Yesterday, Jesse Liauw-A-Fong, a student of the Master of Software Engineering program at UvA, defended his thesis Local Anomaly Detection in Smart Public Transport Vehicles. This research was conducted externally at a company called Ximedes. Jessie’s research is addressing the problem of detecting anomalies, such as a loss of cloud connection, in Smart Public Transport Vehicles (SPTV), such as buses, trams, and metros, comprising many complex heterogeneous systems. It emphasizes the importance of local, context-aware anomaly detection due to the dynamic nature of SPTVs and explores the generalization of anomaly detection, particularly addressing performance, normal region, and quality challenges. The research proposes a unified data collection framework comparing agent-based and agent-less methods, advocating for an agent-based approach for its adaptability and integration ease. It also quantitatively evaluates three local anomaly detection algorithms on real data from a specific bus line. We thank Jessie for his contributions to our research and wish him the best of luck in his future career.