Libelium's IoT technology allows you to know the interior of the Boca del Infierno volcano
The aim of the project has been to build a digital early detection system to predict volcanic eruptions. With the information obtained with the Waspmote sensors, a family of 'digital twins' will be built that digitally simulates what is happening inside the crater and be able 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 time everything that happens inside and outside the craters, and predict eruptions. The company that combines innovative scientific expeditions with technology projects to drive positive change, Qwake, has relied on the technology of Libelium to develop a wireless sensor network in hellmouth, name by which the Masaya volcano of Nicaragua is known.
Masaya is one of the most active Latin American volcanoes. In fact, during the last quarter of 2008 its boiler spewed ash and steam reaching a height of 2,1 Kilometers. At this time, one of its craters has a lava lake inside. 600 square meters that allows to visualize the dynamic behavior of the magma where waterfall effects are appreciated, lava explosions and eruptions.
The Qwake Team, headed by explorer and documentary filmmaker Sam Cossman, the Government of Nicaragua, Libelium and General Electric (GE) have worked on this project to launch the first online volcano. The expedition took place in the months of July and August of 2016.
Qwake needed to implement a wireless monitoring system capable of collecting, transmit and store data in real time. For this reason, chose Libelium technology to obtain information directly from the crater.
To be able to safely access the Santiago Crater, where the open-air lava lake is located, Sam Cossman and his expedition developed a zip line system that would allow both the expedition's own equipment and the material to descend efficiently.. This made it possible to install the Waspmote sensor platforms near the crater to obtain data in an environment as extreme as it is difficult and almost inaccessible..
The sensor platforms implemented at the Masaya Volcano were Waspmote Plug & Sense! Smart Environment PRO and Waspmote Plug&Sense! Ambient Control that acted as repeaters of the signal sent by the first. More than 80 of sensors to measure CO2, H2S, temperature, humidity and atmospheric pressure.
The encapsulated sensor platforms were vacuum-sealed to protect them against heat inside the crater and also in areas near the volcano.. The temperature where they placed most of the sensors was around 150 Degrees Farenheit (approximately 65 degrees Celsius), although in some parts of the volcano they were reached between 800 and 1.000 Degrees Farenheit (between 426 and 537 degrees Celsius).
Waspmote Plug & Sense! Smart Environment PRO sent the information directly to the Meshlium Gateway and in some cases, when the signal was low, to the Waspmote Plug&Sense! Ambient Control that acted as repeater stations. This data was sent via Xbee 900HP of Digi International. The IoT Gateway collected the data and sent information by 3G to the GE database where it was then visualized in Predix, a GE Cloud platform developed for the Industrial Internet.
Early detection of rashes
The main objective of the project has been to build a digital early detection system to predict volcanic eruptions. This information will be used by researchers and scientists to build a family of "digital twins" that digitally simulates what is happening inside the crater..
The ultimate goal of this project is to offer a public service giving access to the population and decision-makers to allow them to experiment with an active volcano in real time..
Predictive analytics tools based on the cloud platform use a combination of the data collected after more than 20 years of field work on the Masaya Volcano and the information obtained by sensors connected to the Waspmote Plug Sensor Platforms & Sense! that were installed in this project. All this data will help anticipate volcanic crises and act in a pioneering way as an Early Warning System. After this first project, the expedition believes that there is great potential to develop other applications in volcanoes around the world..
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• section: Case studies, control, Signal distribution, networks, simulation