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OWL, which is the acronym for Organization, Whereabouts, and Logistics, is an IoT and software solution that helps first responders connect with victims during a natural disaster. It is a project that is a two-part hardware/software solution. It provides an offline communication infrastructure that provides first responders a simple interface for managing all aspects of a disaster.
Bryan Knouse, the team lead worked with Magus Pereira, Nicholas Feuer, Charlie Evans, and Taraqur Rahman – to give birth to the prestigious ‘ Project OWL’. They were inspired by the hurricane that hit Puerto Rico, where all communication was down for not weeks but months.
OWL addresses the fundamental issues that arise in the wake of a natural disaster. It deals with critical operations and communications when connectivity fails. According to Magus Pereira, the physical “clusterduck” network is made of hubs resembling rubber ducks, which can float in flooded areas. Just five of them is required to cover a square mile, and they create a network mesh that can communicate using conversational systems like Alexa and Facebook Messenger to a central application. The OWL software incident management system uses predictive analytics and multiple data sources to build a dashboard for first responders.
The developers say that once this network of ducks is deployed and then clustered, civilians can get on the devices through a really intuitive interface and contact responders with a list of things that are immediately required. This information, allows first responders to coordinate resources, learn about the weather patterns and get information on data analytics through the cloud. The solution uses the latest IBM Watson Studio, Watson Cloud APIs, and Weather Company APIs – all that has been built on the IBM Cloud.
Weather data forms a core part of the application, with information on crucial data like the direction of the nearest cyclone or storm and the conditions you can expect the day after a hurricane flooding or the like. Knouse says that better information and analytics can avoid chaos and misinformation that prevails in the time of disaster. It helps in placing resources at places that are required the most. The efficiency can also improve the number of people that can be saved.
The team behind OWL is working on the testing of the project in environments that have been simulated with response teams. They plan to work out on small incidents before using them in full-scale disasters. Their focus is on regions where annual weather patterns consistently impact communities retrogressively.
With advancements in AI, cloud, blockchain, and IoT, disaster management can be deployed in the remotest of places, in ways that were not thought about before.
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