sc 23(4): e4

Research Article

Intelligent Dashboards to Monitor the Occurrences in Smart Cities – A Portuguese Case Study

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  • @ARTICLE{10.4108/eetsc.v6i4.2796,
        author={Rita Silva and Maria Silva and Gustavo Caldas and Filipe Portela and Henrique Santos},
        title={Intelligent Dashboards to Monitor the Occurrences in Smart Cities -- A Portuguese Case Study},
        journal={EAI Endorsed Transactions on Smart Cities},
        volume={6},
        number={4},
        publisher={EAI},
        journal_a={SC},
        year={2022},
        month={12},
        keywords={Big Data, Data Science, Smart Cities, Business Intelligence, Intervention Requests},
        doi={10.4108/eetsc.v6i4.2796}
    }
    
  • Rita Silva
    Maria Silva
    Gustavo Caldas
    Filipe Portela
    Henrique Santos
    Year: 2022
    Intelligent Dashboards to Monitor the Occurrences in Smart Cities – A Portuguese Case Study
    SC
    EAI
    DOI: 10.4108/eetsc.v6i4.2796
Rita Silva1, Maria Silva1, Gustavo Caldas1, Filipe Portela1,*, Henrique Santos1
  • 1: University of Minho
*Contact email: cfp@dsi.uminho.pt

Abstract

This article concerns the needed response by the Professional Fire Brigade Regiment (FBR) in the city of Lisbon. To solve and answer the question "How to improve FBR intervention requests when an emergency is detected?" the project aims to create a functional prototype containing interactive dashboards allowing the analysis of indicators that improve decision capacity. As results attest, 58% of false alarms are cancelled even after the emergency and rescue means have been activated to the location. About 97% of the suspended requests are not cancelled before the means are sent. The number of records of occurrences tends to increase over the 8 years of study. Sunday is the weekday with the highest number of associated records, with 23.33%, specifically at 9 am and 8 pm. Autumn is the season with more occurrences, with 26.51%. More than 50% of the occurrences are in the administrative services closing time and more than 50% of the registrations send only one vehicle to the place. These indicators aim to understand if these variables are probabilistically associated with requests for interventions to be able to anticipate these scenarios and help in decision-making whenever necessary.