Autores
Escamilla Ambrosio Ponciano Jorge
Rodríguez Mota Abraham
Moreno Ibarra Marco Antonio
Título Crowdsourcing and IoT Towards More Resilient Flooding Prone Cities
Tipo Congreso
Sub-tipo Memoria
Descripción 3rd Ibero-American Congress, ICSC-CITIES 2020
Resumen 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. © 2021, Springer Nature Switzerland AG.
Observaciones DOI 10.1007/978-3-030-69136-3_10 Communications in Computer and Information Science, v, 1359
Lugar Virtual, online
País Indefinido
No. de páginas 139-153
Vol. / Cap.
Inicio 2020-11-09
Fin 2020-11-11
ISBN/ISSN 9783030691356