UAI-FI: using artificial intelligence for automatic passenger counting through Wi-Fi and GPS data

Authors

DOI:

https://doi.org/10.14295/transportes.v30i2.2555

Keywords:

Passenger counting, Bus load, Wi-Fi, Machine learning

Abstract

An important piece of information for planning public transportation is the number of passengers using the system. Several initiatives have started to explore the Wi-Fi packets generated by passengers’ smartphones as means to obtain this information. A sensing device located inside the bus can intercept and collect these packets. By applying filters, e.g., verifying if the signal strength is higher than a threshold, the sensor can infer passengers' presence/absence. However, such limits are set arbitrarily, leading to errors, for example, when close to bus stops. To address this issue, this article proposes a method (UAI-FI) based on an artificial intelligence technique (Support Vector Machine) to classify the origin of packets as inside or outside the bus. To validate UAI-FI, we applied and compared our approach to other methods in a bus line in Goiânia/Brazil. The results suggest that UAI-FI outperformed existing methods. Furthermore, it successfully classified the packet’s origin, obtaining 83.3% and 88.5% of the total number of passengers boarding and alighting the line. Despite the overall similarity, we highlight that UAI-FI’s counting curve presented a delay compared to the manual count indicating that the frequency that Wi-Fi packets are sent can cause the presence/absence of passengers to be perceived at different stops.

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Author Biographies

Marcos Paulino Roriz Junior, Federal University of Goiás, Goiás – Brazil

Possui graduação em Ciências da Computação pelo Instituto de Informática (INF) da Universidade Federal de Goiás (UFG), mestrado em Ciências da Computação pelo mesmo instituto e universidade (INF/UFG) e doutorado em Informática pela Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio). É professor adjunto do curso de Engenharia de Transportes da Universidade Federal de Goiás. Também é membro do Programa de Pós-graduação em Engenharia de Produção (PPGEP) e do Mestrado Profissional em Administração Pública (PROFIAP), ambos da UFG. Seus interesses de pesquisa e área de atuação concentram-se em aplicar e investigar métodos computacionais para planejar, construir, otimizar e avaliar Sistemas Inteligentes de Transporte e Iniciativas de Cidades Inteligentes por meio das seguintes técnicas: Inteligência Artificial (Machine/Deep Learning, Fuzzy Logic, e Computação Evolutiva), Algoritmos e Plataformas de Middleware para Processamento de Fluxo de (Big) Data, Internet das Coisas e Rede de Sensores Sem Fio. Também atua na investigação dos impactos e efeitos colaterais de tais sistemas na sociedade (PROFIAP).

Ronny Marcelo Aliaga Medrano, Federal University of Goiás, Goiás – Brazil

Possui graduação em engeharia civil - ESCUELA MILITAR DE INGENIERIA (2006) e mestrado em Transportes pela Universidade de Brasília (2012). Doutor em Transporte pela Universidade de Brasilia (2016). Atuo profissionalmente como analista de transporte na prefeitura do Governo municipal de La Paz, Bolivia. Como assessor técnico na Empresa de Planejamento e Logística S.A. do Ministerio do Transporte do Brasil, com enfase no desenvolvimento do modelo de transporte do Plano Nacional de Logística Integrada. Como consultor em estudos de demanda para projetos ferroviarios, planos de mobilidade, planos de transporte público. Atualmente é professor do Curso de Engenharia de Transporte da Universidade Federal de Goiás. Trabalha na linha de pesquisa de Inovação, Inteligência em Transporte, com ênfase em Planejamento de Transportes, atuando principalmente nos seguintes temas: Micro simulação e Macrosimulação de sistemas de transporte, Data science in transportation, Modelos de transporte, Comportamento em Transporte, Space-time geography, Inteligência Artificial.

Cristiano Farias Almeida, Federal University of Goiás, Goiás – Brazil

Possui graduação em Engenharia Civil pela Universidade Federal do Pará (1999), mestrado em Transportes pela Universidade de Brasília (2001), doutorado em Transportes pelo Nagoya Institute of Technology no Japão e pela Universidade de Brasília (2008), e Pós-Doutorado em Desenvolvimento de Cluster Logístico pela Université de Liège na Bélgica (2020). Atualmente é Professor Associado, Classe D, Nível 1 da Universidade Federal de Goiás. É professor permanente do Programa de Pós-Graduação Projeto e Cidade (FAV/UFG). É coordenador do Núcleo de Pesquisa em Transportes (NPT-UFG). Ex-bolsista da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). Ex-bolsista do Ministério da Educação, Cultura, Desporto, Ciência e Tecnologia do Japão (Monbukagakusho). Ex-bolsista do Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Ex-bolsista do Wallonie-Bruxelles Internacional.be (WBI). É atualmente Embaixador do Wallonie-Bruxelles Internacional.be (WBI) no Brasil. Elaborou o projeto de implantação do primeiro curso de Engenharia de Transportes Bacharelado da Universidade Federal de Goiás, do qual desempenhou função de Coordenador entre 2015 e 2018. Foi membro da Comissão de Implantação da Faculdade de Ciências e Tecnologia (FCT/UFG). Foi presidente do Núcleo Docente Estruturante (NDE) do curso de Engenharia de Transportes da UFG entre 2015 e 2018. Tem experiência na área de Engenharia de Transportes, com ênfase em Planejamento e Organização do Sistema de Transporte, atuando principalmente nos seguintes temas: transporte não-motorizado, transporte rodoviário semiurbano de passageiros, modelagem de redes de transportes, planejamento de transportes e desenvolvimento econômico regional, planejamento, gestão e controle dos transportes, análise espacial aplicada ao planejamento dos transportes, geografia dos transportes, cluster e plataforma logística. 

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Imagem da capa, volume 30, número 2

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Published

2022-08-06

How to Cite

Roriz Junior, M. P. ., Aliaga Medrano, R. M. ., & Farias Almeida, C. . (2022). UAI-FI: using artificial intelligence for automatic passenger counting through Wi-Fi and GPS data . TRANSPORTES, 30(2), 2555. https://doi.org/10.14295/transportes.v30i2.2555

Issue

Vol. 30 No. 2 (2022)

Section

Artigos

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Copyright (c) 2022 Marcos Paulino Roriz Junior, Ronny Marcelo Aliaga Medrano, Ronny Marcelo Aliaga Medrano, Cristiano Farias Almeida, Cristiano Farias Almeida

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