Elevated hazards are not identified by the naked eye; OpenMV uses AI to detect them in advance

Falling object incidents are often caused by small cracks and aging issues that have long been overlooked. Manual inspections are time-consuming, high-risk, and unable to detect changes promptly. OpenMV proactively identifies façade hazards through continuous visual monitoring.

In densely built-up urban environments with numerous high-rise buildings, ageing façades, expanding cracks, or local spalling—when not detected promptly—can easily lead to safety incidents such as falling objects from height, posing serious risks to personnel and property.

However, traditional façade inspections primarily rely on manual visual checks or high-altitude operations, resulting in long inspection cycles, low coverage frequency, high operational risks, and inconsistent subjective judgments—making it difficult to meet the requirements for continuous safety supervision. By introducing SingTown’s OpenMV intelligent cameras, façade safety inspections can be upgraded from “intermittent manual checks” to “continuous online visual monitoring.”

The camera can be installed at fixed monitoring points around the building or mounted on lifting devices or inspection equipment to capture images of critical façade areas at predefined intervals. OpenMV runs edge detection, texture variation analysis, and crack feature extraction algorithms on the camera’s edge device to analyse subtle structural features on wall surfaces and compare them against historical images to identify abnormal changes such as crack propagation, surface spalling, and local damage.

Leveraging the continuous comparison capability of edge AI, the system can not only detect “whether an issue exists” but also determine “whether the issue is progressively deteriorating”. All identification processes are performed entirely on the OpenMV edge device, with only critical results—such as the location of anomalies and trend information—being output. This significantly reduces the transmission requirements for raw image and video data, thereby lowering system bandwidth and storage demands, and providing property management or operations and maintenance units with clear, actionable maintenance decision support.

Leveraging OpenMV’s on-device AI and edge deployment capabilities, safety management of high-rise building façades has shifted from “post-incident investigation” to “proactive early warning,” effectively enhancing urban operational safety.