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Designed to revolutionize voice-activated technologies, the NeuroVoice chip offers an ultra-low-power solution for processing and enhancing voice data. This chip leverages Neuromorphic Analog Signal Processing to improve voice recognition accuracy, even in noisy environments, making it ideal for integration into smart hearables, voice control systems, and hearing aids. NeuroVoice optimizes voice processing by isolating human speech from background noise, ensuring clear communication without the need for cloud processing. Its power consumption remains below 150µW, allowing for extended usage between charges. The chip's neural network-based voice extraction is tailored to enhance speech intelligibility, catering especially to those with hearing difficulties. Applications of NeuroVoice span across various domains including smart homes and factories, IoT devices, and mobile robotics. Its key features include intelligent voice activity detection and keyword spotting, offering on-device processing capabilities that safeguard user privacy while eliminating latency issues typical of cloud-based solutions.
The NeuroSense chip serves as a state-of-the-art solution for wearables, notably enhancing the accuracy and efficiency of health monitoring applications. It relies on Neuromorphic Analog Signal Processing technology to address key issues in mass-market wearables such as heart rate measurement accuracy and power consumption. NeuroSense ensures always-on, cloud-independent operations, providing three times better heart rate accuracy compared to conventional algorithms while maintaining ultra-low power usage, consuming less than 100µW. The chip is embedded with sophisticated features such as human activity recognition directly at the sensor level, permitting wearables to operate without extensive cloud support. This capability not only offers longer battery life but also boosts the device's data privacy. Furthermore, it simplifies hardware configurations by using fewer components, which significantly reduces the size constraints often associated with wearable technology. NeuroSense also facilitates complex functions like learning and automatically detecting new human activities, making it adaptable for more diverse applications including oxygen saturation measurement, stress monitoring, and sleep tracking. Its design focuses on providing a seamless integration path for manufacturers, ensuring a faster time-to-market with reduced development costs.
The VibroSense chip is engineered to deliver ultra-low-power vibration analysis, making it invaluable for the Industrial IoT sector. By pre-processing vibration data at the sensor level, this chip significantly reduces the volume of data needed to be transmitted, stored, and analyzed, cutting down associated costs and enhancing operational efficiency. Key applications of VibroSense include smart tire monitoring and machinery health diagnostics. For vehicle applications, it accurately detects road conditions and tire vibrations, contributing to improved safety and control. In industrial settings, it supports predictive maintenance by identifying potential machinery faults through vibration patterns, thus preventing costly downtimes. The VibroSense chip shrinks large data sets into compact signatures that are easier to transmit over long distances via narrow-bandwidth networks, without losing the accuracy needed for effective monitoring. This neuromorphic approach simplifies the monitoring of complex systems, allowing for energy-efficient designs that bring inherent cost savings and infrastructure optimizations.
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