Sensors play an important role in collecting real-time information for transportation systems. Nowadays, several different sensor technologies, ranging from traditional ones to mobile sensors in smartphones, are being used to collect a massive data volume on the real-time location and dynamics of users. For example, most of the modern smartphones are equipped with multiple motion sensors, such as accelerometer and magnetometer sensors, which can provide an unprecedented opportunity for the monitoring of the motion status of mobile phone users. On the other hand, there are a wide variety of data mining and prediction techniques, which can support transportation researchers in analyzing raw travel data collected from sensor technologies. This article provides a review of various applications of sensor technologies in transport networks, including travel time estimation, origin–destination matrices estimation, safety analysis, driver behavior monitoring, and transportation mode inference.