Human Presence Detection

Lattice sensAI Demo

Scalable human presence detection – This demo uses artificial intelligence (AI) to implement a human presence detection algorithm. FPGAs have flexible parallel data processing ability, making them more power efficient at such tasks compared to a microprocessor.

Always-on, local intelligence improves security – Bringing AI to the network edge is challenging, but it also offers tremendous opportunity. Designing AI into an iCE40 UltraPlus or ECP5 FPGA instead of cloud-based resources can dramatically reduce power consumption, limiting or even eliminating network bandwidth and latency while accelerating response time. Local processing clearly improves system robustness and security.

Scalable Multi-engine CNN across two FPGA Families – The Lattice inference engine with CNN architecture is able to fit into the iCE40 UltraPlus and several devices of the ECP5 FPGA Family.

Features

  • Accelerated, low-power human presence detection at the network edge using neural network model
  • iCE40 UltraPlus
    • VGG8 like 16-bit CNN
    • 64*64*3 input
    • 6 zone searching
    • Up to 8 frames per second
    • 1 mW of power consumption
  • ECP5 85
    • VGG8 like 16-bit CNN
    • 128*128*3 input
    • 6 zone searching
    • 15 frames per second depending on network selection
    • 0.85 W of power consumption
  • Adjustable Frame-rate
  • Can be optimized between power and response time depending on system needs
Lattice sensAI

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Block Diagram

Documentation

Quick Reference
Downloads
TITLE NUMBER VERSION DATE FORMAT SIZE
EVDK Based Human Presence Detection Demonstration User Guide
1.0 9/26/2018 PDF 1.4 MB
Himax HM01B0 UPduino Shield Based Human Presence Detection Low Power Demonstration User Guide
1.0 9/26/2018 PDF 529.8 KB
TITLE NUMBER VERSION DATE FORMAT SIZE
EDVK Based Human Presence Detection Low Power Demonstration Bitstreams
1.0 9/26/2018 ZIP 3 MB
Himax HM01B0 UPduino Shield Based Human Presence Detection Low Power Demonstration Bitstreams
1.0 9/26/2018 ZIP 592.7 KB


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