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The testing showed ECS-DoT could complete a full ‘sense–think–act’ loop at 50 Herz (Hz) in PX4/Gazebo Hardware in loop (HIL) tests – meaning the chip is able to process flight data and adjust propeller output 50 times per second (50 Hz) in real-time simulation tests.

This is fast enough for many real-time control systems, facilitating the rapid feedback for stable flight; on this basis, it can be said the chip supports stability in several environments, providing flight time improvements of up to 30%.

The purpose of ECS-DoT is for use in advanced on-board, ultra-low-power AI tasks such as inspection and precision landing, while also being designed to use less power than a typical digital watch (<1 mW).

Nanoveu said the next step in its assessment will involve ECS-DoT learning and optimising its own flight strategies through advanced, adaptive-AI techniques; final results from the testing are expected at the end of June, using the PX4/Gazebo platform1 and hardware-in-the-loop (HIL) testbenches.

The completion of this testing will kick off live drone trials.

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EMASS founder Dr Mohammed M. Sabry Aly said the testing had underlined the value of this chip. “This 50 Hz milestone proves ECS-DoT can handle real-time, high-frequency control loops with extreme energy efficiency,” he said.

“It’s a crucial first step toward transforming drones into smarter, longer-flying platforms that can perform complex tasks without cloud dependence or battery trade-offs.”

NVU has been trading at 4.9 cents.

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Fall detection systems are built around the need for sudden movements or impacts indicative of a fall, through the placement of sensors on the chest, wrist and other body parts.

Continuous monitoring is often required, meaning the systems need to perform energy-expensive computations to distinguish falls from other events.

The energy efficiency evaluation compared traditional ‘always on’ systems, optimised power management systems, and EMASS’s ECS-Dot Chipset, with the results showing power readings of around 10 milliwatts (mW), 0.5mW, and 0.112mW respectively.

Additionally, ECS-Dot executed its accurate fall detection AI model in just one millisecond.

These results are just one in a series being done to validate the ECS-Dot Chipset’s computational performance and energy efficiency in real-world use cases; these results indicate the advantageous nature of EMASS ECS-Dot in meeting the increasing demand for energy-efficient, AI-capable chip solutions.

Being able to meet the needs of the fall detection market is a particularly important achievement, given the strength of this sector – which is projected to reach approximately US$748.40 million by 2030 – driven by the growing elderly population, rising adoption of mobile-based solutions for personal safety, and advancements in wearable technology.

Founder of EMASS Professor Mohamed M. Sabry Aly said the assessment had demonstrated the superior qualities of this technology.

“These breakthrough results showcase how the ECS-Dot Chip, when used with advanced AI data processing and modern memory technologies can deliver practical, energy-efficient solutions for various real-world challenges,” he said.

“These results move us closer to our goal to develop and commercialize highly efficient semiconductor solutions that allow for seamless integration of AI into everyday life, improving both functionality and sustainability and opening multiple large unmet market opportunities for our proprietary technology.”

Nanoveu shares have spiked on the news and at 10:44AM they were trading at 3.6 cents – a rise of 9.09% since market open.

Join the discussion: See what HotCopper users are saying about Nanoveu and be part of the conversations that move the markets.

The material provided in this article is for information only and should not be treated as investment advice. Viewers are encouraged to conduct their own research and consult with a certified financial advisor before making any investment decisions. For full disclaimer information, please click here.