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 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
- 7 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
