• The brand new tyre strain monitoring system improves security and person experiences
• ST’s software program ecosystem device, STM32Cube.AI, accelerates the event of the sting AI operate working on the STM32 microcontroller

STMicroelectronics, a worldwide semiconductor chief serving prospects throughout the spectrum of electronics purposes, has introduced that Panasonic Cycle Expertise, Co. Ltd. (Panasonic) has adopted the STM32F3 microcontroller (MCU) and edge AI improvement device, STM32Cube.AI, for his or her TiMO A e-assisted bike. ST’s edge AI options present a tyre strain monitoring system (TPMS) that leverages a complicated AI operate to enhance rider security and comfort.

Panasonic is a number one producer of e-assisted bikes in Japan and provides all kinds of merchandise for varied makes use of to the Japanese market. Their electric-assist bicycle for varsity commuting, TiMO A, runs an AI software on the STM32F3 MCU to deduce the tyre air pressures with out utilizing strain sensors. Based mostly on info from the motor and the bicycle velocity sensor, the system generates a warning to inflate the tyres if needed. ST’s edge AI improvement device, STM32Cube.AI, enabled Panasonic to implement this edge AI operate whereas becoming into STM32F3 embedded reminiscence area. This new operate simplifies tyre air-pressure upkeep, which reinforces rider security and prolongs the lifetime of tyres and different cycle elements. It additionally helps to cut back the price and design work, as there isn’t any want for added {hardware} equivalent to an air strain sensor.

“We develop and manufacture e-assisted bikes with the mission of delivering environmentally pleasant, protected, and comfy transportation, accessible to all,” stated Mr. Hiroyuki KAMO, Supervisor, Software program Growth Part, Growth Division of Panasonic Cycle Expertise. “ST’s STM32F3 MCU supplies price competitiveness and optimum capabilities and efficiency for e-assisted bikes. By combining the STM32F3 MCU with STM32Cube.AI, we have been capable of implement the modern AI operate with out the necessity to change {hardware}. We’ll proceed to extend the vary of fashions with AI capabilities and try to fulfil our mission by leveraging ST’s edge AI options.”

“ST has been actively engaged on the worldwide proliferation of edge AI in each {hardware} and software program, offering edge AI options to a variety of merchandise together with industrial and client tools,” stated Marc Dupaquier, Managing Director of Synthetic Intelligence Options, STMicroelectronics. “This collaboration marks a key step in our efforts, and we’re delighted to have contributed to the primary implementation of this AI operate in Panasonic’s e-assisted bike. We’ll proceed to suggest AI use instances and options for various markets, wherever we will help to reinforce our life.”

ST will showcase edge AI options, together with the STM32 MCU and quite a lot of AI improvement instruments, on the AI Expo at Tokyo Large Sight (Could 22-24, 2024). The e-assisted bike and the motor unit (cutaway pattern) from Panasonic Cycle Expertise, which options the STM32F3 MCU and STM32Cube.AI, are additionally scheduled to be displayed at this expo.

The way it works
The STM32F3 MCU adopted for the TIMO A is predicated on the Arm Cortex-M4 (with a most working frequency of 72 MHz) and encompasses a 128KB Flash, together with varied high-performance analog and digital peripherals optimum for motor management. Along with the brand new inflation warning operate, the MCU determines the electrical help degree and controls the motor.

It leverages STM32Cube.AI to cut back the dimensions of the neural community (NN) mannequin and optimize reminiscence allocation all through the event of this AI operate. STM32Cube.AI is ST’s free edge AI improvement device that converts NN fashions realized by basic AI frameworks into code for the STM32 MCU and optimizes these fashions. The device optimized the NN mannequin developed by Panasonic Cycle Expertise for the STM32F3 MCU rapidly and simply and applied it within the flash reminiscence, which has restricted capability.

ST provides a complete edge AI ecosystem for spreading edge AI to units utilized in a variety of situations. The ecosystem consists of STM32Cube.AI and in addition the NanoEdge AI Studio autoML device. Each instruments are a part of the soon-to-be-available ST Edge AI Suite. All of them can be found freed from cost.