Drive Test Software 3gpp
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The automotive industry is going through an unprecedented transformation. Shared mobility services are changing the definition of car-ownership, cars are becoming carbon-emissions free with EV vehicles, and the race towards automated driving is heating up across the industry. At the same time, the car itself is becoming a sensor hub, generating tons of data (e.g.
Connected car is expected to generate 1.1PB of data per day by 2020). To help the automotive industry in an innovative, and cost-effective, manner, Qualcomm Technologies, Inc. Has created the Qualcomm® drive data platform, which uses cutting-edge technology to intelligently collect and analyze data from different vehicle’s sensors to facilitate smarter vehicles that can determine their location, monitor and learn driving patterns, perceive their surroundings and share this perception with rest of the world reliably and accurately.
These capabilities will be key for many connected car applications, from shared mobility and fleet management to 3D High definition mapping and future automated driving. Precise location is crucial for navigation, 3D high resolution mapping, autonomous driving, and shared mobility services. For example, autonomous vehicles need to precisely locate themselves on an HD map, understand where they are relative to the world, determine their route and safely stay within the confines of the road/lane. This will require innovation in computer vision, sensor processing and location technologies, such as GNSS with Dead Reckoning (DR) and Visual Inertial Odometry (fusing information from cameras and motion sensors). Next generation vehicles need to perceive their surroundings and share this information with rest of the world reliably and accurately. For example, they need to understand their road environment (road signs, lane markers, etc.), and analyze data about driving patterns to improve autonomous driving. Qualcomm’s long-term investments and research in on-device machine learning, sensor fusion and computer vision that are optimized for low power heterogeneous compute platforms will allow the vehicles to become more intelligent in accurately perceiving the world.
The accuracy of perception and machine learning for decision making is critical for different levels of autonomy. Autonomous cars will rely on high fidelity sensor information sharing and 3D mapping to safely navigate their environment. Our leading Gigabit class LTE modems and 5G leadership will enable autonomous cars to download high resolution maps and share other necessary sensor and driving information. Additionally, Vehicle-to-everything (V2X) is becoming a key technology for enabling fully autonomous driving. V2X complements the capabilities of other sensors that are limited by line of sight (e.g. Radar, LiDAR and camera systems) by providing 360-degree non-line-of sight awareness, extending a vehicle’s ability to “see” further down the road – even at blind intersections or in bad weather conditions. Currently, Qualcomm Technologies has 802.11p-based solutions and is pioneering Cellular V2X on the path to 5G.
Horse Handicapping Software Ratings. In this sense, the 3GPP in Release 10 presents a study named Minimization Drive Test (MDT), which aims to. To demonstrate the importance of including the MOS index [10] of a voice call in the 3GPP - MDT project. Less Measurement Software) and VQT (Voice Quality Test) tools were used. These tools use the ITU-T. At that time, the 3GPP implemented some functions for the SON, such as minimization of drive test, energy saving, handover optimization, and load balancing. 8.1.2.2 SON in 3GPP. Finally, there are a few use cases of self-healing standardized in Release 9: self-recovery of NE software Self-Healing in 5G HetNets ◾ 153.
On-device machine learning will play a key role in resolving data from different sensors and providing vehicles with visual perception to understand road environments, from recognizing traffic signs and road conditions to identifying vehicles and pedestrians. To support the automotive ecosystem, Qualcomm Technologies offers a deep learning software development kit (SDK). The SDK, called the Qualcomm® Snapdragon™ Neural Processing Engine (NPE), is optimized to utilize the Snapdragon heterogeneous compute capabilities to provide OEMs a powerful, energy efficient platform for delivering next level of intelligence. As the first commercially announced, automotive-grade processor with an optional integrated X12 LTE modem capable of Cat 12 speeds, the Snapdragon 820 Automotive processor delivers the next level of intelligence and unprecedented mobile connectivity. The NPE and Qualcomm® Symphony SDKs from Qualcomm Technologies, Inc. Are designed to allow our customers to spread the neural networks’ workloads between the heterogeneous computing engines, such as Computer Processing Unit (CPU), Graphical Processing Unit (GPU), and Digital Signal Processor (DSP), within the Snapdragon 820 automotive processor; maximizing the computational performance and power efficiency of our SoC. Site Map ©2017 Qualcomm Technologies, Inc.
And/or its affiliated companies. Nothing in these materials is an offer to sell any of the components or devices referenced herein. Mde Unlocker 1.3 Serial.
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