NeuroSense, Edge Intelligence to your product

Custom Algorithm Development Process

1.Understanding Customer Data Processing Demand

“Can I develop a wearable sensor that recognizes the cow’s fertility?”

“Can I analyze the fault data of our motor and develop a pre-diagnosis sensor?”

2. Customer Data Collection

  • Data Gathering Tool
  • Data Labeling Tool

3. Data Analysis and Classification Algorithm Development

  • Data processing
  • Feature generation and selection
  • Training / Simulation
  • Neuron array output

4. Porting Custom Hardware

DATA → Gathering & Labeling(Data gathering phone application) → { [Sensor/ Cloud Application : “Efficient Toolchain Optimized for Edge AI Devices”] Machine Learning → Intelligence pack(Edge Embedded optimized python-based ML framework) → } Bin.SW - Firmware → HW Flash(Firmware development environment)