From Lens to Cloud: How to Build a Scalable IoT Camera System
More than 1.5 billion linked cameras are estimated to be in use around the world by 2026, in smart cities, factories, homes, and hospitals. This will drive an industry that
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Inside the Minds of Experts: Tech Trends & Business Evolution
More than 1.5 billion linked cameras are estimated to be in use around the world by 2026, in smart cities, factories, homes, and hospitals. This will drive an industry that
In a world where the Internet of Things (IoT) is forecasted to network more than 29 billion devices by 2030 (Statista), voice-activated smart devices have become essential resources for everything
Today’s changing world of embedded systems requires scalability to be a core feature. It is anticipated that the global digital signal processor market will increase from close to USD 110
According to IEEE/McKinsey, poor engineering or design choices account for up to 70% of digital product failures. However, businesses that work with knowledgeable Product Engineering Services report a 40% faster
Now that technology is evolving so rapidly, embedded vision systems are increasingly used in automotive safety, automation of industry, consumer electronics, and healthcare. From a
In embedded systems, camera product design faces unique challenges that can undermine image quality and system performance. Issues like chromatic aberration, autofocus failures, and image stitching latency are critical in applications such as drones, medical imaging, and multi-camera VR. Camera design engineering demands precise hardware tuning, custom firmware, and optimized software to overcome these hurdles. Using Yocto-based BSPs, engineers can integrate tailored drivers and algorithms for robust solutions. This blog details five camera-specific problems in camera design and their technical fixes, spotlighting image stitching. Chromatic Aberration in Lens Systems Chromatic aberration in camera design causes color fringing, degrading image clarity
Check out our QNX BSP Demo in the NXP platform here, live in action – Click Here The boot time in the real-time systems should be faster to achieve systems objectives and be reliable enough to meet its demand. QNX Real Time Operating System is a leader in the operating systems market and achieves great results applying advanced methods in boot enhancing without losing functionality and performance. This blog takes a look at six tried and tested strategies QNX normally employs in order to reduce boot time further helping developers create solutions that are always primed and ready for action.
Check out our QNX BSP Demo in the NXP platform here, live in action – Click Here Why Is It Important to Optimise Boot Time? Businesses prefer boot time optimisation as it allows them to enhance user experience as well as operational efficiency. Moreover, for sectors such as automotive, where every passing second counts, quicker boot times offer more responsive systems. Similarly, embedded Linux boot time optimisation provides for enhanced reliability and performance when it comes to ADAS or infotainment systems. The below image vividly illustrates two critical scenarios – defence and medical – where choosing the right operating system
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