powered by Nvidia®
for object detection
combination of objects in real-time
Configure model detection parameters and start detection in real-time
Runs on our AI edge device, the IIoT AI Controller
Train any type of object or combination of objects for object detection in the cloud and apply inference in real-time on the edge.
Parallel streams /
any IP CAM
Up to 8 camera streams can be served in combination with our IIoT AI Controller
It dynamically detects the classes required for object detection and enables you to decide which classes you actually want to detect objects for.
Configure focus areas for object detection, confidence thresholds etc.
Which classes you want the model to detect is defined by how it is trained in the cloud. The final model definition is served to IIoT CAM by our Smart IIoT Controller's OTA service
real-time Object Detection
- Training is done in the cloud through AWS DL AMI and results are tracked in the cloud
- Generated model weights are automatically stored
- Model weights can be applied to the object detection micro-service configuration
- The OTA service or our Smart IIoT Controller deploys the weights to the model service
- The model service runs the inferencing
Training is done by using labelled images (supervised learning) and is done in the cloud on AWS DL AMI.
Results are tracked and based on the results model weights are selected and applied to the model service configuration.
Our Smart IIoT Controller's OTA service will make sure that the correct weights are used for the model service on the edge.
Change detection regions and line crossing areas for each camera stream.
Change the actual IoU and Confidence thresholds and the actual object classes to detect.
Start detection and track detected objects with live camera streams and/or measurements in the cloud.
IIoT AI CAM can be used to combine with other sensor measurements.
Potential applications are: detection of amount of people in a room or particular area, control of safety gear of people (e.g. helmet, vest), etc.