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aiSensing Announces AI-based Predictive Maintenance Solution Based on QuickLogic EOS S3 Platform and SensiML Analytics Toolkit

Share this article Share this article SAN JOSE, Calif., May 20, 2021 /PRNewswire/  QuickLogic Corporation (NASDAQ: QUIK), a developer of ultra-low power multi-core voice-enabled SoCs, embedded FPGA IP, and Endpoint AI solutions, today announced that its customer, aiSensing, has developed an AI-enabled Industrial IoT solution that can determine multiple fault modes for predictive maintenance applications.  This vibration sensor employs Artificial Intelligence/Machine Learning (AI/ML) techniques to intelligently monitor equipment status and identify and signal when different fault modes occur. The aiSensing solution is based on QuickLogic s QuickAI platform including the ultra-low power EOS™ S3 multi-core sensor processing SoC, QuickFeather development kit, and SensiML Analytics Toolkit for endpoint AI applications.

Schneider Electric digitalisiert die Heizungsflotte von Suter

Schneider Electric digitalisiert die Heizungsflotte von Suter
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GPU-Computer GP-3000? Neue Dimension im Embedded Computing

GPU-Computer GP-3000? Neue Dimension im Embedded Computing
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Lattice introduces Automate stack

Lattice introduces Automate stack • Scalable Motor Control – accelerates development offlexible motor control systems, including a GUI-based user interface for system monitoring and control. • Predictive Maintenance – minimizes machine downtime by monitoring multiple motors in a system. • Embedded Real-time Networking – implements an extensible sense and control system for a large number of devices using a Lattice Nexus FPGA as the central controller. • Cyber Resiliency – enables a hardware Root-of-Trust that can detect, protect, and recover from a firmware-based attack in real time. • Easy-to-use Software Design Methodology – the stack supports Lattice Propel  for simplifying development of industrial automation systems with software/hardware co-processing using an embedded RISC-V processor.

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