“AI Urban Management Officer” is here: an automatic encroachment operation identification system built on OpenMV

Illegal street vending recurs frequently; the challenge of governance lies not in “detecting it once” but in its “long-term persistence.” OpenMV enables management to shift from concentrated rectification to daily perception through continuous visual monitoring.

Occupying public roads for commercial operations is a common issue in urban governance; business facilities such as stalls, shelves, and tables encroach upon sidewalks or vehicular lanes, not only disrupting traffic order but also posing safety hazards—particularly pronounced during morning and evening rush hours or in densely populated areas.

Managing through manual inspections incurs high labor costs and makes it difficult to achieve long-term, continuous supervision, easily resulting in management blind spots where problems recur immediately after personnel leave.

Based on SingTown’s OpenMV smart camera, automated and routine visual monitoring can be conducted in areas prone to recurring incidents, such as key road sections, school perimeters, and commercial districts.

After the camera is fixedly deployed, OpenMV runs object detection algorithms on the edge device to automatically identify objects related to encroachment on public space, such as stalls, shelves, sunshades, and carts. Meanwhile, by integrating road boundaries, pedestrian walkway extents, and configured virtual rule lines, it determines in real time whether commercial activities have crossed designated boundaries.

When the system detects that business facilities encroach upon roads, obstruct pedestrian pathways, or exceed their licensed scope of operations, it can instantly output identification results at the edge side for on-site alerts, violation evidence collection, or automatic reporting to the urban management platform, thereby providing objective evidence for subsequent law enforcement.

Leveraging the on-device AI capabilities and edge deployment advantages of OpenMV, the management of unauthorized street occupation has shifted from periodic rectification to continuous perception and real-time detection, significantly reducing the burden on manual inspections and enhancing both the responsiveness and precision of urban governance.