Bringing AI to e-assisted bikes for affordable safety boost

ST's Edge AI solutions are utilised in a tyre pressure monitoring system (TPMS) that employs an advanced AI function to enhance safety and convenience for the rider.

Panasonic, a prominent e-assisted bike manufacturer in Japan, has adopted these technologies for the TiMO A, an electric assist bicycle designed for school commuting. The STM32F3 MCU runs an AI application that estimates tyre air pressures without relying on pressure sensors. Utilising data from the motor and the bicycle's speed sensor, the system can prompt the rider to inflate the tires when necessary. The STM32Cube.AI tool facilitated the implementation of this AI functionality within the constrained memory space of the STM32F3, simplifying tyre pressure maintenance and contributing to safer riding experiences and the longevity of the bicycle's components, while also reducing costs and design complexity by eliminating the need for a pressure sensor.

Marc Dupaquier, Managing Director of Artificial Intelligence Solutions at STMicroelectronics, commented: "ST has been actively working on the global proliferation of Edge AI in both hardware and software, providing Edge AI solutions to a wide range of products including industrial and consumer equipment. This collaboration marks a key step in our efforts, and we are delighted to have contributed to the first implementation of this AI function in Panasonic’s e-assisted bike. We will continue to propose AI use cases and solutions for diverse markets, anywhere we can help to augment our life."

ST is set to display its Edge AI solutions, including the STM32 MCU and various AI development tools, at the AI Expo at Tokyo Big Sight from 22-24 May 2024. The TiMO A e-assisted bike and a cutaway sample of the motor unit from Panasonic Cycle Technology, showcasing the STM32F3 MCU and STM32Cube.AI, will also be exhibited at the expo.

The STM32F3 MCU, pivotal for the TiMO A, utilises the Arm Cortex-M4 processor (capable of operating up to 72MHz) and is equipped with 128KB Flash memory and an assortment of high-performance analog and digital peripherals ideally suited for motor control. Beyond the new inflation warning feature, the MCU also regulates the level of electric assistance and manages motor operation.

ST promotes a comprehensive Edge AI ecosystem to broaden the application of Edge AI across devices in various settings. This ecosystem encompasses STM32Cube.AI and the NanoEdge AI Studio autoML tool, both of which will be part of the forthcoming ST Edge AI Suite, offered free of charge.