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In a bold step toward reshaping the drone technology landscape, Nanoveu Ltd (ASX: NVU) has launched a two-phase trial to test the capabilities of its ultra-efficient embedded AI chip — ECS-DoT — in commercial drone platforms. The company’s subsidiary, EMASS, is leading the charge to demonstrate how this next-gen chip could redefine drone endurance and intelligence.
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The ECS-DoT chip is engineered to operate at sub-milliwatt power levels (<1mW), enabling drones to process complex AI tasks onboard, without constant uplinks to cloud servers. This results in significant efficiency gains: extended flight times, reduced data transmission, and real-time autonomy for tasks like infrastructure inspection, formation flying, and emergency response.
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Nanoveu’s announcement comes as Australia’s drone sector anticipates explosive growth, with projections of 60 million drone flights annually by 2043, and global UAV shipments forecast to top 7.5 million units by 2029. Amid this surging demand, ECS-DoT positions itself as a scalable solution for UAV manufacturers looking to embed AI at the edge while minimising energy use.
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In Phase 1, ECS-DoT is being evaluated through hardware-in-the-loop simulations using the PX4/Gazebo platform. Phase 2 will involve live drone deployments to validate gains in flight time (targeting 12–18 extra minutes per 60-minute mission) and power efficiency (up to 25% improvement). Crucially, the chip is also being tested for advanced use cases such as smart environmental sensing and autonomous landings.
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While NVU shares remained unchanged at $0.036 on Monday, the stock has delivered a staggering 89.47% return over the past year, underlining investor optimism about Nanoveu’s shift from surface materials to smart semiconductor systems.
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Nanoveu CEO Alfred Chong and EMASS founder Dr. Mohamed Sabry both emphasised the chip’s transformative potential beyond drones — eyeing applications in wearables, AR/VR, and the company’s own EyeFly3D platform.
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As the trials advance, the spotlight will be on how ECS-DoT performs in real-world drone scenarios — potentially charting a new flight path for AI-powered aerial systems.
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