Chiral Software’s ZombieCam system has been selected for participation in the upcoming JIFX experiments. The team is looking forward to testing the technology and discovering creative ways of interfacing with other fresh-out-of-the-lab technology. As always the goal is to use our creativity and innovation to defend the United States and keep us ahead of our adversaries. ZombieCam is not just a camera, it is a platform for sensing and interacting with the environment.
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USDA Forest Service selects Chiral Software to develop embedded machine learning system
USDA Forest Service – Savannah River Research Team has selected Chiral Software to develop CoyoteCam, an embedded machine learning system which performs wildlife management tasks. This system, developed under earlier research contracts with USDA Forest Service, will now be deployed to “secure” an area of approximately one square mile to prevent entry of coyotes, while allowing all other animals to enter freely.
The coyote is the apex predator in the ecosystem at the Savannah River location. By excluding just this animal, but letting others enter freely, the Forest Service researchers will observe what happens to an ecosystem without its apex predator. Use of an embedded, autonomous, solar powered machine learning vision system is the only way this could be achieved without causing harm to animals or the ecosystem. The NVidia module is connected to Chiral developed electronics which allow it to control an electric curtain, which is the same as an electric fence but allows animals to pass through easily when it is not active.
CoyoteCam uses Ethernet cameras and NVidia embedded systems, with customized software and training sets, to achieve this goal. The systems are compact, solar powered, and can run indefinitely. Chiral’s team will deploy to the Savannah River Site (SRS) to deploy a set of these systems.
This same technology will be applied to other challenges in wildlife management and defense.
ZombieCam software receives certification from OTTI
Chiral Software’s ZombieCam remote surveillance software has received a Certificate to Field from the Operational Test and Training Infrastructure (OTTI) Authorizing Official (AO). ZombieCam is now on the OTTI Evaluated / Approved products list and is ready for deployment within the Air Force.
This certification allows ZombieCam to be added to any authorized system environment. Information System Security Managers (ISSMs) can determine the impact of adding ZombieCam and update appropriate ATO documentation. This allows for rapid deployment of ZombieCam into production environments.
Chiral Software’s ZombieCam product awarded Phase II SBIR
After developing the ZombieCam concept in a AFWERX Phase I SBIR, Chiral’s team evaluated the potential of the system and created a plan and goals for a prototype development. The concept of ZombieCam was formulated into a new concept for ground-based situational awareness: the RASP system.
- Remote: a device which is compact, rugged, easy to set up, requires no tools, no special training. It also need to be affordable and replaceable, because remote devices are subject to theft and damage
- Autonomous: capable of operating without a power supply, wired network, or hands-on maintenance. Autonomy at scale also requires detailed device health monitoring so maintenance can be scheduled before a device completely fails
- Sensor: the primary purpose is to sense the environment, by capturing images
- Platform: new capabilities and modalities of both sensing and responding can be added in future to meet future mission requirements. The system has enough on-board compute resources and power to support new missions and new technologies
The RASP concept is connected with the existing deployed ZombieCam cloud based software and patented AI to provide security from ground threats in remote locations. No other system today is designed to meet this need.
Chiral Software’s Direct to Phase II SBIR proposal was awarded today.
Chiral Software begins research in embedded machine learning for USDA Forest Service
Chiral Software was awarded a contract today to continue development of the CoyoteCam embedded system for machine learning based wildlife management. The goal is to automatically select animals using images, to control an electric fence which will selectively exclude a target species. The CoyoteCam system uses NVidia modules, with battery and solar power, for deployment at the Forest Service research station at the Department of Energy Savannah River Site.
This is an exciting use of machine learning and may have applications to many tasks for surveillance, security, and wildlife management, and continues Chiral’s earlier research work.
Chiral Software receives AFWERX Phase I SBIR to explore anomaly detection for ground threat detection
Chiral Software, in its DARPA research contract over the past two years, has deployed practical target detection systems which function in real time, on battery power. We considered possible security applications and realized, if we had an anomaly detection algorithm, and inexpensive sensors we could deploy in remote areas, we would be able to provide a new security solution and concept which currently doesn’t exist. We refined this concept and proposed a feasibility study and evaluation.
Today we received an award of a Phase I SBIR from AFWERX to explore the ZombieCam concept. We will implement the algorithm and deploy with available off the shelf sensor options and gather information from potential users.
We are excited about the support from AFWERX in this development.