AI

Deep Analytics Opens EOD Data Hub for Beta Testing

Deep Analytics

Deep Analytics LLC, a leading developer of artificial intelligence (AI) solutions for the DoD, has completed initial development of an Explosive Ordnance Disposal (EOD) image data hub where experts can share photographs and details of improvised explosive devices (IEDs). The EOD Data Hub is now open for beta testing by military ordnance disposal personnel and public safety bomb technicians.

“Development of the EOD Data Hub is a major step towards enabling ordnance disposal professionals to share knowledge so they can perform their difficult jobs more safely and effectively,” said Greg Hewitt, Deep Analytics Co-Founder. “We invite credentialed professionals from military EOD teams and police bomb squads to test the Data Hub and provide us with feedback.”

The EOD Data Hub beta site may be accessed at https://eoddatahub.com/. To create an account for beta testing, personnel must upload an EOD school graduation certificate.

Deep Analytics developed the Data Hub and community under contract to the DoD Irregular Warfare Technical Support Directorate (IWTSD) in Washington D.C. The site will be the focal point of an online community where EOD personnel educate themselves and engage with each other on the many types of explosive hazards they encounter.

The Data Hub beta site guides users through the process of uploading photographs of IEDs as they were found in the field. Next, users are asked to identify visible components, such as power sources, detonators, and wire bundles. The beta testers will be encouraged to suggest how the site may be improved with new features or made more user-friendly.

“The Data Hub will grow into a massive photographic archive of IED designs searchable by component,” said Hewitt. “The online community will also participate in competitions that will sharpen their ordnance identification skills.”

In addition, IWTSD will leverage the Data Hub as an unclassified database of labeled IED photographs to develop Machine Learning (ML) object detection algorithms. These automated algorithms will be applied to video feeds streaming from stationary or mobile cameras, including drones, to find bombs hidden along the routes of convoys or at crowded public events before they harm members of the military or the general public.

For more such updates and perspectives around Digital Innovation, IoT, Data Infrastructure, AI & Cybersecurity, go to AI-Techpark.com.

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