TY - GEN
T1 - Crowdsourcing and IoT Towards More Resilient Flooding Prone Cities
AU - Escamilla-Ambrosio, Ponciano J.
AU - Pulido-Navarro, Maria G.
AU - Hernández-Gutiérrez, Isabel V.
AU - Rodríguez-Mota, Abraham
AU - Moreno-Ibarra, Marco A.
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Crowdsourcing is a phenomenon where groups of persons sometimes from different backgrounds participate to accomplish a task by making use of technology. Internet of Things (IoT) is able to incorporate a large number of heterogeneous devices such as sensors, surveillance cameras, smartphones, home appliances, etc., all data generated by these devices is processed and analysed to incorporate applications that will make life easier for the end users. This article proposes that community members of a specific urban zone, prone to flooding, collaborate in sharing information about weather conditions using IoT techniques. The gathered information is sent to a cloudlet to be analysed together with information from weather forecast and a network of sensors and surveillance cameras installed in specific areas inside and surrounding the studied zone. Having members of the very community studied involved in the process will exploit the available IoT technologies and the use of crowdsourcing at a lower cost leading to the development of what is called Smart City. This paper revises the available technology and proposes a system that will help in collecting and evaluating information for prediction purposes as to whether the community involved is at risk of being flooded. It is being noted that this risk is getting higher every year due to overpopulation, bad urbanisation, and climate change. Results show that the use of this technology will improve weather forecast so the community could react in time in case of flooding threats.
AB - Crowdsourcing is a phenomenon where groups of persons sometimes from different backgrounds participate to accomplish a task by making use of technology. Internet of Things (IoT) is able to incorporate a large number of heterogeneous devices such as sensors, surveillance cameras, smartphones, home appliances, etc., all data generated by these devices is processed and analysed to incorporate applications that will make life easier for the end users. This article proposes that community members of a specific urban zone, prone to flooding, collaborate in sharing information about weather conditions using IoT techniques. The gathered information is sent to a cloudlet to be analysed together with information from weather forecast and a network of sensors and surveillance cameras installed in specific areas inside and surrounding the studied zone. Having members of the very community studied involved in the process will exploit the available IoT technologies and the use of crowdsourcing at a lower cost leading to the development of what is called Smart City. This paper revises the available technology and proposes a system that will help in collecting and evaluating information for prediction purposes as to whether the community involved is at risk of being flooded. It is being noted that this risk is getting higher every year due to overpopulation, bad urbanisation, and climate change. Results show that the use of this technology will improve weather forecast so the community could react in time in case of flooding threats.
KW - Crowdsourcing
KW - Flooding risk
KW - Internet of things
KW - Resiliency
KW - Smart cities
UR - http://www.scopus.com/inward/record.url?scp=85102616333&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-69136-3_10
DO - 10.1007/978-3-030-69136-3_10
M3 - Contribución a la conferencia
AN - SCOPUS:85102616333
SN - 9783030691356
T3 - Communications in Computer and Information Science
SP - 139
EP - 153
BT - Third Ibero-American Congress, ICSC-Cities 2020, 2020, Revised Selected Papers
A2 - Nesmachnow, Sergio
A2 - Hernández Callejo, Luis
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd Ibero-American Congress, ICSC-CITIES 2020
Y2 - 9 November 2020 through 11 November 2020
ER -