Frequently asked questions
Intenseye is an AI platform capable of connecting existing cameras in manufacturing facilities to prevent accidents. Our deep learning-powered AI models can predict and analyze body posture, ergonomics, danger zone violations, personal protective equipment usage in real-time. Based on our instant notification system facilities can stop violations before they turn into accidents.
Camera feed is processed and deleted on the fly and never stored. Our system never identifies people, nor stores identities. All the output is anonymized and aggregated and reported by our dashboard and API as visual or tabular data. We don’t rely on facial recognition, instead taking in visual cues from all features across the body. Intenseye is fully compliant with GDPR and US State laws.
Security is always our top priority. We manage our security in multiple ways.
The data fed into Intenseye from cameras are secured by TLS protocol between client and server. The frames from cameras are never physically stored on hardware. They are stored in memory which is closed to outside access and they are deleted shortly after sending it. (Happens every in 0.1 - 0.2 ms ).
To encrypt the communication internally and externally, we use the most secure encryption algorithms. Each service has it’s own identity and it’s own access rights. A service can whitelist the services which can connect to itself and validate using the central authentication mechanism.
Intenseye servers use hash based algorithm to determine if the correct version of the operating system and images are used inside the machine.
Services inside Intenseye infrastructure uses HTTP or RPC protocols to communicate with each other. Since the internal connection is encrypted, if someone is able to get inside the network, they will not be able to decode the message.
We have various endpoints for you to integrate your software or hardware into our real-time notification system.
You can check out our API documentation from here! And make sure to let us know about your clever use cases.
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