By mimicking human processes and behaviors, our intelligent computing systems augment human capabilities, both as standalone systems and as a layer of embedded processing in sensing technologies. This enables automation of complex processes or prediction of future states. Combining intelligent computing with our expertise in sensor data, we produce complete systems that both gather and interpret human physiologic and non-physiologic data.

Although intelligent computing underlies almost every project at Archinoetics, please read below or use the links to the left to learn more about a few projects in which it is a primary component.

Unmanned Surveillance

As technology and surveillance demands grow, the increasing amounts of data are quickly exceeding the capacity of intelligence analysts. Archinoetics created an automated system that mimics a human’s ability to discard common occurrences while identifying anomalies, including distinguishing movement of interest from environmental motion. The system learns normal patterns of behavior to predict the next temporal action.

Neurobiologically Inspired Computing
Building off of our expertise in neurophysiology and intelligent computing, Archinoetics created a learning architecture that merges brain dynamics-based learning with the concepts of evolutionary and experiential models. The resulting computing platform encompasses sensor, communications, and affector infrastructure, enabling collaborative autonomous learning that can be applied to robotics, UAVs, and UUVs.

Automated FPGA Design

The Field-Programmable Automation System (F-PAS) is an intelligent system that streamlines the FPGA design process into a single interface while enabling even a single engineer to create the best design solution for the desired application using commercially-available CAD tools.

Self-Aware Computing

Self-aware computing systems dynamically adapt while monitoring system health and metrics to optimize the performance of the system for a specified goal. Archinoetics is developing self-aware systems to be used as a controller for applications such as sensor networks or even optimized personal computing.