Visual Observation to Detect Macroplastic Object in River: A Review of Current Knowledge

Authors

  • Nani Anggraini The University of Kitakyushu
  • Irfan Tawakkal Universitas Hasanuddin
  • Djusdil Akrim Universitas Bosowa
  • Indriyani Rachman The University of Kitakyushu
  • Toru Matsumoto The University of Kitakyushu

DOI:

https://doi.org/10.23969/jcbeem.v8i1.12254

Keywords:

microplastic, Visual Observation, Object Detection, Water Bodies, River

Abstract

Currently, the world is facing the problem of plastic pollution in water bodies. Plastic waste has become an abundant pollutant in the marine, coastal and river environments, making it a major threat to aquatic life. Visual Observation in plastic monitoring is a popular method used to measure quantity, composition, and distribution, identify emerging trends, and design preventive measures or mitigation strategies. This study attempts to review recent studies regarding visual observation for detecting macroplastic objects in terms of current research trends and methodologies and suggests promising future research directions. This study used a systematic method with a bibliometric approach and qualitative content analysis to identify and review 108 articles on detecting litter objects in the water. The study results show that automatic object detection is starting to become a trend in visual Observation by relying on artificial intelligence (AI) with UAV devices and cameras that are processed using Machine Learning and Deep Learning methods which provide promising accuracy results.

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References

A. B. D. Nandiyanto, M. K. Biddinika, and F. Triawan, “How bibliographic dataset portrays decreasing number of scientific publication from Indonesia,” Indones. J. Sci. Technol., vol. 5, no. 1, pp. 154–175, Feb. 2020, doi: 10.17509/ijost.v5i1.22265.

A. L. Andrady and M. A. Neal, “Applications and societal benefits of plastics,” Philos. Trans. R. Soc. B Biol. Sci., vol. 364, no. 1526, pp. 1977–1984, Jul. 2009, doi: 10.1098/rstb.2008.0304.

B. Fang et al., “Artificial intelligence for waste management in smart cities: a review,” Environ. Chem. Lett., vol. 21, no. 4, pp. 1959–1989, Aug. 2023, doi: 10.1007/s10311-023-01604-3.

B. Gewert, M. Ogonowski, A. Barth, and M. MacLeod, “Abundance and composition of near surface microplastics and plastic debris in the Stockholm Archipelago, Baltic Sea,” Mar. Pollut. Bull., vol. 120, no. 1–2, pp. 292–302, Jul. 2017, doi: 10.1016/j.marpolbul.2017.04.062.

B. S. Ramadan, I. Rachman, N. Ikhlas, S. B. Kurniawan, M. F. Miftahadi, and T. Matsumoto, “A comprehensive review of domestic-open waste burning: recent trends, methodology comparison, and factors assessment,” J. Mater. Cycles Waste Manag., vol. 24, no. 5, pp. 1633–1647, Sep. 2022, doi: 10.1007/s10163-022-01430-9.

C. Chen, “Science Mapping: A Systematic Review of the Literature,” J. Data Inf. Sci., vol. 2, no. 2, pp. 1–40, Mar. 2017, doi: 10.1515/jdis-2017-0006.

C. Martin, S. Parkes, Q. Zhang, X. Zhang, M. F. McCabe, and C. M. Duarte, “Use of unmanned aerial vehicles for efficient beach litter monitoring,” Mar. Pollut. Bull., vol. 131, pp. 662–673, Jun. 2018, doi: 10.1016/j.marpolbul.2018.04.045.

H. Ritchie and M. Roser, “Plastic Pollution,” Plastic Pollution, 2022. https://ourworldindata.org/plastic-pollution

L. Fallati, A. Polidori, C. Salvatore, L. Saponari, A. Savini, and P. Galli, “Anthropogenic Marine Debris assessment with Unmanned Aerial Vehicle imagery and deep learning: A case study along the beaches of the Republic of Maldives,” Sci. Total Environ., vol. 693, p. 133581, Nov. 2019, doi: 10.1016/j.scitotenv.2019.133581.

L. Lebreton and A. Andrady, “Future scenarios of global plastic waste generation and disposal,” Palgrave Commun., vol. 5, no. 1, p. 6, Jan. 2019, doi: 10.1057/s41599-018-0212-7.

L. Xie, Z. Chen, H. Wang, C. Zheng, and J. Jiang, “Bibliometric and Visualized Analysis of Scientific Publications on Atlantoaxial Spine Surgery Based on Web of Science and VOSviewer,” World Neurosurg., vol. 137, pp. 435-442.e4, May 2020, doi: 10.1016/j.wneu.2020.01.171.

M. Geraeds, T. Van Emmerik, R. De Vries, and M. S. Bin Ab Razak, “Riverine Plastic Litter Monitoring Using Unmanned Aerial Vehicles (UAVs),” Remote Sens., vol. 11, no. 17, p. 2045, Aug. 2019, doi: 10.3390/rs11172045.

M. Nur, I. Hamidah*, A. Permanasari, A. Gafar, I. Rachman, and T. Matsumoto, “Low Carbon Education: A Review and Bibliometric Analysis,” Eur. J. Educ. Res., vol. 9, no. 1, pp. 319–329, Jan. 2020, doi: 10.12973/eu-jer.9.1.319.

M. Soori, B. Arezoo, and R. Dastres, “Artificial intelligence, machine learning and deep learning in advanced robotics, a review,” Cogn. Robot., vol. 3, pp. 54–70, 2023, doi: 10.1016/j.cogr.2023.04.001.

N. Anggraini, R. Muis, F. Ariani, S. Yunus, and . S., “Model of Solid Waste Management (SWM) in Coastal Slum Settlement: Evidence for Makassar City,” Nat. Environ. Pollut. Technol., vol. 20, no. 2, Jun. 2021, doi: 10.46488/NEPT.2021.v20i02.002.

N. J. Van Eck and L. Waltman, “Software survey: VOSviewer, a computer program for bibliometric mapping,” Scientometrics, vol. 84, no. 2, pp. 523–538, Aug. 2010, doi: 10.1007/s11192-009-0146-3.

O. Klapka and A. Slaby, “Visual Analysis of Search Results in Scopus Database,” in Digital Libraries for Open Knowledge, E. Méndez, F. Crestani, C. Ribeiro, G. David, and J. C. Lopes, Eds., in Lecture Notes in Computer Science, vol. 11057. Cham: Springer International Publishing, 2018, pp. 340–343. doi: 10.1007/978-3-030-00066-0_36.

R. Geyer, J. R. Jambeck, and K. L. Law, “Production, use, and fate of all plastics ever made,” Sci. Adv., vol. 3, no. 7, p. e1700782, Jul. 2017, doi: 10.1126/sciadv.1700782.

R. Muis, N. Anggraini, F. Ariani, S. Yunus, and . Z., “Survey of Environmental Baseline in the Nunukan Agriculture Area, Indonesia,” Nat. Environ. Pollut. Technol., vol. 20, no. 1, pp. 237–242, Mar. 2021, doi: 10.46488/NEPT.2021.v20i01.025.

S. Armitage, K. Awty-Carroll, D. Clewley, and V. Martinez-Vicente, “Detection and Classification of Floating Plastic Litter Using a Vessel-Mounted Video Camera and Deep Learning,” Remote Sens., vol. 14, no. 14, p. 3425, Jul. 2022, doi: 10.3390/rs14143425.

T. Miles-Board, “From people to reefs: marine debris and plastic pollution in North Queensland”.

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, vol. 521, no. 7553, pp. 436–444, May 2015, doi: 10.1038/nature14539.

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Published

2024-03-16

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