РОЗРОБЛЕННЯ СИСТЕМИ МОНІТОРИНГУ ДЛЯ ЗАРЯДНОЇ СИСТЕМИ ЕЛЕКТРОМОБІЛІВ З ЗАСТОСУВАННЯМ МЕТОДІВ МАШИННОГО НАВЧАННЯ

This work is devoted to resolving the issue of ICEing, where internal combustion engine vehicles occupy electric vehicle charging spots, causing inconvenience and disruption. It proposes a solution using magnetometers and machine learning methods for automatic classification of charging spot occupancy. The stages of data collection and processing of magnetometer signal are discussed, along with testing various machine learning models. The study evaluates different machine learning algorithms to identify the most effective approach for charging spot occupancy classification. Integration of the developed model on an STM32 microcontroller for real-world implementation is envisaged.