How can software understand the uncertainty in any sensor measurements just based on the data sent to it?

How can software understand the uncertainty in any sensor measurements just based on the data sent to it?

How can software understand the uncertainty in any sensor measurements just based on the data sent to it?

To complement our Signaloid C0 uncertainty tracking compute platform, we provide products that can be integrated into the data acquisition path to automatically analyze the uncertainty in data and to encode it in a form that can be fed to unmodified programs running on Signaloid's compute platform. The Signaloid S0 hardware (https://www.signaloid.ai/hardware) is a small digital integrated circuit design that is small and efficient enough to be integrated even into miniature sensors. The Signaloid D0 () is integrated with the Signaloid Cloud Engine and the Signaloid Cloud Developer Platform and can analyze data from sources such as AWS S3 Buckets, and to pass that processed data in a form that can be fed into unmodified applications running on Signaloid's computing platform.

We provide our customers direct access to running their applications on our computing platform. From our customer's perspective, they think they are running on a custom processor. That processor most customers run on is implemented as a virtualization layer on top of AWS but the virtualization is not only using software (AWS allows us to have part of our implementation in FPGAs deployed in the AWS infrastructure) but at the same time we don't fully depend on that FPGA support.