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Qualcomm released its next-generation AI-powered camera design platform using its latest purpose-built systems on a chip (SoCs) to better enable on-device machine learning and processing capabilities.
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The platforms are designed for edge computing use cases that need support for video processing and analytics. The SoCs can be applied to an array of devices including smart security cameras, sports cameras, wearable and body cameras, robotics, inventory management, smart displays, and dash cams.
What it means: Qualcomm’s upgraded platform series improves the quality and applicability of its vision intelligence technology and could help popularize the use of computer vision more broadly.
- An onboard processor and AI engine can increase devices’ speeds. By integrating an advanced image signal processor (ISP) into Qualcomm’s AI engine, the platform’s processing times could be improved, as it doesn’t need to communicate as much with a distant server. Bringing processing and analytics onto a camera allows it to process in real time without having to wait for data to be sent between a device and a server.
- Its software can be optimized for a wide array of use cases. The platform includes Android- and Linux-based software platforms as well as advanced camera software development kits (SDKs) to allow users to tweak it for enterprise, industrial, and consumer use. This opens up smart cameras to even more use case-specific applications, such as allowing dash cams to monitor and alert an auto insurance company to accidents or risky behavior.
Bigger picture: Enabling devices to process data locally reduces the burden on networks, which is important as device numbers continue to grow.
Smart cameras will play a big role in smart cities and connected industrial facilities, and increasingly large streams of data will need to be sent over networks as a result. This could result in slower transmissions, which would limit the functionality of connected devices.
But cameras enabled by Qualcomm’s vision intelligence platform will be able to provide processing and analytics support locally, cutting down on the amount of data that must travel through providers’ networks. Relieving networks’ data streaming burdens will be especially important as the number of connected devices grows.
The number of cellular IoT connections globally is projected to exceed 4 billion by 2024, according to Ericsson. IoT equipment providers building on Qualcomm’s platform will be able to provide companies like AT&T or Verizon, who offer smart city and enterprise IoT solutions, technology which can limit demand on their networks.
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