Read our Case Study with about leveraging technologies in a power constraint environment using the Movidius VPU.
viso.ai software leverages the latest hardware and software technology from Intel to meet these diverse and challenging requirements. The use case runs on Intel® Core™ i3 processors, combined with the Intel® Movidius™ Myriad™ X VPU for Deep Learning inference, in a robust and industrial housing.
Additionally, the Deep Learning models are optimized using the Intel® Distribution of OpenVINOTM Toolkit , a software kit that helps developers and data scientists speed up computer vision workloads, streamline deep learning inference and deployments, and enable execution across a range of Intel® hardware.
The computer is mounted inside of the delivery vans. The Movidius Myriad X VPU provides enough power to perform object detection on three input camera streams in real time at low electrical power consumption. The output is used to warn the driver about potential obstacles, while the Intel Core i3 processor performs geometrical transformation tasks to display the live video streams to the driver inside of the delivery van.
Use of the latest, optimized Intel® AI technologies has resulted in significant damage-related cost reduction, according to initial KPI assessments after the first month of system usage. Further features are now planned to be integrated into the same system, in order to scale the benefits observed even more.
According to Arkadiusz Hruszowiec, Intel Business Development Manager for the region, “this project is a proof-point that our strategy of enabling AI on edge devices works in practice. By using the Intel® Distribution of OpenVINO™ toolkit and Intel® Vision Accelerator Solutions, viso.ai is able to take video streams, analyze them in a deep-learning model and draw insights in real time at the edge, which result in real business impact for the end customer.”
Read the full case study here.