TY - JOUR
T1 - From sensing to action
T2 - Quick and reliable access to information in cities vulnerable to heavy rain
AU - Gaitan, Santiago
AU - Calderoni, Luca
AU - Palmieri, Paolo
AU - Veldhuis, Marie Claire Ten
AU - Maio, Dario
AU - Van Riemsdijk, M. Birna
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/1
Y1 - 2014/12/1
N2 - Cities need to constantly monitor weather to anticipate heavy storm events and reduce the impact of floods. Information describing precipitation and ground conditions at high spatio-temporal resolution is essential for taking timely action and preventing damages. Traditionally, rain gauges and weather radars are used to monitor rain events, but these sources provide low spatial resolutions and are subject to inaccuracy. Therefore, information needs to be complemented with data from other sources: from citizens' phone calls to the authorities, to relevant online media posts, which have the potential of providing timely and valuable information on weather conditions in the city. This information is often scattered through different, static, and not-publicly available databases. This makes it impossible to use it in an aggregate, standard way, and therefore hampers efficiency of emergency response. In this paper, we describe information sources relating to a heavy rain event in Rotterdam on October 12-14, 2013. Rotterdam weather monitoring infrastructure is composed of a number of rain gauges installed at different locations in the city, as well as a weather radar network. This sensing network is currently scarcely integrated and logged data are not easily accessible during an emergency. Therefore, we propose a reliable, efficient, and low-cost ICT infrastructure that takes information from all relevant sources, including sensors as well as social and user contributed information and integrates them into a unique, cloud-based interface. The proposed infrastructure will improve efficiency in emergency responses to extreme weather events and, ultimately, guarantee more safety to the urban population.
AB - Cities need to constantly monitor weather to anticipate heavy storm events and reduce the impact of floods. Information describing precipitation and ground conditions at high spatio-temporal resolution is essential for taking timely action and preventing damages. Traditionally, rain gauges and weather radars are used to monitor rain events, but these sources provide low spatial resolutions and are subject to inaccuracy. Therefore, information needs to be complemented with data from other sources: from citizens' phone calls to the authorities, to relevant online media posts, which have the potential of providing timely and valuable information on weather conditions in the city. This information is often scattered through different, static, and not-publicly available databases. This makes it impossible to use it in an aggregate, standard way, and therefore hampers efficiency of emergency response. In this paper, we describe information sources relating to a heavy rain event in Rotterdam on October 12-14, 2013. Rotterdam weather monitoring infrastructure is composed of a number of rain gauges installed at different locations in the city, as well as a weather radar network. This sensing network is currently scarcely integrated and logged data are not easily accessible during an emergency. Therefore, we propose a reliable, efficient, and low-cost ICT infrastructure that takes information from all relevant sources, including sensors as well as social and user contributed information and integrates them into a unique, cloud-based interface. The proposed infrastructure will improve efficiency in emergency responses to extreme weather events and, ultimately, guarantee more safety to the urban population.
KW - heavy rain.
KW - Smart city
KW - urban ICT infrastructures
KW - weather sensing
UR - https://www.scopus.com/pages/publications/84908425499
U2 - 10.1109/JSEN.2014.2354980
DO - 10.1109/JSEN.2014.2354980
M3 - Article
AN - SCOPUS:84908425499
SN - 1530-437X
VL - 14
SP - 4175
EP - 4184
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 12
M1 - 6892929
ER -