Abstract
Flooding is one of the most frequent and costly natural disasters affecting mankind. However, implementing Internet of Things (IoT) technology to monitor river behavior may help mitigate or prevent future disasters. This article outlines the hardware development of an IoT system (RiverCore) and defines an application scenario in a specific hydrological region of the state of Colima (Mexico), highlighting the characteristics of data acquisition and data processing used. Both fixed position and moving drifter node systems are described along with web-based data acquisition platform developments integrated with IoT techniques to retrieve data through 3G cellular networks. The developed architecture uses the Message Queuing Telemetry Transport (MQTT) protocol, along with encryption and security mechanisms, to send real-time data packages from fixed nodes to a server that stores retrieved data in a non-relational database. From this, data can be accessed and displayed through different customizable queries and graphical representations, allowing future use in flood analysis and prediction systems. All of these features are presented along with graphical evidence of the deployment of the different devices and of several cellular communication and on-site data acquisition tests.
Highlights
Floods are among the most frequent natural disasters, causing significant damage to infrastructure and displacing, injuring or killing large numbers of persons
The RiverCore data-logger we propose in this paper is designed using a 32-bit architecture and allows users to connect to a wide variety of sensors which implement the same communication protocols
RiverCore is designed to use an Message Queuing Telemetry Transport (MQTT) protocol to send data through a SIM cellular communication module which is integrated into its main board
Summary
Floods are among the most frequent natural disasters, causing significant damage to infrastructure and displacing, injuring or killing large numbers of persons. Several studies [1,2,3] have proposed flood warning and prediction systems, implementing Internet of Things (IoT)-based technology to monitor river behaviour before and during flood events to control flood-prone areas, helping mitigate or prevent future disasters. In 2017, Lamichhane and Sharma [1] state that floods take the lives of more people than many other natural disasters, due to their frequent occurrence and rather unpredictable nature. In the U.S, for example, flash floods kill more than 140 persons per year. Sensors 2019, 19, 127 off, adding to fatalities and causing billions of dollars’ worth of damage. Between 1980 and 2015, weather-related events like floods accounted for over $500 billion USD in damage in Europe alone [4]
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