Smart City Gnosys

Smart city article details

Title	Exploiting Geospatial Data Of Connectivity And Urban Infrastructure For Efficient Positioning Of Emergency Detection Units In Smart Cities
ID_Doc	25400
Authors	Peixoto J.P.J.; Bittencourt J.C.N.; Jesus T.C.; Costa D.G.; Portugal P.; Vasques F.
Year	2024
Published	Computers, Environment and Urban Systems, 107
DOI	http://dx.doi.org/10.1016/j.compenvurbsys.2023.102054
Abstract	The detection of critical situations through the adoption of multi-sensor Emergency Detection Units (EDUs) can significantly reduce the time between the initial stages of urban emergencies and the actual responses to relieve its negative effects, usually through the rescuing of endangered people, the attending to eventual victims, and the mitigating of its causes. However, although the benefits of such units are well known, their proper positioning in a city is challenging when considering a limited set of available units. In this sense, data-driven approaches can be leveraged to provide a better perception of the urban environments under consideration, allowing emergency management systems to be tailored to the specificities of a target city, thus improving the positioning of EDUs. This article proposes the processing of geospatial data of emergency-related urban infrastructure to support the computing of risk zones in a city, which is retrieved from the OpenStreetMap database together with the map of streets within a defined area. Since risk zones indirectly indicate the proportional number of detection units to be deployed, for each configuration setting of the EDUs, we propose an algorithm that computes the positions for such units only on streets, in a balanced way. Furthermore, considering that EDUs are expected to report detected emergencies through a wireless connection, we have also modelled the coverage area of existing networks in a city, which is also processed according to a suitable dataset. The proposed algorithm performs a fine-grained positioning of EDUs based on the number of active networks, flexibly favouring the EDUs' connectivity requirements such as reliability, throughput, latency, and transmission costs according to the actual demands of any urban emergency management system. Experimental results with real data demonstrated the applicability of the proposed mathematical model and the associated algorithm, reinforcing its practical application for the planning and construction of smart cities. © 2023 The Authors
Author Keywords	Barcelona; Emergency detection; Geospatial data processing; Sensors deployment; Urban computing; Wireless networking

Similar Articles

Id	Similarity	Authors	Title	Published
39902	0.925	Peixoto J.P.J.; Costa D.G.; Franca Rocha W.D.J.S.D.; Portugal P.; Vasques F.	On The Positioning Of Emergencies Detection Units Based On Geospatial Data Of Urban Response Centres	Sustainable Cities and Society, 97 (2023)
24010	0.92	Peixoto J.P.J.; Costa D.G.; De J. S. Da Franca Rocha W.; Portugal P.; Vasques F.	Enhancing The Computation Of Risk Zones Based On Emergency-Related Infrastructure In Smart Cities	Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023 (2023)
40901	0.893	Peixoto J.P.J.; Costa D.G.; De J. S. Da Franca Rocha W.; Portugal P.; Vasques F.	Optimizing The Deployment Of Multi-Sensors Emergencies Detection Units Based On The Presence Of Response Centers In Smart Cities	ISC2 2022 - 8th IEEE International Smart Cities Conference (2022)
14250	0.875	Peixoto J.P.J.; Costa D.G.; Franca Rocha W.D.J.S.D.; Portugal P.; Vasques F.	Cityzones: A Geospatial Multi-Tier Software Tool To Compute Urban Risk Zones	SoftwareX, 23 (2023)
5551	0.863	Sebillo M.; Vitiello G.; Grimaldi M.; Chiara D.D.	A Territorial Intelligence-Based Approach For Smart Emergency Planning	Data Science and Big Data Analytics in Smart Environments (2021)
21397	0.86	Bittencourt J.C.N.; Costa D.G.; Portugal P.; Vasques F.	Dynamic Sensor Configuration For Multi-Target Emergency Detection In Smart Cities	Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023 (2023)
59939	0.857	Coelho G.A.A.; Jesus T.C.; Costa D.G.	Urban Emergency Detection System Using Hierarchical, Collaborative And Configurable Wireless Sensor Networks	Brazilian Symposium on Computing System Engineering, SBESC (2023)
39930	0.857	Bittencourt J.C.N.; Costa D.G.; Portugal P.; Peixoto M.L.M.; Vasques F.	On The Spatiotemporal Knowledge-Driven Vulnerability Assessment Of Urban Areas: A Clustering-Based Approach	International Journal of Disaster Risk Reduction, 127 (2025)
1245	0.854	Bittencourt J.C.N.; Costa D.G.; Portugal P.; Vasques F.	A Data-Driven Clustering Approach For Assessing Spatiotemporal Vulnerability To Urban Emergencies	Sustainable Cities and Society, 108 (2024)