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Arthur Edwards
Faculty of Telematics, University of Colima, 333 University Avenue, Colima C.P. 28045, Mexico

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Journal article
Published: 14 September 2020 in Sensors
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This paper presents a system of sensors used in flash flood prediction that offers critical real-time information used to provide early warnings that can provide the minutes needed for persons to evacuate before imminent events. Flooding is one of the most serious natural disasters humans confront in terms of loss of life and results in long-term effects, which often have severely adverse social consequences. However, flash floods are potentially more dangerous to life because there is often little or no forewarning of the impending disaster. The Emergency Water Information Network (EWIN) offers a solution that integrates an early warning system, notifications, and real-time monitoring of flash flood risks. The platform has been implemented in Colima, Mexico covering the Colima and Villa de Alvarez metropolitan area. This platform consists of eight fixed riverside hydrological monitoring stations, eight meteorological stations, nomadic mobile monitoring stations called “drifters” used in the flow, and a sniffer with data muling capability. The results show that this platform effectively compiles and forwards information to decision-makers, government officials, and the general public, potentially providing valuable minutes for people to evacuate dangerous areas.

ACS Style

José Ibarreche; Raúl Aquino; R. M. Edwards; Víctor Rangel; Ismael Pérez; Miguel Martínez; Esli Castellanos; Elisa Álvarez; Saul Jimenez; Raúl Rentería; Arthur Edwards; Omar Álvarez. Flash Flood Early Warning System in Colima, Mexico. Sensors 2020, 20, 5231 .

AMA Style

José Ibarreche, Raúl Aquino, R. M. Edwards, Víctor Rangel, Ismael Pérez, Miguel Martínez, Esli Castellanos, Elisa Álvarez, Saul Jimenez, Raúl Rentería, Arthur Edwards, Omar Álvarez. Flash Flood Early Warning System in Colima, Mexico. Sensors. 2020; 20 (18):5231.

Chicago/Turabian Style

José Ibarreche; Raúl Aquino; R. M. Edwards; Víctor Rangel; Ismael Pérez; Miguel Martínez; Esli Castellanos; Elisa Álvarez; Saul Jimenez; Raúl Rentería; Arthur Edwards; Omar Álvarez. 2020. "Flash Flood Early Warning System in Colima, Mexico." Sensors 20, no. 18: 5231.

Journal article
Published: 02 January 2019 in Sensors
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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.

ACS Style

Carlos Moreno; Raúl Aquino; José Ibarreche; Ismael Pérez; Esli Castellanos; Elisa Álvarez; Raúl Rentería; Luis Anguiano; Arthur Edwards; Paul Lepper; Robert M. Edwards; Ben Clark. RiverCore: IoT Device for River Water Level Monitoring over Cellular Communications. Sensors 2019, 19, 127 .

AMA Style

Carlos Moreno, Raúl Aquino, José Ibarreche, Ismael Pérez, Esli Castellanos, Elisa Álvarez, Raúl Rentería, Luis Anguiano, Arthur Edwards, Paul Lepper, Robert M. Edwards, Ben Clark. RiverCore: IoT Device for River Water Level Monitoring over Cellular Communications. Sensors. 2019; 19 (1):127.

Chicago/Turabian Style

Carlos Moreno; Raúl Aquino; José Ibarreche; Ismael Pérez; Esli Castellanos; Elisa Álvarez; Raúl Rentería; Luis Anguiano; Arthur Edwards; Paul Lepper; Robert M. Edwards; Ben Clark. 2019. "RiverCore: IoT Device for River Water Level Monitoring over Cellular Communications." Sensors 19, no. 1: 127.

Journal article
Published: 28 April 2016 in Sensors
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This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.

ACS Style

Néstor Cárdenas-Benítez; Raúl Aquino-Santos; Pedro Magaña-Espinoza; José Aguilar-Velazco; Arthur Edwards-Block; Aldo Medina Cass. Traffic Congestion Detection System through Connected Vehicles and Big Data. Sensors 2016, 16, 599 .

AMA Style

Néstor Cárdenas-Benítez, Raúl Aquino-Santos, Pedro Magaña-Espinoza, José Aguilar-Velazco, Arthur Edwards-Block, Aldo Medina Cass. Traffic Congestion Detection System through Connected Vehicles and Big Data. Sensors. 2016; 16 (5):599.

Chicago/Turabian Style

Néstor Cárdenas-Benítez; Raúl Aquino-Santos; Pedro Magaña-Espinoza; José Aguilar-Velazco; Arthur Edwards-Block; Aldo Medina Cass. 2016. "Traffic Congestion Detection System through Connected Vehicles and Big Data." Sensors 16, no. 5: 599.

Journal article
Published: 29 November 2013 in Sensors
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This paper introduces wireless sensor networks for Ambient Assisted Living as a proof of concept. Our workgroup has developed an arrhythmia detection algorithm that we evaluate in a closed space using a wireless sensor network to relay the information collected to where the information can be registered, monitored and analyzed to support medical decisions by healthcare providers. The prototype we developed is then evaluated using the TelosB platform. The proposed architecture considers very specific restrictions regarding the use of wireless sensor networks in clinical situations. The seamless integration of the system architecture enables both mobile node and network configuration, thus providing the versatile and robust characteristics necessary for real-time applications in medical situations. Likewise, this system architecture efficiently permits the different components of our proposed platform to interact efficiently within the parameters of this study.

ACS Style

Raúl Aquino-Santos; Diego Martinez-Castro; Arthur Edwards-Block; Andrés Felipe Murillo-Piedrahita. Wireless Sensor Networks for Ambient Assisted Living. Sensors 2013, 13, 16384 -16405.

AMA Style

Raúl Aquino-Santos, Diego Martinez-Castro, Arthur Edwards-Block, Andrés Felipe Murillo-Piedrahita. Wireless Sensor Networks for Ambient Assisted Living. Sensors. 2013; 13 (12):16384-16405.

Chicago/Turabian Style

Raúl Aquino-Santos; Diego Martinez-Castro; Arthur Edwards-Block; Andrés Felipe Murillo-Piedrahita. 2013. "Wireless Sensor Networks for Ambient Assisted Living." Sensors 13, no. 12: 16384-16405.

Journal article
Published: 13 June 2012 in Sensors
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Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

ACS Style

Apolinar González; Raúl Aquino; Walter Mata; Alberto Ochoa; Pedro Saldaña; Arthur Edwards. Open-WiSe: A Solar Powered Wireless Sensor Network Platform. Sensors 2012, 12, 8204 -8217.

AMA Style

Apolinar González, Raúl Aquino, Walter Mata, Alberto Ochoa, Pedro Saldaña, Arthur Edwards. Open-WiSe: A Solar Powered Wireless Sensor Network Platform. Sensors. 2012; 12 (6):8204-8217.

Chicago/Turabian Style

Apolinar González; Raúl Aquino; Walter Mata; Alberto Ochoa; Pedro Saldaña; Arthur Edwards. 2012. "Open-WiSe: A Solar Powered Wireless Sensor Network Platform." Sensors 12, no. 6: 8204-8217.