Alif Semiconductor and onsemi Build an Extremely Efficient AI Camera System Reference Design using AI/ML

Computer Vision is taken to the next level of performance and efficiency by combining Alif's Ensemble™ MCU with onsemi's image sensor. The time required to complete each machine learning inference is 87 times less than that performed on a typical competing MCU, paving the way for low-power AI/ML cameras in a multitude of IoT applications

PLEASANTON, Calif., Nov. 15, 2022 /PRNewswire/ -- Alif Semiconductor and onsemi, a leader in intelligent power and sensing technologies, collaborated to create a complete camera reference design to maximize performance and efficiency for low power applications using machine vision such as supplemental security cameras, biometric ID passage control, retail management, and smart eyewear.

The challenge of implementing imaging products with a long battery life and enough localized AI/ML capability to be useful comes down to power consumption, ML inference latency time, and many times fitting into a restrained physical space. These issues are addressed by combining technologies from Alif using a highly integrated low-power MCU, and a compact low-power image sensor from onsemi.

Alif's Ensemble family of secure microcontrollers (MCUs) contain an ample amount of on-chip memory to store and process all image data without the need for external components that add cost, size, and consume extra energy. To further reduce power consumption, Alif's proprietary aiPM™ technology utilizes dual-processing regions within the MCU that uniquely accelerate machine learning. The MCU's High Efficiency region is designed to be always on to sense the environment, while the MCU's High Performance region wakes as needed to rapidly execute heavy workloads and return to sleep. For example, the High-Performance region can complete an ML inference for object detection in just 786 μsec, which is 87 times faster than a typical competing Arm®Cortex®-M based MCU running the same task at similar clock frequency. The dual processing regions in Ensemble MCUs enable extremely long battery life by serving up the optimum amount of processing power at any given time to satisfy immediate requirements.

"We've incorporated onsemi's sensor onto our development kit making it quite simple for developers to build their own AI imaging products," said Mark Rootz, VP of Marketing at Alif Semiconductor. "Starting from scratch on a design like this is no easy task when you deal with managing an image pipeline while optimizing machine learning and stretching power efficiency to the max. We do it all here in this reference design."

onsemi provides image sensors with a wide choice of resolutions, optical formats, and technologies for IoT applications including drones and barcode scanners. The ultra-miniature ARX3A0 sensor in this reference design is extremely low power, drawing less than 3.2 mW while active.

"onsemi offers a portfolio of low-power sensors designed specifically for AI/ML applications, which matches perfectly with the power-efficient engine in Alif's MCUs," said Steve Harris, Sr. Director of Marketing at onsemi. "This combination of low-power sensing and processing results in maximized battery or power efficiency for a broad range of AI-based systems."

For more information, come to the onsemi booth (101) in hall C4 at electronica 15 Nov 2022, and visit our website at www.alifsemi.com.

About Alif Semiconductor:

Alif Semiconductor was founded in 2019 with the vision to address the rapidly growing market need for broad, scalable, and connected AI-enabled embedded computing solutions that are genuinely power efficient. This need led to Alif Semiconductor's creation of microcontrollers and a new class of embedded controllers, fusion processors, that enable seamless integration of technology for everyday life by unlocking innovative low-power techniques, unparalleled functional integration, accelerated AI and ML edge processing, high security, ubiquitous wireless connectivity, and operating system diversity. For more information go to www.alifsemi.com.

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Becca Wirta
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