Utilizando visão computacional para avaliação equitativa de propriedades em áreas urbanas

Autores

DOI:

https://doi.org/10.33448/rsd-v14i7.48995

Palavras-chave:

Inteligência Artificial, Visão Computacional, Áreas Urbanas, Avaliação Equitativa, Avaliação de Imóveis, Cidades Inteligentes.

Resumo

O objetivo do presente artigo é apresentar um estudo sobre a utilização da visão computacional baseada em IA (Inteligência Artificial) para avaliação equitativa de propriedades em áreas urbanas. Esta revisão sistemática da literatura explora o campo emergente da aplicação da Inteligência Artificial, em especial da visão computacional, para aprimorar a equidade, a precisão e a eficiência na avaliação de propriedades em ambientes urbanos. Baseando-se em uma ampla gama de artigos acadêmicos — incluindo discussões sobre IA em cidades inteligentes, aplicações de visão computacional e metodologias de revisão sistemática —, este estudo sintetiza o conhecimento atual sobre o potencial da visão computacional orientada por IA para superar as limitações dos métodos convencionais e contribuir para um desenvolvimento urbano mais equitativo.

Referências

Ahn, M. J., & Chen, Y.-C. (2020). Artificial intelligence in government. Proceedings of the 21st Annual International Conference on Digital Government Research. https://doi.org/10.1145/3396956.3398260

Al-Ansi, A. M., Garad, A., Jaboob, M., & Al-Ansi, A. (2024). Elevating e-government: Unleashing the power of AI and IoT for enhanced public services. SSRN. https://doi.org/10.2139/ssrn.4883206

Antwi, B. O., Adelakun, B. O., & Eziefule, A. O. (2024). Transforming financial reporting with AI: Enhancing accuracy and timeliness. International Journal of Advanced Economics, 6(6), 205-223. https://doi.org/10.51594/ijae.v6i6.1229

Ardabili, B. R., Pazho, A. D., Noghre, G. A., Neff, C., Bhaskararayuni, S. D., Ravindran, A., Reid, S., & Tabkhi, H. (2023). Understanding policy and technical aspects of AI-enabled smart video surveillance to address public safety. arXiv. https://doi.org/10.48550/arxiv.2302.04310

Bibri, S. E., Huang, J., Jagatheesaperumal, S. K., & Krogstie, J. (2024). The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review. Environmental Science and Ecotechnology, 20, 100433. https://doi.org/10.1016/j.ese.2024.100433

Chen, Y.-C., Ahn, M. J., & Wang, Y. (2023). Artificial intelligence and public values: Value impacts and governance in the public sector. Sustainability, 15(6), 4796. https://doi.org/10.3390/su15064796

Crossetti, M. da G. O. (2012). Revisão integrativa de pesquisa na enfermagem o rigor cientifico que lhe é exigido. Revista Gaúcha de Enfermagem, 33(2), 8-9. https://doi.org/10.1590/S1983-14472012000200001

Gupta, R., Reebadiya, D., & Tanwar, S. (2021). 6G-enabled edge intelligence for ultra-reliable low latency applications: Vision and mission. Computer Standards & Interfaces, 77, 103521. https://doi.org/10.1016/j.csi.2021.103521

Hamirul, Darmawanto, Elsyra, N., & Syahwami. (2023). The role of artificial intelligence in government services: A systematic literature review. Open Access Indonesia Journal of Social Sciences, 6(3), 998-1003. https://doi.org/10.37275/oaijss.v6i3.163

Himeur, Y., Sayed, A. N., Alsalemi, A., Bensaali, F., & Amira, A. (2023). Edge AI for internet of energy: Challenges and perspectives. Internet of Things, 25, 101035. https://doi.org/10.1016/j.iot.2023.101035

Liu, Y., Yang, D., Wang, Y., Liu, J., Liu, J., Boukerche, A., Sun, P., & Song, L. (2024). Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models. ACM Computing Surveys, 56(7), 1-38.

Lotlikar, P., & Mohs, J. N. (2021). Examining the role of artificial intelligence on modern auditing techniques. Strategic Management Quarterly, 9(2). https://doi.org/10.15640/smq.v9n2a1

Margetts, H. (2022). Rethinking AI for good governance. Daedalus, 151(2), 360-371. https://doi.org/10.1162/daed_a_01922

Messaoudi, M. D., Ménélas, B.-A. J., & Mcheick, H. (2022). Review of navigation assistive tools and technologies for the visually impaired. Sensors, 22(20), 7888. https://doi.org/10.3390/s22207888

Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104. https://doi.org/10.1016/j.ijinfomgt.2020.102104

Ochoa-Ruiz, G., Angulo-Murillo, A. A., Ochoa, A., Aguilar-Lobo, L. M., Vega-Fernández, J. A., & Natraj, S. (2020). An asphalt damage dataset and detection system based on RetinaNet for road conditions assessment. Applied Sciences, 10(11), 3974. https://doi.org/10.3390/app10113974

Pan, Y., & Zhang, L. (2020). Roles of artificial intelligence in construction engineering and management: A critical review and future trends. Automation in Construction, 122, 103517. https://doi.org/10.1016/j.autcon.2020.103517

Pereira, A. S., Shitsuka, D. M., Parreira, F. J., & Shitsuka, R. (2018). Metodologia de pesquisa científica. Editora da UAB/NTE/UFSM.

Reades, J., De Souza, J., & Hubbard, P. (2018). Understanding urban gentrification through machine learning. Urban Studies, 56(5), 922-942. https://doi.org/10.1177/0042098018789054

Rjab, A. B., & Mellouli, S. (2019). Artificial intelligence in smart cities. Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance. https://doi.org/10.1145/3326365.3326400

Roberts, A., & Goullette, S. (1996). CCTV surveillance: The local authority's role - A review of current practice. *Proceedings of the Institution of Civil Engineers - Municipal Engineer, 115*(2), 61-67. https://doi.org/10.1680/imuen.1996.28908

Sagayam, K. M., Winston, J. J., Wahab, M. H. A., Bhushan, B., Ambar, R., & Poad, H. M. (2021). Combination of thermal and sRGB imaging techniques for advanced surveillance system. Annals of Emerging Technologies in Computing, 5(5), 27-33. https://doi.org/10.33166/aetic.2021.05.003

Shah, N., Bhagat, N., & Shah, M. (2021). Crime forecasting: A machine learning and computer vision approach to crime prediction and prevention. Visual Computing for Industry, Biomedicine, and Art, 4(1). https://doi.org/10.1186/s42492-021-00087-9

Spencer, B. F., Hoskere, V., & Narazaki, Y. (2019). Advances in computer vision-based civil infrastructure inspection and monitoring. Engineering, 5(2), 199-222. https://doi.org/10.1016/j.eng.2018.11.030

Surianarayanan, C., Lawrence, J. J., Chelliah, P. R., Prakash, E., & Hewage, C. (2023). A survey on optimization techniques for edge artificial intelligence (AI). Sensors, 23(3), 1279. https://doi.org/10.3390/s23031279

Valle-Cruz, D., Ruvalcaba-Gómez, E. A., Sandoval-Almazán, R., & Criado, J. I. (2019). A review of artificial intelligence in government and its potential from a public policy perspective. Proceedings of the 20th Annual International Conference on Digital Government Research (pp. 91-99). ACM. https://doi.org/10.1145/3325112.3325242

Vanky, A., & Le, R. (2023). Urban-semantic computer vision: A framework for contextual understanding of people in urban spaces. AI & Society, 38(3), 1193-1207. https://doi.org/10.1007/s00146-022-01625-6

Vijeikis, R., Raudonis, V., & Dervinis, G. (2022). Efficient violence detection in surveillance. Sensors, 22(6), 2216. https://doi.org/10.3390/s22062216

Wang, D., Lu, C.-T., & Fu, Y. (2023). Towards automated urban planning: When generative and ChatGPT-like AI meets urban planning. arXiv. https://doi.org/10.48550/arxiv.2304.03892

Yiğitcanlar, T., Agdas, D., & Degirmenci, K. (2022). Artificial intelligence in local governments: Perceptions of city managers on prospects, constraints and choices. AI & Society, 38(3), 1135-1150. https://doi.org/10.1007/s00146-022-01450-x

Yiğitcanlar, T., & Cugurullo, F. (2020). The sustainability of artificial intelligence: An urbanistic viewpoint from the lens of smart and sustainable cities. Sustainability, 12(20), 8548. https://doi.org/10.3390/su12208548

Yiğitcanlar, T., David, A., Li, W., Fookes, C., Bibri, S. E., & Ye, X. (2024). Unlocking artificial intelligence adoption in local governments: Best practice lessons from real-world implementations. Smart Cities, 7(4), 1576-1625. https://doi.org/10.3390/smartcities7040064

Yiğitcanlar, T., Desouza, K. C., Butler, L., & Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13(6), 1473. https://doi.org/10.3390/en13061473

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Publicado

2025-07-02

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Ciências Exatas e da Terra

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Utilizando visão computacional para avaliação equitativa de propriedades em áreas urbanas. Research, Society and Development, [S. l.], v. 14, n. 7, p. e0314748995, 2025. DOI: 10.33448/rsd-v14i7.48995. Disponível em: https://rsdjournal.org/rsd/article/view/48995. Acesso em: 5 dez. 2025.