Qualcomm introducing Drive Data platform for sensor fusion
04 January 2017
Qualcomm is introducing the Qualcomm Drive Data Platform to collect and analyze intelligently information from a vehicle’s sensors. Cars will be able to determine their location up to lane-level accuracy, to monitor and to learn driving patterns, to perceive their surroundings, and to share this reliable and accurate data with the rest of the world.
These capabilities will be key for many connected car applications, from shared mobility and fleet management to 3D high-definition mapping and automated driving. Qualcomm Drive Data platform is built on three pillars: heterogeneous connectivity; precise positioning; and on-device machine learning, all integrated into the Qualcomm Snapdragon solution.
The platform uses a Qualcomm Snapdragon 820Am automotive processor. With an optional integrated X12 LTE modem capable of up to Cat 12 speeds, the Snapdragon 820Am is designed to deliver the next level of intelligence and mobile connectivity (e.g., 802.11p, Wi-Fi and Bluetooth LE).
It is designed to fuse data from the vehicle’s camera feed with inertial sensors and navigation data, optimized for precise positioning up to lane-level accuracy even in challenging environments such as urban canyons.
Additionally, Qualcomm Technologies is offering a deep-learning software development kit (SDK). The SDK, called the Qualcomm Snapdragon Neural Processing Engine (SNPE), is engineered to use the Snapdragon processor’s heterogeneous compute capabilities to provide auto makers a powerful, energy-efficient platform for delivering the next level of automotive intelligence.
More technical details on the Qualcomm Drive Data Platform will be forthcoming. At CES 2017, Qualcomm is demonstrating map crowdsourcing and critical safety alert use cases, as well as the Qualcomm Drive Data platform with Nauto partnership for fleet-based use cases.
How does the 820A compare to NVIDIA’s PX2 with 24 trillion deep learning operations per second?
Posted by: Account Deleted | 04 January 2017 at 03:29 AM