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Open Access

Turning Trash into Treasure: Developing an Intelligent Bin for Plastic Bottle Recycling

Institute of Information Technology, Jahangirnagar University, Dhaka 1342, Bangladesh
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Abstract

Plastic pollution has emerged as a major global concern due to its enduring nature and limited recycling options. In response to this critical challenge, this paper presents a novel approach utilizing a Detection-Based Reward System (DBRS) alongside an innovative business model to promote effective plastic waste management, reduce plastic waste accumulation in the nature, and uphold environmental cleanliness. Leveraging the YOLOv5 algorithm for its exceptional accuracy, speed, and open-source availability, plastic bottle detection becomes a pivotal aspect of this system. Users seamlessly enroll in the system, triggering an automated detection process that computes reward points corresponding to their deposited plastic bottles. These reward points are meticulously stored within a centralized database. Beyond its operational facets, this comprehensive system encompasses a robust business model, strategically poised to capture widespread engagement with waste disposal practices, thereby contributing to the realization of Sustainable Development Goals (SDGs) geared towards fostering a healthier environment. Notably, the DBRS attains cutting-edge performance in plastic bottle detection, boasting an impressive mean Average Precision (mAP) of 0.973, underscoring its efficacy in tackling plastic pollution.

Keywords

deep learningsmart environmentYOLOv5business modelreward system

References

[1]

K. Pardini, J. J. P. C. Rodrigues, O. Diallo, A. K. Das, V. H. C. D. Albuquerque, and S. A. Kozlov, A smart waste management solution geared towards citizens, Sensors, vol. 20, no. 8, p. 2380, 2020.
DOI Google Scholar
[2]

S. Majchrowska, A. Mikołajczyk, M. Ferlin, Z. Klawikowska, M. A. Plantykow, A. Kwasigroch, and K. Majek, Deep learning-based waste detection in natural and urban environments, Waste Manag., vol. 138, pp. 274–284, 2022.
DOI Google Scholar
[3]

P. Singh and V. P. Sharma, Integrated plastic waste management: Environmental and improved health approaches, Procedia Environ. Sci., vol. 35, pp. 692–700, 2016.
DOI Google Scholar
[4]

D. K. A. Barnes, F. Galgani, R. C. Thompson, and M. Barlaz, Accumulation and fragmentation of plastic debris in global environments, Phil. Trans. R. Soc. B, vol. 364, no. 1526, pp. 1985–1998, 2009.
DOI Google Scholar
[5]
H. Ritchie, V. Samborska, and M. Roser, Plastic pollution, https://ourworldindata.org/plastic-pollution, 2023.
[6]

T. Gupta, R. Joshi, D. Mukhopadhyay, K. Sachdeva, N. Jain, D. Virmani, and L. Garcia-Hernandez, A deep learning approach based hardware solution to categorise garbage in environment, Complex Intell. Syst., vol. 8, no. 2, pp. 1129–1152, 2022.
DOI Google Scholar
[7]

X. Chen, Machine learning approach for a circular economy with waste recycling in smart cities, Energy Rep., vol. 8, pp. 3127–3140, 2022.
DOI Google Scholar
[8]
P. Chowdhury, R. Sen, D. Ray, P. Roy, and S. Sarkar, Garbage monitoring and disposal system for smart city using IoT, in Proc. 2 nd Int. Conf. Green Computing and Internet of Things (ICGCIoT), Bangalore, India, 2018, pp. 455–460.
DOI
[9]

A. Namoun, B. R. Hussein, A. Tufail, A. Alrehaili, T. A. Syed, and O. BenRhouma, An ensemble learning based classification approach for the prediction of household solid waste generation, Sensors, vol. 22, no. 9, p. 3506, 2022.
DOI Google Scholar
[10]
Z. Zhang, Q. Tong, C. Yi, X. Fu, J. Ai, and Z. Wang, The appropriate image enhancement method for underwater object detection, in Proc. IEEE 22 nd Int. Conf. Communication Technology (ICCT), Nanjing, China, 2022, pp. 1627–1632.
DOI
[11]

Z. Cao, F. Mei, D. Zhang, B. Liu, Y. Wang, and W. Hou, Recognition and detection of persimmon in a natural environment based on an improved YOLOv5 model, Electronics, vol. 12, no. 4, p. 785, 2023.
DOI Google Scholar
[12]

C. Jeyalakshmi, M. Alagarsamy, R. Kalaiarasan, M. Easwaran, Y. Thangavel, and P. Paramasivam, Plastic waste management system using metal shredder for clean environment, Adv. Mater. Sci. Eng., vol. 2022, p. 1598868, 2022.
DOI Google Scholar
[13]
A. Chitreddy, K. Gogineni, V. Anirudh, P. V. Akhilesh, K. K. Vamsi, and P. S. Latha, Application of sensors using IoT for waste management system, in Proc. Int. Conf. Intelligent Computing and Smart Communication 2019, Hyderabad, India, 2019, pp. 1565–1575.
DOI
[14]
R. K. Singhvi, R. L. Lohar, A. Kumar, R. Sharma, L. D. Sharma, and R. K. Saraswat, IoT based smart waste management system: India prospective, in Proc. 4 th Int. Conf. Internet of Things: Smart Innovation and Usages (IoT-SIU), Ghaziabad, India, 2019, pp. 1–6.
DOI
[15]
S. Sreejith, R. Ramya, R. Roja, and A. S. Kumar, Smart bin for waste management system, in Proc. 5 th Int. Conf. Advanced Computing & Communication Systems (ICACCS), Coimbatore, India, 2019, pp. 1079–1082.
DOI
[16]

E. Vrochidou, N. Kagkasidis, G. Koutaliaga, and C. Sgouros, iBIN: Intelligent monitoring system for recyclable materials using Arduino and the IoT, International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, vol. 5, no. 12, pp. 1–5, 2017.
DOI Google Scholar
[17]

B. J. Praveena, K. Bhagyalaxmi, and M. Priyanka, A secure incentive based waste monitoring system using IoT, AIP Conf. Proc., vol. 2424, no. 1, p. 060002, 2022.
DOI Google Scholar
[18]
K. Johar, A. Rajput, R. Kalra, and Nithyavathy, An edge-based dustbin for smart compacting and segregating, in Proc. 7 th IRC Conf. Science, Engineering and Technology, Singapore, 2022, pp. 583–595.
DOI
[19]
A. Gaddam and A. K. Nikhath, Smart dustbin: A reward provider, in Proc. Int. Conf. Advances in Computer Engineering and Communication Systems, Hyderabad, India, 2021, pp. 1–11.
DOI
[20]
R. Prokscha, M. Schneider, and A. Höß, Efficient edge deployment demonstrated on YOLOv5 and coral edge TPU, in Industrial Artificial Intelligence Technologies and Applications, O. Vermesan, F. Wotawa, M. D. Nava, and B. Debaillie, eds. New York, NY, USA: River Publishers, 2023, pp. 141–155.
DOI
[21]
N. Singh, P. Sastry, B. S. Niharika, A. Sinha, and V. Umadevi, Performance analysis of object detection algorithms for waste segregation, in Proc. 3 rd Int. Conf. Artificial Intelligence and Smart Energy (ICAIS), Coimbatore, India, 2023, pp. 940–945.
DOI
[22]
T. Mahendrakar, A. Ekblad, N. Fischer, R. White, M. Wilde, B. Kish, and I. Silver, Performance study of YOLOv5 and faster R-CNN for autonomous navigation around non-cooperative targets, in Proc. IEEE Aerospace Conf. (AERO), Big Sky, MT, USA, 2022, pp. 1–12.
DOI
[23]
E. W. Weisstein, Convex hull, https://mathworld.wolfram.com/ConvexHull.html, 2024.
[24]

P. Rathore and S. P. Sarmah, Modeling and identification of suitable motivational mechanism in the collection system of municipal solid waste supply chain, Waste Manag., vol. 129, pp. 76–84, 2021.
DOI Google Scholar
[25]
L. V. Vencer, Bottles synthetic images, https://www.kaggle.com/datasets/vencerlanz09/bottle-synthetic-images-dataset, 2022.
[26]
Kaggle, Plastic bottles in the wild image dataset, https://www.kaggle.com/datasets/siddharthkumarsah/plastic-bottles-image-dataset, 2023.
[27]
Kaggle, Plastic bottle, https://www.kaggle.com/datasets/munira1020/plastic-bottle, 2023.
Journal of Social Computing
Volume 5 Issue 1,
March 2024
Pages 1-14
DOI: 10.23919/JSC.2024.0001
Cite this article:
Munira S, Paul N, Alam MA, et al. Turning Trash into Treasure: Developing an Intelligent Bin for Plastic Bottle Recycling. Journal of Social Computing, 2024, 5(1): 1-14. https://doi.org/10.23919/JSC.2024.0001

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Received: 11 November 2023
Revised: 17 January 2024
Accepted: 31 January 2024
Published: 30 March 2024
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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