Image credit: Photo by Lucas Leonel Suárez on Unsplash
Image credit: Photo by Lucas Leonel Suárez on UnsplashIn this article we propose a Cloud-based platform for the detection and prediction of snow avalanches. The platform is based on data gathering from sensors, data collection in Cloud and using this data as an input for the developed Machine Learning algorithms. We discuss the different phases of the data workflow and present the proposed system’s functionalities. We also analyze the data validation and pre-processing operations necessary before applying the Machine Learning algorithms on the gathered data. We also present the integration of the Machine Learning capabilities with the OpenGate cloud platform.
In the realm of natural disaster prediction and management, the innovative MEWS project stands out as a beacon of technological advancement and practical application. At the heart of this initiative is Amplía Soluciones, under the leadership of our team, which has played a pivotal role in developing the project’s artificial intelligence inference engine.
Our journey began with enhancing the big data capabilities of our IoT platform, OpenGate. This robust platform was intricately designed to ingest and prepare vast amounts of data, paving the way for data scientists from Beia Consult International to perform their analytical magic. The collaboration between our teams was instrumental in harnessing the data effectively for predictive analytics.
A significant milestone in our project was integrating a full-fledged LoRaWAN stack into OpenGate. This integration allowed us to seamlessly receive, normalize, and process the data from remote sensors and gateways. This advancement was not just about technology integration; it was about creating a reliable and efficient pipeline for data to flow from the most remote sensors right into our central analytics system.
The AI inference engine, a brainchild of our team at Amplía Soluciones, stands as the project’s crown jewel. This engine is the core that makes predictions about potential snow avalanches. By analyzing the data fed into it, the engine can identify patterns and indicators that signify a high risk of avalanches, thus enabling timely warnings and potentially saving lives and property.
The integration of OpenGate’s automation rules with our AI inference engine marked a significant leap in our project’s capabilities. These rules allow OpenGate to interact with the inference engine, triggering alarms and mobilizing response mechanisms in the event of a high avalanche risk detection. This automation not only enhances the speed of response but also ensures accuracy and reliability in avalanche prediction.
Our project is more than a technological endeavor; it is a commitment to safety and proactive disaster management. The collaborative efforts between Amplía Soluciones, Beia Consult International, and other stakeholders have culminated in a system that not only predicts snow avalanches but also paves the way for advanced natural disaster management strategies.
As we continue to refine and enhance MEWS, we stand at the forefront of innovation, demonstrating how technology can be a powerful ally in safeguarding communities against the unpredictable forces of nature.