This research will develop a coherent and holistic freight data collection framework for tracking vehicles and shipments and for surveying all relevant freight agents (e.g. producers, shippers, logistics providers, carriers wholesalers, retailers, end-consumers) with considerable time and geographical coverage (national, regional/urban, and rural areas). The framework is based on innovative and scalable technologies, and it aims to ameliorate inherent limitations in current freight data collection methods, obtain unprecedented freight data for statistical purposes, and enable the implementation of a new generation of freight models, including agent-based models. The key concept underlying this proposal is the Future Mobility Survey (FMS) tool, which has already proven effective in passenger surveys. FMS will use smartphones and global positioning system (GPS) loggers, advanced sensing and communication technologies, and machine learning algorithms to collect data reflecting what all relevant freight agents do, not what they say they do. State-of-the-art sensing devices enhance the quality and quantity of data, especially when combined with information from agents themselves.