SPECIAL NOTICE
70 -- Technology Licensing Opportunity for Real-Time Anomalous Activity Detection in Video Surveillance
- Notice Date
- 11/11/2022 9:12:46 AM
- Notice Type
- Special Notice
- NAICS
- 518210
— Data Processing, Hosting, and Related Services
- Contracting Office
- BATTELLE ENERGY ALLIANCE�DOE CNTR Idaho Falls ID 83415 USA
- ZIP Code
- 83415
- Solicitation Number
- BA-1431
- Response Due
- 11/30/2022 8:00:00 AM
- Point of Contact
- Andrew Rankin
- E-Mail Address
-
andrew.rankin@inl.gov
(andrew.rankin@inl.gov)
- Description
- TECHNOLOGY LICENSING OPPORTUNITY Real-Time Anomalous Activity Detection in Video Surveillance A novel video surveillance technology capable of identifying and localizing unprecedented anomalous activity. Opportunity:�� Idaho National Laboratory (INL), managed and operated by Battelle Energy Alliance, LLC (BEA), is offering the opportunity to enter into a license and/or collaborative research agreement to commercialize the anomalous activity detection technology. This technology transfer opportunity is part of a dedicated effort to convert government-funded research into job opportunities, businesses, and, ultimately, an improved way of life for the American people. Overview:������� Video surveillance footage generated globally exceeded 2 Exabytes in 2019 and continues to grow exponentially. It is the most generated media format and the most expensive to process. Artificial intelligence mechanisms have simplified object identification and localization within an image frame with relatively high accuracy. However, the most exciting problem is video surveillance identifying and localizing unprecedented activities for which the model has never been trained to recognize. These anomalous activities are the most interesting for real-time alert generation. Description:��� This invention leverages the single image time series representation (SITSR) technology that INL has previously developed to accomplish real-time anomalous activity detection in video surveillance footage. The technology utilizes hours of unlabeled video surveillance footage considered ""normal"" and contains no unprecedented activities for training the model. Once the model is trained, any unprecedented activity is flagged as anomalous. The anomaly is localized in the video footage image in time and space; all model analysis occurs in real time. Benefits:��� ������ Alternative approaches focus on supervised learning, while this technology uses unsupervised learning. This technology is the only approach capable of detecting anomalous activities. Applications:�� � Identifying and localizing unprecedented activity in video surveillance footage. This capability would benefit any site with the deployment of surveillance cameras, including: Airports, gas stations, university campuses, schools, national laboratories, nuclear reactor facilities, electronic exchanges, police departments, national parks, and home security systems. Development Status:� TRL 3, currently undergoing proof-of-concept work. INL seeks to license the above intellectual property to a company with a demonstrated ability to bring such inventions to the market. Exclusive rights in defined fields of use may be available. Added value is placed on relationships with small businesses, start-up companies, and general entrepreneurship opportunities. Please visit Technology Deployment�s website at https://inl.gov/inl-initiatives/technology-deployment for more information on working with INL and the industrial partnering and technology transfer process. Companies interested in learning more about this licensing opportunity should contact Andrew Rankin at td@inl.gov.
- Web Link
-
SAM.gov Permalink
(https://sam.gov/opp/881bf6d33e534323b9970e1b8680ab0e/view)
- Place of Performance
- Address: Idaho Falls, ID 83415, USA
- Zip Code: 83415
- Country: USA
- Zip Code: 83415
- Record
- SN06515371-F 20221113/221111230053 (samdaily.us)
- Source
-
SAM.gov Link to This Notice
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