Abstract: The flow and sediment of inland waterways are generally characterized by strong time-varying, nonlinearity and randomness. The rapid and efficient measurement of the spatio-temporal data in a large range is noted as a challenging task. With the development of shipborne sensors, Internet of Things, mobile computing and other technologies, the hydrology observations based on shipborne sensors have drawn more attentions in the past several years. The research progress of shipborne integrated underwater and aquatic measurement system is introduced. The technical requirements of a shipborne observation system of waterway hydrology are thus demonstrated in details. The basic principles and characteristics of the information processing technology of flow and sediment particles are further analyzed. A literature review of intelligent multi-source image processing methods for waterway engineering is provided. Prospects of the core sensors, intelligent algorithms, real-time computing models and other key technologies are summarized. The technical analysis shows that it is generally feasible to develop an integrated mobile measurement system for hydrological elements of inland waterways based on the new generation of artificial intelligence technology and the high resolution shipborne sensors.