The aim of the project was to build a digital early warning system to predict volcanic eruptions. With the information obtained with the Waspmote sensors are going to build a family of 'digital twins' digitally simulate what is happening inside the crater and to experiment with an active volcano in real time.
Volcanologists bet on the latest technologies offered by the Internet of Things (IoT) to monitor in real everything that happens inside and outside the craters time, and predict eruptions. The company combines innovative scientific expeditions technology projects to drive positive change, Qwake, It has relied on technology Libelium to develop a network of wireless sensors on the Hellmouth, name by which it is known the Masaya volcano in Nicaragua.
Masaya is one of the most active volcanoes in Latin America. In fact, during the last quarter of 2008 its boiler and steam spewed ash to a height of 2.1 kilometers. At the moment, one of its craters has inside a lava lake of 600 square meters to visualize the dynamic behavior of magma where cascading effects, explosions and lava eruptions are seen.
Qwake team, led by explorer and documentary filmmaker Sam Cossman, the Government of Nicaragua, Libelium y General Electric (GIVE) They have worked on this project to launch the first volcano online. The expedition took place in the months of July and August 2016.
Qwake needed to implement a wireless monitoring system capable of collecting, transmitting and storing data in real time. For this reason, they chose Libelium technology to obtain information directly from the crater.
Para poder acceder de manera segura al Cráter Santiago, donde se encuentra el lago de lava a cielo abierto, Sam Cossman y su expedición desarrollaron un sistema de tirolinas que permitiera descender de manera eficiente tanto al propio equipo de la expedición como al material. Esto permitió instalar las plataformas de sensores Waspmote cerca del cráter para obtener datos en un ambiente tan extremo como difícil y casi inaccesible.
The sensor platforms implemented in the Masaya Volcano were Waspmote Plug & Sense! Environment Smart PRO and Waspmote Plug & Sense! Ambient Control acting as repeaters the signal sent by the first. They were connected over 80 sensors to measure CO2, H2S, temperature, humidity and atmospheric pressure.
The encapsulated sensor platforms were vacuum sealed to protect them from the heat inside the crater and also in areas near the volcano. The temperature where most placed sensors was around 150 degrees Fahrenheit (about 65 degrees Celsius), although in some parts of the volcano reached between 800 and 1,000 degrees Fahrenheit (between 426 and 537 degrees Celsius).
Waspmote Plug & Sense! PRO Smart Environment sent the information directly to Meshlium Gateway and in some cases, when the signal was low, the Waspmote Plug & Sense! Ambient Control acting as relay stations. This data is sent through Xbee 900HP of Digi International. Gateway IoT data collected and sent to the 3G information database where GE was then Predix displayed on a Cloud platform developed GE Industrial Internet.
Early detection of eruptions
The main objective of the project was to build a digital early warning system to predict volcanic eruptions. This information will be used by researchers and scientists to build a family of "digital twin" that digitally simulates what is happening inside the crater.
The ultimate goal of this project is to provide a public service giving access to people and those responsible for decision making to allow them to experiment with an active volcano in real time.
Predictive analytical tools based on cloud platform using a combination of data collected after more than 20 years of field work in the Masaya Volcano and the information obtained by the sensors connected to the sensor platforms Waspmote Plug & Sense! who settled in this project. All these data will help anticipate volcanic crisis and act as a pioneering way Early Warning System. After this first project, the expedition believes there is great potential to develop other applications volcanoes around the world.
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• Section: Cases of study, Control, Distribution signals, Networks, Simulation