## 5 Application of Self-Sensing Materials for
### Traffic Monitoring
This finding is corroborated by laboratory experiments showing an increase in FCR variations with escalating load levels [91]. In the case of an unloaded truck, the front axle load is heavier than the other axles, resulting in a larger FCR change under the first axle compared to the subsequent axles. Conversely, in loaded trucks, the FCR changes are higher under axles other than the first, since in the loaded condition, the first axle beneath the driving cabin is lighter than the other axles. Similarly, the practical application of self-sensing cementitious composite, doped with 2.5% CB by weight of cement and 30% granulated blast furnace slag (GBFS) by weight of cement, for traffic detection has been investigated in the field under various types of vehicles [231]. In line with previous studies discussed earlier, the findings presented the detection of axle load based on the drastic changes in voltage over time. Considering the obtained results, it can be concluded that the sensing performance of self-sensing cementitious composites doped with CNMs can be further enhanced by incorporating GBFS content, primarily due to its high iron oxide (Fe\({}_{2}\)O\({}_{3}\)) content, typically around 11.9%. Therefore, it is evident that incorporating additional additives with higher electrical conductivity can significantly improve the sensitivity of multifunctional cementitious composites while addressing sustainability concerns in civil structures [202]. To achieve this, some conductive recycled waste materials can be considered for incorporation into multifunctional cementitious composites for the production of self-sensing feature [233]. The self-sensing cementitious sensor developed with a 1% CNF content by weight of the binder has been installed in a mortar slab to detect human motion and traffic flow [229]. The sensor, integrated into the mortar slab, successfully detected human motion in two scenarios: \"up-down feet\" and \"jumped up-down feet\". The FCR increased when feet are on the ground, which then approaches the baseline when feet are lifted. In contrast, in the \"jumped\" condition, the FCR initially increased with the weight of the human body and then further increased during the jumping action. Similarly, the traffic flow was detected by the sensors installed in the mortar slab. The findings also demonstrated that the developed sensors are capable of detecting passing vehicular axles at various speeds. Given the demonstrated ability of the developed self-sensing cementitious sensor to detect both axle load and human motion, it can be inferred that this material could also be utilized for speed calculation purposes. In another study, a self-sensing cementitious composite incorporating chopped carbon fiber (CCF) and macro end hook steel fiber (SF) was evaluated in a field setting for its ability to detect traffic flow [234]. The findings revealed that there are significant temporal fluctuations in the FCR during the passage of vehicles over the self-sensing pavement. Furthermore, it was found that larger FCR changes occur when the electrical signals are captured from electrodes positioned closer to the applied axle load. This finding underscores the importance of strategic electrode placement in such applications. To incorporate sustainability measures, an environmentally friendly self-sensing cementitious pavement was developed by integrating an eco-friendly binder (EVIzero) and CNFs [235]. The performance of the developed self-sensing cementitious pavement was evaluated in the field under the passage of bicycle wheels. During the loading stages, a weight of 58 kg was applied, and in the unloading stages, the bicycle wheels were removed. The developed self-sensing pavement demonstrated significant sensitivity under the passage of bicycle wheels. The findings also revealed that the developed self-sensing cementitious pavement exhibited responsiveness under various loading conditions, including fast unloading, slow unloading, fast loading, and fast unloading.