system. Overall, thise study presents a promising solution for addressing the challenges of waste management, particularly in urban areas. The system’s ability to provide real-time data on waste levels and efficient collection can greatly improve the effectiveness and efficiency of waste management. Additionally, integrating QR codes for waste classification enhances the system’s capabilities and makes it more user-friendly. Thise study is a valuable resource for researchers and practitioners working in the field of waste management and IoT. Taelman et al. [7] presented a literature review of waste management practices in European cities by analyzing current practices, identifying their strengths and weaknesses, and considering economic, environmental, and social sustainability factors. The authors also provide examples of best practices and recommendations for city planners and policymakers to improve waste management practices in their cities. Pelonero et al. [16][14] proposed a data-centric approach to design an IoT-based garbage collection system that aims to incentivize citizens to recycle waste and improve their waste disposal habits. The proposed system utilizes IoT sensors and a mobile app to collect data on garbage collection and recycling rates. The collected data are then used to incentivize citizens to recycle more and reduce their waste generation. The system allows citizens to receive rewards in the form of discounts, vouchers, or loyalty points for their recycling efforts, and an incentivization mechanism can encourage citizens to recycle more and contribute to the overall sustainability of the city. The proposed system also includes features such as the real-time monitoring of waste levels, dynamic route planning, and the predictive maintenance of garbage collection trucks for efficient and cost-effective waste management. The paper highlights the importance of citizen participation and engagement in waste management and proposes a data-driven solution to improve waste management practices that has the potential The paper [21][15] proposes a smart waste management system called the internet of garbage bins (IoGBs), which uses IoT technology to monitor waste bin fill levels and optimize waste collection schedules, reducing operational costs and improving the sustainability of waste management. Smart cities are being introduced globally, with examples in cities like Mangaluru [22[16][17],23], Seoul [24][18], Greater Noida [25][19], and Kerala [26][20] where innovative QR code-based systems have been successfully implemented for household waste collection. In this system, primary waste collection vehicles, responsible for collecting refuse from door to door, employ QR code scanning technology placed at household entrances during the collection process. Subsequently, the gathered refuse is transferred to secondary collection vehicles, which then transport it to designated disposal sites. Furthermore, beyond waste management, the QR codes installed at residences can serve as versatile tools, facilitating various public services, including the payment of utility bills, property taxes, and telephone bills, among others. Panainte-Lehadus et al. [27][21] have presented a case study conducted in a specific locality to evaluate the efficiency of different household waste collection methods and statistics about the community involved in the waste collection. The authors used a combination of data analysis, surveys, and interviews to collect and analyze data on waste generation, collection, and disposal. The results showed that the current waste collection system in the locality was inefficient, with high contamination levels and illegal dumping. The data analysis also presented that community characteristics such as education level, locality, age, and gender have a substantial effect on the household waste collection mechanism. The authors recommend several improvements, such as the implementation of separate collection for organic waste, the use of recycling bins, and education and awareness campaigns to promote sustainable waste management practices. The study provides valuable insights into the challenges and opportunities of household waste collection, highlighting the importance of effective waste management strategies in promoting sustainable development. Some trash collection systems have high development and maintenance costs. The authors in [28][22] present a new approach to trash collection that involves an automated system that can move around autonomously, detect trash, and collect it. The system consists of a mobile base, a manipulator arm, and a set of sensors, including a camera and a lidar. The paper describes the design and construction of the system and evaluates its performance in simulated and real-world environments. The results demonstrate the feasibility and effectiveness of the proposed approach, which can potentially improve the efficiency and sustainability of trash collection. Vishnu et al. [29][23] proposed a waste management system using IoT devices to track waste levels in public and residential bins. The proposed system measures the level of unfilled bins using an ultrasonic sensor, which calculates the ground distance from the bin’s surface to get the capacity. It is also used to send location, store data for statistics measurements, and send all of the processed data to the central monitoring station, which give stats about the level of bins. Further, the decision on waste collection will be made based on the bin level. Table 1 provides a concise overview of the various studies in the field of trash management, shedding light on the diversity of approaches used to tackle the different tasks associated with trash collection systems. QR codes have been used in different contexts in previous studies. For example, QR codes have been used for tracking domestic waste segregation [30][24] or wastebank sorting [31][25].
Table 1.
A brief tabular outline of the related works with the proposed trash management tasks.
  Trash Management Tasks
Used Techniques QR Code RFID IoT Sensors Data Collection Route Planing Bin Overflow Control
Zhang et al. [32][26]     ✓ ✓ ✓ ✓
Hannan et al. [33][27]   ✓ ✓ ✓ ✓ ✓
Anjum et al. [34][28]   ✓ ✓   ✓ ✓
Anjum et al. [35][29]     ✓ ✓ ✓ ✓
Nguyen et al. [36][30]     ✓ ✓ ✓ ✓
Metagar et al. [37][31]   ✓ ✓     ✓
Pardini et al. [38][32]     ✓     ✓
Jagannathan et al. [30][24] ✓   ✓      
Aleyadeh and Taha [39][33]     ✓ ✓ ✓ ✓
Wandee et al. [40][34] ✓   ✓ ✓    
Sosunova and Porras [41][35]   ✓ ✓ ✓ ✓ ✓
Widaningsih and Suheri [31][25] ✓     ✓    

References

  1. Argulwar, P.; Borse, S.; Argulwar, K.N.; Gurunathappa, U.S. IoT-Based Smart Garbage Management System. In Proceedings of the International Conference on Intelligent Computing and Applications (ICICA), Chennai, India, 10–11 March 202; Springer: Berlin/Heidelberg, Germany, 2018; pp. 237–245.
  2. Podlasek, A.; Jakimiuk, A.; Vaverková, M.D.; Koda, E. Monitoring and assessment of groundwater quality at landfill sites: Selected case studies of Poland and the Czech Republic. Sustainability 2021, 13, 7769.
  3. Aparna, H.; Bhumijaa, B.; Avila, J.; Thenmozhi, K.; Amirtharaja, R.; Praveenkumar, P.; Umamaheswari, B. IoT Assisted Waste Collection and Management System Using QR Codes. In Proceedings of the International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 27–29 January 2021; pp. 1–4.
  4. Anh Khoa, T.; Phuc, C.H.; Lam, P.D.; Nhu, L.M.B.; Trong, N.M.; Phuong, N.T.H.; Dung, N.V.; Tan-Y, N.; Nguyen, H.N.; Duc, D.N.M. Waste Management System Using IoT-Based Machine Learning in University. Wirel. Commun. Mob. Comput. 2020, 2020, 6138637.
  5. Knickmeyer, D. Social factors influencing household waste separation: A literature review on good practices to improve the recycling performance of urban areas. J. Clean. Prod. 2020, 245, 118605.
  6. Fatimah, Y.A.; Govindan, K.; Murniningsih, R.; Setiawan, A. Industry 4.0 based sustainable circular economy approach for smart waste management system to achieve sustainable development goals: A case study of Indonesia. J. Clean. Prod. 2020, 269, 122263.
  7. Taelman, S.E.; Tonini, D.; Wandl, A.; Dewulf, J. A Holistic Sustainability Framework for Waste Management in European Cities Concept Development. Sustainability 2018, 10, 2184.
  8. Gaikwad, M.; Gayke, A.; Kamble, P.; Pisal, S.; Tilekar, S. Smart Waste Management System Using IoT Based Dustbin and QR System. Int. J. Adv. Sci. Res. Eng. Trends 2021, 6, 18–21.
  9. Pardini, K.; Rodrigues, J.J.; Diallo, O.; Das, A.K.; de Albuquerque, V.H.C.; Kozlov, S.A. A Smart Waste Management Solution Geared Towards Citizens. Sensors 2020, 20, 2380.
  10. Sheng, T.J.; Islam, M.S.; Misran, N.; Baharuddin, M.H.; Arshad, H.; Islam, M.R.; Chowdhury, M.E.; Rmili, H.; Islam, M.T. An Internet of Things Based Smart WasTe Management System Using LoRa and Tensorflow Deep Learning Model. IEEE Access 2020, 8, 148793–148811.
  11. Rogoff, M.J.; Ross, D.; Wood, J.L. Automated Waste Collection–How to Make Sure It Makes Sense for Your Community. Am. Public Work. Assoc. Report. 2010, 77, 44–48.
  12. Glouche, Y.; Sinha, A.; Couderc, P. A smart waste management with self-describing complex objects. Int. J. Adv. Intell. Syst. 2015, 8, 1–16.
  13. Glouche, Y.; Couderc, P. A Smart Waste Management with Self-Describing Objects. In Proceedings of the International Conference on Smart Systems, Devices and Technologies (SMART), Rome, Italy, 23–28 June 2013.
  14. Pelonero, L.; Fornaia, A.; Tramontana, E. From Smart City to Smart Citizen: Rewarding Waste Recycle by Designing a Data-Centric IOT Based Garbage Collection Service. In Proceedings of the International Conference on Smart Computing (SMARTCOMP), Bologna, Italy, 14–17 September 2020; pp. 380–385.
  15. Jaid Jim, A.A.; Kadir, R.; Mamun, M.A.A.; Nahid, A.A.; Ali, M.Y. A noble proposal for Internet of garbage bins (IoGB). Smart Cities 2019, 2, 214–229.
  16. Smart Cities Council. Mangaluru Smart City Begins QR Code Based House-to-House Garbage Collection. Available online: https://www.smartcitiescouncil.com/article/mangaluru-smart-city-begins-qr-code-based-house-house-garbage-collection (accessed on 15 September 2023).
  17. Mangalore City. Smart Way to Collect Waste in Smart City Mangalore by Using QR Codes. Available online: https://mangalorecity.in/smart-way-to-collect-waste-in-smart-city-mangalore-by-using-qr-codes-check-out-how/ (accessed on 15 September 2023).
  18. SmartCitiesWorld News. Seoul to Use QR Codes for Smarter Management of Trash Bins. Available online: https://www.smartcitiesworld.net/news/news/seoul-to-use-qr-codes-for-smarter-management-of-trash-bins-6967 (accessed on 15 September 2023).
  19. NDTV. Greater Noida to Go Hi-Tech for Door-to-Door Waste Collection with GPS, CCTVs. Available online: https://www.ndtv.com/india-news/qr-code-gps-and-cctv-greater-noida-authority-to-go-hi-tech-for-door-to-door-waste-collection-2539684 (accessed on 15 September 2023).
  20. News18 Telugu. Garbage Collection with QR Code Scanning-Ideal Standing Municipality. Available online: https://pipanews.com/garbage-collection-with-qr-code-scanning-ideal-standing-municipality-news18-telugu/ (accessed on 15 September 2023).
  21. Panainte-Lehadus, M.; Vulpe, M.; Nedeff, V.; Mosnegutu, E.; Przydatek, G.; Tomozei, C.; Chitimus, D. Study on the Method of Household Waste Collection: Case Study. Appl. Sci. 2022, 12, 7490.
  22. Othman, H.; Petra, M.I.; De Silva, L.C.; Caesarendra, W. Automated trash collector design. J. Phys. Conf. Ser. 2020, 1444, 012040.
  23. Vishnu, S.; Ramson, S.J.; Senith, S.; Anagnostopoulos, T.; Abu-Mahfouz, A.M.; Fan, X.; Srinivasan, S.; Kirubaraj, A.A. IoT-Enabled solid waste management in smart cities. Smart Cities 2021, 4, 1004–1017.
  24. Jagannathan, U.K.; Balaji, N.; Brunda, A.; Gagan, M. QR Code Enabled Domestic Waste Segregation Tracking. In Proceedings of the International Conference on Industrial Engineering and Operations Management, Istanbul, Turkey, 7–10 March 2022.
  25. Widaningsih, S.; Suheri, A. Design of Waste Management System Using QR Code for Effective Management in Wastebank. J. Phys. Conf. Ser. 2021, 1764, 012066.
  26. Zhang, Q.; Li, H.; Wan, X.; Skitmore, M.; Sun, H. An intelligent waste removal system for smarter communities. Sustainability 2020, 12, 6829.
  27. Hannan, M.; Al Mamun, M.A.; Hussain, A.; Basri, H.; Begum, R.A. A review on technologies and their usage in solid waste monitoring and management systems: Issues and challenges. Waste Manag. 2015, 43, 509–523.
  28. Anjum, M.; Sarosh Umar, M.; Shahab, S. Analysis of IoT and Communication Technologies to Develop Waste Management Service Framework for Smart City. In Proceedings of the International Conference on Sustainable Expert Systems (ICSES), Lalitpur, Nepal, 9–10 September 2022; Springer: Singapore, 2022; pp. 691–707.
  29. Anjum, M.; Shahab, S.; Umar, M.S. Smart Waste Management Paradigm in Perspective of IoT and Forecasting Models. Int. J. Environ. Waste Manag. 2022, 29, 34–79.
  30. Nguyen, S.T.; Le, B.N.; Dao, Q.X. AI and IoT-powered Smart University Campus: Design of Autonomous Waste Management. In Proceedings of the International Symposium on Electrical and Electronics Engineering (ISEE), Ho Chi Minh, Vietnam, 15–16 April 2021; pp. 139–144.
  31. Metagar, S.M.; Sayyed, F.R.; Singhvi, P. Garbage Management System Using Arduino Device to support Swachh Bharath Mission. In Proceedings of the OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON), Raigarh, India, 8–10 February 2023; pp. 1–6.
  32. Pardini, K.; Rodrigues, J.J.; Hassan, S.A.; Kumar, N.; Furtado, V. Smart Waste Bin: A New Approach for Waste Management in Large Urban Centers. In Proceedings of the Vehicular Technology Conference (VTC-Fall), Chicago, IL, USA, 27–30 August 2018; pp. 1–8.
  33. Aleyadeh, S.; Taha, A.E.M. An IoT-Based architecture for waste management. In Proceedings of the International Conference on Communications Workshops (ICC Workshops), Kansas City, MO, USA, 20–24 May 2018; pp. 1–4.
  34. Wandee, P.; Bussabong, Z.; Duangkum, S. Application for a Waste Management via the QR-Code System. Int. J. Adv. Comput. Sci. Appl. 2022, 13, 659–664.
  35. Sosunova, I.; Porras, J. IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review. IEEE Access 2022, 10, 73326–73363.
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