Exploiting geospatial data of connectivity and urban infrastructure for efficient positioning of emergency detection units in smart cities

Peixoto, João Paulo Just; Bittencourt, João Carlos N.; Jesus, Thiago C.; Costa, Daniel G.; Portugal, Paulo; Vasques, Francisco

doi:10.1016/j.compenvurbsys.2023.102054

Computers, Environment and Urban Systems

2024

DOI: 10.1016/j.compenvurbsys.2023.102054

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Exploiting geospatial data of connectivity and urban infrastructure for efficient positioning of emergency detection units in smart cities

João Paulo Just Peixoto,

João Carlos N. Bittencourt,

Thiago C. Jesus

et al.

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Cited by 4 publications

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A cost-benefit secured DAG based analysis of distributed energy generation in urban settings

Jing,

Zhang,

et al. 2024

Sustainable Cities and Society

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A cost-benefit secured DAG based analysis of distributed energy generation in urban settings

Jing,

Zhang,

et al. 2024

Sustainable Cities and Society

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A data-driven clustering approach for assessing spatiotemporal vulnerability to urban emergencies

Bittencourt,

Costa,

Portugal

et al. 2024

Sustainable Cities and Society

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Modeling and Analyzing Urban Sensor Network Connectivity Based on Open Data

Musznicki,

Piechowiak,

Zwierzykowski

2023

Sensors

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The optimization of network topology is crucial to achieve efficient data transmission in wireless sensor networks. Recently it has been proven that emerging open data sources can be used for modeling the structures of heterogeneous urban sensor networks. With this, leveraging real location data of various networked and sensing devices became feasible and essential. This approach enables the construction and analysis of more accurate representations based on frequently updated actual network infrastructure topology data, as opposed to using synthetic models or test environments. The presented modeling method serves as the basis for the designed architecture and implemented research environment. This paper introduces a set of algorithms which transform devices’ location data into graph-based wireless network connectivity models. Each algorithm is thoroughly discussed and evaluated. Moreover, static (momentary) and dynamic (time-spanning) network topologies are constructed in four large Polish cities based on publicly available data. Multidimensional simulation-based analysis is conducted to investigate the characteristics of the modeled structures. Directions for further research are suggested as well.

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Exploiting geospatial data of connectivity and urban infrastructure for efficient positioning of emergency detection units in smart cities

Cited by 4 publications

References 50 publications

A cost-benefit secured DAG based analysis of distributed energy generation in urban settings

A cost-benefit secured DAG based analysis of distributed energy generation in urban settings

A data-driven clustering approach for assessing spatiotemporal vulnerability to urban emergencies

Modeling and Analyzing Urban Sensor Network Connectivity Based on Open Data

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