ANAHEIM, Calif., Sept. 15, 2026 (GLOBE NEWSWIRE) -- At Embedded World North America 2026, BrainChip Holdings Ltd. (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), a global leader in ultra-low-power, fully digital, event-based neuromorphic AI, is demonstrating three battery-powered edge AI applications — radar classification, human presence detection and fall detection — running entirely on device in real time at booth #6623.

The live demonstrations use BrainChip’s reference platforms to show how low-power, edge AI applications can move from proof of concept toward deployable products.

Each demonstration runs on three hardware platforms: production AKD1500 M.2 cards; the BrainBoard1500 NICLA development board; and the award-winning AkidaTag, a standalone smart sensor integrating an MCU, an AKD1500 chip and a companion mobile application.

"These aren't lab bench demos — they are battery-powered, field-deployable proofs of concept that developers can retrain with their own data," said Steve Brightfield, chief product officer at BrainChip. "That is the critical step between a lab demo and a product on the market. At Embedded World North America, visitors can see all three applications running in the palm of their hands."

The demonstrations at the BrainChip booth include:

• Radar Classification — A Raspberry Pi 5 with an integrated AKD1500 M.2 card and automotive radar front end performs micro-Doppler classification in real time. Traditional radar can detect an object’s presence; this demonstration also classifies the object by analyzing its micro-Doppler signature.
• Fall Detection — An AkidaTag module from SpanIdea integrates a Nordic wireless MCU and the AKD1500S chip in a device that fits in the palm of your hand. It performs real-time, battery-powered fall detection on device for health monitoring and wearable applications. The module is available for pre-order, with documentation and repositories publicly available on the BrainChip Developer Hub.
• Human Detection — A BrainBoard1500, NICLA-compatible development platform from Neuromorphyx performs real-time, person presence detection entirely on device. By processing sensor data and making inference decisions locally, the system eliminates the need to transmit video streams while maintaining responsiveness and data privacy.
  

The Backdrop For BrainChip’s Market Momentum

These demonstrations show how BrainChip delivers edge AI intelligence with ultra-low SWaP-C (Size, Weight, Power and Cost) products developers can plug into, run inference on and deploy across mobile, industrial and wearable markets.

That matters for the broader edge AI market, as it moves the category from bench demos to hardware developers can buy, build and deploy in the power- and size-constrained environments where conventional AI silicon can't go. 

BrainChip’s momentum also comes as privacy regulations, latency requirements and battery budgets continue to migrate inference away from the cloud and onto the device. It also comes as cloud-independent AI execution is moving from a differentiator to a procurement requirement in defense, industrial and medical sectors.

More broadly, the increase in edge devices, such as industrial sensors, cameras, robots and wearables, is fueling demand for edge AI silicon. ABI Research's 2Q 2026 market update estimates the edge AI chipset market at $34.4 billion in 2026, growing to $96 billion by 2031, with unit shipments more than doubling from 711 million to 1.59 billion.

About BrainChip Holdings Ltd.

BrainChip is the worldwide leader in edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, Akida™, uses neuromorphic principles to analyze only essential sensor inputs at the point of acquisition, processing data with unmatched efficiency, precision and energy economy. BrainChip’s technology is deployed across industries including aerospace, defense, industrial IoT, healthcare, consumer devices, and wearables. Explore more at www.brainchip.com.

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