Maxim Integrated Products, Inc. and Aizip Inc. announced that Maxim Integrated’s MAX78000 neural-network microcontroller detects people in an image using Aizip’s Visual Wake Words (VWW) model at just 0.7 millijoules (mJ) of energy per inference. This is 100 times lower than conventional software solutions, and the most economical and efficient IoT person-detection solution available. The low-power network provides longer operation for battery-powered IoT systems that require human-presence detection, including building energy management and smart security cameras.
The MAX78000 low-power, the neural-network accelerated microcontroller executes AI inferences at less than 1/100th of the energy of conventional software solutions to dramatically improve run-time for battery-powered edge AI applications. The mixed precision VWW network is part of the Aizip Intelligent Vision Deep Neural Network (AIV DNN) series for image and video applications and was developed with Aizip’s proprietary design automation tools to achieve greater than 85 percent human-presence accuracy.
Key Advantages include:
Extended Battery Life: Efficient AI model and low power microcontroller system-on-chip (SoC) reduce inference energy to 0.7 mJ, allowing 13 million inferences from a single AA/LR6 battery.
Cost-Effective Intelligence at the Edge: Extreme model compression enables accurate smart vision with a memory-constrained, low-cost AI accelerated microcontroller and budget-friendly image sensors.
The MAX78000 microcontroller and MAX78000EVKIT# evaluation kit are available now at Maxim Integrated’s website and through authorized distributors. The MAX78000 is $8.50 (1000-up, FOB USA) and the evaluation kit is $168.00.
AIV DNN series models, tools, and services are available directly from Aizip.