Author(s): Adrian Pedrozo-Acuna; Jorge A. Magos-Hernandez; Juan A. Sanchez-Peralta; Alejandra Amaro-Loza; Agustin Brena-Naranjo
Linked Author(s): Adrián Pedrozo Acuña
Keywords: Smart monitoring; Precipitation; Disdrometers; Sensor network; Urban hydrology; WSN
Abstract: This paper presents a real-time system for issuing warnings of intense precipitation events during major storms, developed for Mexico City, Mexico. The system is based on high-temporal resolution (Δt=1min) measurements of precipitation in 6 different points within the city, which report variables such as intensity, number of raindrops, raindrop size, kinetic energy, fall velocity, etc. Each one of these stations, is comprised of an optical disdrometer (OTT Parsive 2) to measure size and fall velocity of hydrometeors, a solar panel to guarantee an uninterrupted power supply, a wireless broadband access to internet, and a resource constrained device known as Raspberry Pi3 for the processing, storage and sharing of the sensor data over the world wide web. The developed platform follows a component-based system paradigm allowing users to implement custom algorithms and models depending on application requirements. The system is in place since July 2016, and continuous measurements of rainfall in real-time are published over the internet through the webpage www. oh-iiunam. mx. Additionally, the developed platform for the data collection and management interacts with the social network known as Twitter to enable real-time warnings of precipitation events. Key contribution of this paper is the design and implementation of a scalable, easy to use, interoperable platform that facilitates the development of real-time precipitation sensor networks and warnings. The system was used to issue warnings during the wet season of 2016 in Mexico City, producing timely information to key decision makers in charge of the operation of key drainage infrastructure. The system is easy to implement and could be used as a prototype for systems in other regions of the world.
Year: 2017