Inspecting water filters in treatment facilities is tedious and costly, often requiring manual media disruption, significant labor, and extended downtime. These challenges underscore the need for improved methods to assess filter conditions efficiently and accurately. Given the essential role of water filters in safeguarding water infrastructure, periodic evaluations are crucial to detecting irregularities, such as unevenness or misalignment in the gravel support layers and piping within the filter system. Such structural anomalies can disrupt water flow across filtration layers, compromising water quality standards due to inadequate backwash operations characterized by unregulated, high-speed water streams from the filter base aimed at cleansing the filter media. Traditional inspection techniques, which require physically disturbing the filter media, are time-consuming and labor-intensive, involving at least two personnel for several hours, and risk overlooking defects due to limited sampling areas. To address these challenges, this study examines a new non-invasive approach that leverages the uneven backwash process and water flow data to identify water filters that contain defective filtration materials and structural problems without contact-based inspection. A central hypothesis of our investigation is that when subsurface structural irregularities disrupt normal backwash operations and flow patterns, they subsequently produce both visible surface deformations and distinctive anomalies in recorded sensor data. This non-invasive method assesses filters’ structural health and backwash efficiency in water treatment facilities through 3D laser scanning and sequential sensor data analysis. It aims to streamline the inspection process and reduce the costs and inaccuracies associated with manual media interruption. The results show uneven geometric features of the filter medium surface correlated with underlying structural faults and filter performance degradation, which is also validated by the sensor data. The proposed method offers a comprehensive understanding of the condition of water filters.