River scouring, a challenging environmental and engineering problem, endangered the safety and stability of many hydraulic structures like bridges. Sedimentation and its transport by water flow from riverbeds and banks, intensified by natural disasters and anthropogenic activities, may undermine structural stability, causing collapses. Some conventional scouring monitoring methods are visual check and spot sampling, which have limited real-time, are time-consuming, and do not reflect rapid or progressive changes. Technological advancement has enabled researchers to develop new solutions that include sensor-embedded systems, IoT architecture, remote methodologies, and analytical models to address these issues. Presenting the most recent technologies used in river scouring monitoring, this paper outlines their use, advantages, and disadvantages. It is crucial to mention that sensor-based systems enable the monitoring structural and environmental parameters with high accuracy and at a continuous level. In contrast, IoT networks allow data exchange in real-time mode and initiate an alert if necessary. Scouring analysis at a larger scale is possible through noncontact methods such as remote sensing through LiDARs and satellite imagery, and machine learning aids in predictive analysis by learning from historical and real-time data. Integrating various fields makes preventing such risks that lead to structural failures and their socio-economic consequences easier. The review stresses the importance of coherently implementing these technologies to develop large-scale, inexpensive, and robust monitoring systems that may function effectively in various environments. Future developments are aimed at increasing the precision of the predictions, increasing the service life of the sensors, and resolving issues such as data fusion and interoperability. These advancements will radically change infrastructure safety and vulnerability to diverse environmental threats.