Maxim, Aizip team on lowest-power IoT person detection

April 20, 2021 // By Rich Pell
Maxim, Aizip team on lowest-power IoT person detection
Analog and mixed-signal semiconductor maker Maxim Integrated Products and IoT AI model developer Aizip have teamed to provide what they claim is the lowest-power IoT person detection solution.

The companies 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, say the companies, is 100 times lower than conventional software solutions, and the most economical and efficient IoT person detection solution available.

The low-power network is designed to provide longer operation for battery-powered IoT systems that require human-presence detection, including building energy management and smart security cameras.

"Aizip was quick to exploit our per layer quantization capability to reduce weight storage and achieve a compact, energy-efficient model for human detection," says Robert Muchsel, Maxim Integrated Fellow and architect of the MAX78000 microcontroller. "I look forward to working with them on future projects."

The MAX78000 low-power, neural-network accelerated microcontroller executes AI inferences at less than 1/100th 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% human-presence accuracy.

Key advantages of the solution are offered as:

  • 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.

Professor Bruno Olshausen at UC Berkeley, a highly recognized expert in neural computation/neural network models who also serves as an advisor to Aizip adds, "The combination of Maxim Integrated's ultra-low power chip solutions and Aizip's compact AI models is an important development that will enable many novel and exciting applications in the IoT world."

The MAX78000 microcontroller and MAX78000EVKIT evaluation kit cost $8.50 (1000-up, FOB USA) and $168.00, respectively. AIV

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