The research in this thesis focuses on developing an alert system to detect damage or impact on bridge. It employs Raspberry Pi and accelerometers for real-time health monitoring. The methodology includes bridge model creation, testing under no damage, impact, and structural damage conditions, and data processing for vibration frequency analysis. The aim is to differentiate between normal bridge conditions, collisions, and structural damages, providing timely notifications for necessary investigations or repairs. The study addresses the challenges in bridge safety and aims to improve maintenance efficiency and reliability.