DHS Awards ENSCO $2.9 Million Contract for Biological Hazard Detection

ENSCO Inc is celebrating its 50th anniversary with a SenseNet contract award and a new partnership to develop national security solutions.

The Department of Homeland Security (DHS) Science and Technology Directorate (S&T) announced a new 18-month, $2.9 million contract award to ENSCO, Inc. on April 12. The contract covers continued work on SenseNet, an effort to develop a low-cost integrated sensor system that can detect biological health hazards in buildings and other high-occupancy indoor facilities.

DHS initiated the SenseNet program to improve biological detection system performance by further integrating and fusing multiple sensor types, and developed strategies to share the cost burden of a system through commercial utility and application.

“Biological and environmental health hazards can pose a high threat to our nation. S&T is working to develop an innovative solution to this evolving problem using sensors that not only quickly and accurately detect possible hazards, but also distinguish between naturally occurring events and those that may be threats,” said William N. Bryan, Senior Official Performing the Duties of the Under Secretary for Science and Technology.

During prior phases of the program, ENSCO designed, developed, and successfully demonstrated a prototype system that could be adapted for a variety of building layouts. This current effort will build an architecture that integrates multiple sensor types that are potentially highly distributed and will generate data that can be collected and analyzed in the cloud for rapid situational awareness and response.

With this new award, ENSCO will continue to develop, integrate, test, and demonstrate a tiered aerosol detection system that combines low-cost and rapid dedicated environmental monitoring sensors with newly emerging commercial sensors being used by citizens and facility owners for air quality, pollution tracking, and building efficiency purposes.

ENSCO also recently announced it has partnered with DeepSig Inc. as the launch customer for DeepSig’s OmniSIG™ SDK, a real-time signal processing product that enables users to train their own deep learning-based signal detection and classification sensors. By employing deep learning artificial intelligence, OmniSIG can detect WiFi, Bluetooth, 3/4/5G, and other signals up to 1,000 times faster than existing technology.

ENSCO is training the OmniSIG sensor to detect and classify wireless and radar signals of high interest for customers in the Department of Defense and U.S. Intelligence Community.

The OmniSIG sensor not only detects and classifies signals, but also understands the spectrum environment to inform contextual analysis and decision making.

Kylie Bielby has 20 years' experience in reporting and editing a wide range of security topics, covering geopolitical and policy analysis to international and country-specific trends and events. She is an editor and contributor for Jane's by IHS Markit, a columnist for security and counter-terror publications, and a former managing editor for Homeland Security Today.

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