Accurate travel time information is required to efficiently plan and effectively manage transportation network. Technologies and data sources such as Bluetooth detectors and INRIX offer the potential to continuously collect the data and use it for long-term transportation planning as well as real-time traffic condition monitoring. However, their ability to accurately collect travel time data is still unclear. First phase of this study focused on capturing and estimating link/section level travel times using manual floating car method, Global Positioning System (GPS) floating car method, Bluetooth detectors, and INRIX. A comparison between travel times collected manually and using various technologies (GPS, Bluetooth detectors and INRIX) was performed. Results showed that both Bluetooth detectors and INRIX gave promising estimates for freeways. However, travel time data captured for arterial streets using Bluetooth detectors were less accurate and not dependable when compared to other technologies. Moreover, data from Bluetooth detectors showed a significant number of outliers. Therefore, the second phase focused on filtering raw sample of Bluetooth detectors data, estimating travel time, and then comparing with manual data to recommend filtering and data capturing criteria.