## 1 Introduction  
Structural health monitoring (SHM) of bridges can provide important information about structural performance and may help to detect anomalies or threats originating from damages or deteriorations at early stages. SHM can also be used to estimate remaining lifetime, to assist in bridge maintenance planning, to verify construction designs and to deliver important data in the case of disasters or extreme events [1; 2]. There exist three different techniques of SHM for bridges that can be classified into in situ, on-site and remote monitoring techniques. In situ monitoring techniques use sensors that are installed directly at a structure. On-site monitoring techniques are based on more complex sensors that are brought to a bridge during the monitoring campaign. Remote monitoring is done from a greater distance, for example by analyzing photographs of the structure taken from satellites or airplanes [3]. Especially in situ monitoring systems are often realized with the help of wireless sensor networks (WSNs), as they are inexpensive and easy to install on existing structures. Wireless sensor networks consist of sensor nodes, which are self- or battery-powered small units and communicate wireless with each other. Several wireless sensor network systems have been introduced during the last few years and decades for structural health monitoring of bridges. [PERSON] gives in [4] a comprehensive overview of installations for short-term monitoring and long-term monitoring. Short-term installations like [5; 6; 7; 8; 9; 10; 11] mostly measure accelerations, but some also include sensors for strain, temperature and velocity. Limitations arise mostly from the high power demands of the sensor nodes or base stations. [PERSON] et al. [11], for example, presents a wireless sensor network to monitor the Zhengdian Highway Bridge based on wireless sensor nodes, which use an MSP430 microcontroller and a CC2420 radio. The nodes are running TinyOS, which uses MintRout to send data over multi-hops to a base station. Including an energy storage of 7500 mAh, a node is able to monitor strain or acceleration continuously for around 168 h, or when choosing a sampling period of 1 h/day, the lifetime can be extended to 168 days. The base station is connected via a USB connector to a powerful host computer. Amongst the wireless monitoring systems reviewed in [4], there are also three long-term monitoring installations, one on the Jindo Bridge [12], one on the Stork Bridge [13] and one on the New Carquinez Bridge [14]. The work in [4] summarizes the challenges arising in long-term installations originating from power supplies, communication reliability, sensor reliability and challenging environmental conditions. As [PERSON] and [PERSON] point out in [15], large and dense sensor network deployments are often affected by large transmission delays as sensors cannot transmit their data concurrently. To increase communication reliability and to balance communication range, power consumption, data rate and link quality, [PERSON] and [PERSON] [15] introduce a wireless sensor node that uses frequency-division multiplexing to transmit data simultaneously using different frequencies. Furthermore, in [16], [PERSON] introduces a wireless sensor platform for SHM applications. The wireless sensor platform includes a power management unit to reduce the platform's energy consumption and can be equipped with several types of sensors ranging from low power to energy-hungry devices. [PERSON] also proposes an adaptive radio transmission power control algorithm along with a single-hop communication strategy. The power control algorithm adjusts the radio transmission energy to the link quality to save energy during the wireless data acquisition [16]. With respect to structural health monitoring, one other important measurement is the three-dimensional displacement of a structure or of parts of it.