Got your number(plate): XMOS announces low cost, low power ALPR reference design for smart parking
Design intends to help shift solutions away from high cost, high power hardware in favour of streamlined, efficient machine learning
Bristol UK, 17 March 2022 — Leading British chip company XMOS today announces its reference solution for Automatic Licence Plate Recognition (ALPR), designed to move ALPR in parking garages away from complex, resource-intensive hardware and towards simple on-device AI.
Developed in partnership with computing specialist Cloudtop, the reference design can read slow-moving licence plates at a distance of 3-5 metres with high accuracy. Thanks to the capabilities of XMOS’ xcore.ai silicon, Cloudtop’s machine learning model – originally designed to work with high resolution video frames – has been seamlessly adapted to work in a low power, low cost scenario without sacrificing accuracy.
Parking garages that utilise ALPR have traditionally integrated hardware that is far beyond the spec required for slow-moving, close-range plate recognition. High-resolution cameras, operating on complex machine learning models that depend on cloud connectivity for image processing, have made the implementation of ALPR prohibitively expensive in many cases.
XMOS’ reference design instead provides the required power and intelligence on-device, dramatically lowering both power consumption and the Bill of Materials (BOM) in comparison to standard ALPR solutions. In removing the need for high-cost hardware and virtually eliminating the need for cloud connectivity, such a device becomes a realistic component of the ALPR infrastructure across the smart city.
“For smart parking, cloud connectivity and huge processing power is simply overkill,” commented Aneet Chopra, VP Product, Marketing & Business Development, XMOS. “It makes ALPR networks far more expensive than they need to be, makes maintenance more complex, and comes rife with privacy concerns inherent to the cloud.
“The reference design we’ve developed eliminates those issues simply by streamlining the process. If you can deliver the intelligence and power you need on-device, you avoid sending all raw data to cloud, or excessively expensive or powerful hardware. That’s only going to help us drive progress in ALPR in the long run.”
“Simplicity and affordability are two priorities in the ALPR space, not only to drive sales but to encourage innovation” commented, Prof. Zhang, Co-founder of Cloudtop. “Making devices cheaper, simpler and more reliable will be hugely important for the smart city, and downscaling machine learning models so that they can run on mass-producible silicon like xcore.ai affords developers the funding and design flexibility to experiment.”
XMOS and Cloudtop will showcase the solution at tinyML Summit in San Francisco, between 28-30th March, and invite all attendees to visit their exhibition stand and poster presentation. If you would like to find out more about the reference design, or would like to discuss working in partnership with XMOS on a similar solution, please register your interest here: https://www.xmos.ai/alpr
A deep tech company at the leading edge of the artificial intelligence of things (AIoT), XMOS addresses the evolving market need for flexible compute to serve an ever-widening range of smart things including voice, imaging, and ambient sensing.
The company’s uniquely flexible xcore processors allow product designers to architect system-on-chip solutions purely in software, enabling faster time to market with differentiated systems that are cost-effective and energy efficient.
Charlie Apsey / Ben Musgrove, Wildfire
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