Structure health monitoring is a general term used to describe the process of assessing the civil structure status and detecting and/or identifying any damage that occurs in the structure under monitoring. This work presents the design and operation of a synchronized structure health monitoring system that utilizes the internet of things technology. The proposed system consists of leaf nodes, a central node, and a monitoring server. The system utilizes two different wireless technologies to efficiently transfer the data and eliminate the need of fixed network infrastructure. The leaf nodes collect the acceleration signals from specific points in the structure using synchronized accelerometer sensors and send these signals to the central node using short range wireless communication protocol. The sampling process is synchronized among different sensors using an accurate timing signal from the global positioning system and an accurate external clock. The central node gathers the signals and relays them to a remote server using long range cellular internet connectivity. At the server, different damage detection and identification techniques are applied on the received data to assess the status of the structure. We provide details about the proposed system design and operation including the hardware and software parts. The different damage detection and identification techniques were considered and compared for predicting structural damage. Moreover, practical experiments were carried out, in which a five-story building model and real plane truss bridge were used to test the system. The results show the feasibility of the proposed synchronized system in automating the change in stiffness and mass by monitoring the dynamic behaviour.