Principales Tendencias de Investigación en la Gestión de Residuos utilizando Inteligencia Artificial

Autores/as

  • Ing. Gloria M. Aponte F. Universidad Católica Andrés Bello image/svg+xml

DOI:

https://doi.org/10.5281/

Palabras clave:

gestión de residuos, inteligencia artificial, tendencias de la investigación, rendimiento, utilización

Resumen

La generación de residuos se ha convertido en un problema global debido al crecimiento demográfico, el desarrollo industrial, económico y social; por ello es un área de importante atención para minimizar el impacto ambiental y el riesgo de enfermedades en la población. El objetivo de este trabajo es presentar un análisis de las principales tendencias de investigación en la gestión de residuos utilizando inteligencia artificial mediante la evolución de las publicaciones en revistas y congresos especializados en el área. Se utilizó la investigación documental, aunada a la técnica de análisis bibliométrico y de contenido para examinar la información obtenida en el periodo 2015-2024. Se usó la base de datos Lens.org como fuente de información principal que mediante el uso de palabras clave a través de diferentes estrategias de búsquedas se recuperó la información relevante en el periodo indicado. Los principales resultados evidencian que la comunidad científica internacional presenta un gran interés en realizar investigación relacionada con mejorar la gestión de residuos utilizando la inteligencia artificial, y China es uno de los países líderes que aplica estas herramientas para gestionar los residuos. Las aguas residuales, residuos sólidos, de construcción, plásticos y generación de energía, son los principales residuos tratados con inteligencia artificial.

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Biografía del autor/a

  • Ing. Gloria M. Aponte F., Universidad Católica Andrés Bello

    Ingeniero Químico, Docente - Investigadora, Centro de Investigación y Desarrollo de Ingeniería, Facultad de Ingeniería, Universidad Católica Andrés Bello (UCAB). Venezuela.

Referencias

[1] Burduk, A. et al. (2022). Waste Management with the Use of Heuristic Algorithms and Internet of Things Technology. Sensors 2022, 22(22), 8786. https://doi.org/10.3390/s22228786

[2] Akhtar, M.; Hannan, M.A.; Begum, R.A.; Basri, H.; Scavino, E. (2017). Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization. Waste Management. 2017, 61, 117–118. https://doi.org/10.1016/j.wasman.2017.01.022

[3] World Bank Group (2022). Solid waste management. https://www.worldbank.org/en/topic/urbandevelopment/brief/solid-waste-management

[4] Karunambiga, K. & Sathiya, M. (2023). Technological View on Smart Waste Management. International Journal of Computer Applications Technology and Research. Volume 12–Issue 03, 30-31, 2023. D https://doi.org/10.7753/IJCATR1203.1008

[5] Alsabt, R.; Alkhaldi W.; Adenle Y.A.; Alshuwaikhat, H. M. (2024). Optimizing waste management strategies through artificial intelligence and machine learning - An economic and environmental impact study. Cleaner Waste Systems. Volume 8, August 2024. https://doi.org/10.1016/j.clwas.2024.100158.

[6] SWANA (2023). How AI is revolutionizing solid waste management. https://swana.org/news/blog/swana-post/swana-blog/2023/12/11/how-ai-is-revolutionizing-solid-waste-management

[7] Bingbing F., Jiacheng Y, Zhonghao Chen, Z.; et al. (2023). Artificial intelligence for waste management in smart cities: a review. Environmental Chemistry Letters (2023) 21:1959–1989 https://doi.org/10.1007/s10311-023-01604-3

[8] Nguyen, TD.; Cherif, R.; Mahieux, P-Y.; Jérome Lux, J.; Aït-Mokhtar, A. & Bastidas-Arteaga, E. Artificial intelligence algorithms for prediction and sensitivity analysis of mechanical properties of recycled aggregate concrete: A review. Journal of Building Engineering Année : 2023. https://10.1016/j.jobe.2023.105929

[9] Feroz, A.; Zo, H.; Chivaburi, A. (2021). Digital Transformation and Environmental Sustainability: A Review and Research Agenda. Sustainability 2021, 13(3), 1530. https://doi.org/10.3390/su13031530

[10] Ihsanullah, I.; Alam, G.; Jamal, A. & Shaik, F. (2022). Recent advances in applications of artificial intelligence in solid waste management: A review. ChemosphereVolume 309, Part 1, December 2022

[11] Abdallah, M.; Talib, MA. Feroz, S.; Nasir, Q.; Abdalla, H. & Mahfood, B. (2020). Artificial intelligence applications in solid waste management: A systematic research review. Waste management (New York, N.Y.), Volume: 109, pp. 231-246. May 15, 2020. https://doi.org/10.1016/j.wasman.2020.04.057

[12] Tran Luu, TN. Et al. (2023). AI application for solid waste sorting in Global South. https://sdgs.un.org/sites/default/files/2023-05/A41%20-%20Thien-An%20Tran%20Luu%20-%20AI%20Application%20for%20Solid%20Waste%20in%20the%20global%20south.pdf

[13] Zhang, Q., Yang, Q., Zhang, X., Bao, Q., Su, J., and Liu, X. (2021).Waste image classification based on transfer learning and convolutional neural network. Waste Management, 2021, 135, pp. 150-157. https://doi.org/10.1016/j.wasman.2021.08.038

[14] Nasir, I., & Aziz Al-Talib, G. A. (2023). Waste Classification Using Artificial Intelligence Techniques:Literature Review. Technium: Romanian Journal of Applied Sciences and Technology, 5, 49–59. https://doi.org/10.47577/technium.v5i.8345

[15] Sharma, P. & Vaid, U. (2021). Emerging role of artificial intelligence in waste management practices. IOP Conference. Series: Earth and Environmental Science 889 (2021) 012047 https://iopscience.iop.org/article/10.1088/1755-1315/889/1/012047/pdf

[16] Sami, K.; Amin, Z. & Hassan, R. (2020). Waste Management Using Machine Learning and Deep Learning Algorithms. International Journal on Perceptive and Cognitive Computing, 6(2), 97–106. https://doi.org/10.31436/ijpcc.v6i2.165

[17] Aponte, G. (2022). Panorama internacional de la economía circular a través del análisis de la producción científica y tecnológica. Tekhne 25(1), 2022, pp.18-30

[18] Kumari, N. et al. (2023). Role of Artificial Intelligence in Municipal Solid Waste Management. British Journal of Multidisciplinary And Advanced Studies. VOL. 4 NO. 3 (2023). https://doi.org/10.1016/j.jobe.2023.105929

[19] Shah K.B.;Visalakshi S. Guragain, D.P.; Panigrahi, R. (2024). Advancing smart city sustainability with Internet of Things and artificial intelligence aided low-cost digital twin systems for waste management. Microsystems Technology, 2024. https://doi.org/10.1007/s00542-024-05827-4

[20] Khan, D.; Samadder, S. (2014). Municipal solid waste management using Geographical Information System aided methods: A mini review.. Waste Management & Research. 2014;32(11):1049-1062.https://doi.org/10.1177/0734242X14554644

[21] Olawade, D.; Fapohunda, O.; Wada, O.; Usman, S. et al. (2024). Smart waste management: A paradigm shift enabled by artificial intelligence. Waste Management Bulletin. Volume 2, Issue 2, June 2024, Pages 244-263. https://doi.org/10.1016/j.wmb.2024.05.001

[22] Ferrer, J, Alba, E. (2019) BIN-CT: Urban Waste Collection based on Predicting the Container Fill Level Biosystems Vol. 186, December 2019, 103962. https://doi.org/10.1016/j.biosystems.2019.04.006

[23] Kontokosta, C.E.; Hong, B.; Johnson, N. E.; Starobin, D. (2018). Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities. Computers Environment and Urban Systems 70 151–162. https://doi.org/10.1016/j.compenvurbsys.2018.03.004.

[24] Bijos, J. et al. (2021). Towards Artificial Intelligence in Urban Waste Management: an early prospect for Latin America. IOP Conf. Series: Materials Science and Engineering 1196 (2021) 012030 doi:10.1088/1757-899X/1196/1/012030

[25] Costa, B.; Bernardes, A.; Pereira, J.; Zampa, V.; Pereira, V.; Matos, G.; Soares, E.; Soares, C. and Silva, A. (2018). Artificial Intelligence in Automated Sorting in Trash Recycling. Conference: XV Encontro Nacional de Inteligência Artificial e Computacional Porto Alegre: SBC pp 198–205

[26] Arayakandy, A.; Gupta, A. and Thakur, R. (2019). Design and Development of Classification Model for Recyclability Status of Trash Using SVM International. Journal for Research in Applied Science & Engineering Technology (IJRASET) 7 3, 2146–50. DOI: 10.22214/ijraset.2019.3396

[27] Bansal, S.; Patel, S.; Shah, I.; Patel, A.; Makwana, J.; Thakker, R. (2019). AGDC: Automatic Garbage Detection and Collection Robotics. https://arxiv.org/pdf/1908.05849#:~:text=AGDC%20is%20the%20robotic%20system,microcontroller%20controlling%20the%20robotic%20arm

[28] Shiraj, T.B. et al. (2024). Sustainable Waste Management System Using Artificial Intelligence and Satellite Communication: A Case Study. 2024 3rd International Conference on Advancement in Electrical and Electronic Engineering, ICAEEE 2024

[29] Thao, L.Q. (2023). An automated waste management system using artificial intelligence and robotics. Journal of Material Cycles and Waste Management. Volume 25, Issue 6, Pages 3791 - 3800November 2023

[30] Sroka, N. (2023). How AI is Revolutionizing Solid Waste Management. Recuperado de: https://swana.org/news/blog/swana-post/swana-blog/2023/12/11/how-ai-is-revolutionizing-solid-waste-management

[31] Statista (2024). Global population and municipal solid waste generation shares in 2018, by select country. https://www.statista.com/statistics/1026652/population-share-msw-generation-by-select-country/

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Publicado

2026-10-09

Número

Sección

Artículo de Revisión

Cómo citar

[1]
G. M. Aponte Figueroa, « Principales Tendencias de Investigación en la Gestión de Residuos utilizando Inteligencia Artificial», Publ.Cienc.Tecnol, vol. 19, n.º 1, pp. 4–21, oct. 2026, doi: 10.5281/.