Sentry - HLU

In a "multi-layer" hierarchical architecture where low-level functionality is needed to control real-time devices to the application layer where complex algorithms  are performed, the High Level Unit (HLU) is the processing unit which is delegated to perform the functionality considered application.

For example, the HLU can be dedicated to detecting and tracking different types of "objects" in the images (interest classes in video frames), including people and dogs.

In a security application, the detected objects are treated differently: the first neglected, the seconds reported as intruders.

Typically, the HLU communicates with a Ground Control Station (GCS), a software application designed to monitor and supervise system activities.

Algorithms are based on two state-of-the-art approaches, namely convolutional neural networks and tracking with  "particle filters".
The convolutional neural networks (CNN) are machine learning algorithms that have been particularly interesting in the scientific world and in the industrial world over the last few years. Their main application uses them as "Object Detection" and "Classification" on images. Tracking based on particle filter, on the other hand, is an algorithm for tracking objects of interest in images based on a probabilistic approach that provides good performance in scalability and tracking performance. 

The  mentioned algorithms require considerable computational capacity to be executed. Usually, you can not run them "online" because processing a single image takes time in the order of seconds. However, the embedded platform used to accelerate the computation of machine learning algorithms to enable it to be "online".

The platform is made up of highly performing HW chipsets, including 256 CUDA cores, Quad ARM® V8A architecture,
Encode (HEVC) and 
Decode (12-Bit), 8 GB LPDDR4 memory, 32 GB eMMC, Camera Serial Interface up to 6 Rooms, CAN, USB, Ethernet, WiFi, Bluetooth.

The GPU consists of 256 CUDA cores, allowing parallel execution of a large number of processes, ensuring a considerable speedup while processing the images. Along with the computational capacity of the quad core ARM processor, it is possible to split the computational burden on the different computing units, taking into account the intrinsic characteristics of each processor.

The presence of a HW decoder on the platform guarantees the real-time decoding of the h264 stream produced by the rooms without any aggravation of the ARM CPU.

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