In an effort to promote sustainable mobility, electric vehicles have emerged as a crucial innovation in the global transportation sector. This research, undertaken in conjunction with Brain Technologies and its innovative Evergrin project, investigates the use of artificial intelligence in electric vehicles, with a specific focus on the classification of accelerator pedal signals using neural networks. The research explores the application of Tiny machine learning (TinyML) in the automotive industry using the Raspberry Pi RP2040 as the microcontroller of choice. Key research questions include the ability of neural networks to detect anomalies in pedal signals, performance differences between TinyML models and neural networks, and the trade-off between model latency and accuracy on microcontrollers.