Crowd Management: A New Challenge for Urban Big Data Analytics

Autor(es)

Celes, Clayson ^{[1, 2]} ; Boukerche, Azzedine ^[3] ; Loureiro, Antonio A. F. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Fed Minas Gerais, Belo Horizonte, MG - Brazil

^[2] Univ Ottawa, Comp Sci, Ottawa, ON - Canada

^[3] Univ Ottawa, Ottawa, ON - Canada

• Tipo de documento: Artigo Científico
• Fonte: IEEE COMMUNICATIONS MAGAZINE; v. 57, n. 4, p. 20-25, APR 2019.
• Citações Web of Science: 0

Resumo

The increasing availability of tremendous amounts of data generated by people, vehicles, and things have provided unprecedented opportunities for understanding human behavior in the urban environment. At the same time, crowd management systems can benefit city planning, emergency control, and mobile network design. In this work, we exploit urban data as a way of analyzing crowd behavior. We analyze the types of crowd situations, describe the major types of urban data, and highlight their strengths and weaknesses. We then discuss the key research challenges and opportunities in the analysis of urban environments. Moreover, through case studies, we explain how to apply urban data for spatial, temporal, and semantic observations of crowd situations. (AU)

• Processo FAPESP: 15/24536-2 - Projeto de serviços e aplicações para IOT
• Beneficiário: Antonio Alfredo Ferreira Loureiro
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 15/24494-8 - Comunicação e processamento de big data em nuvens e névoas computacionais
• Beneficiário: Nelson Luis Saldanha da Fonseca
• Modalidade de apoio: Auxílio à Pesquisa - Temático