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GithubUnleashed pets constitute a recurring management challenge in communities and parks—visible yet difficult to regulate. Manual inspections are prone to blind spots, while conventional surveillance systems struggle to automatically discern detailed behaviors. OpenMV enables the system to directly identify whether a pet is on a leash for the first time.

In public areas such as communities, parks, and pedestrian streets, pets being off-leash is a frequent and difficult-to-manage issue.
Manual inspections are prone to temporal and spatial blind spots, while conventional video surveillance—although capable of “seeing”—struggles to automatically determine the specific behavior of “leash usage,” resulting in insufficient enforcement. Leveraging SingTown’s OpenMV intelligent camera, the system utilizes AI vision capabilities to automatically identify pet leash status on-site, providing technical support for civilized pet ownership management.
Cameras are deployed at community entrances and exits, main passageways, or key areas to continuously capture footage.
OpenMV runs object detection algorithms on the edge device to simultaneously identify “humans” and “pets” in the image, and further analyzes small targets between them by combining leash-line feature recognition with spatial relationship modeling to determine whether the pet is under effective restraint.
When the system detects a scenario where “a person and a pet are walking together without a leash,” it can instantly output the result on the device side, trigger voice alerts via connected devices, or report the incident to the community management platform to enable rapid intervention.
OpenMV deploys complex visual recognition and judgment logic directly on the camera edge side, offering advantages of low power consumption, low latency, and no need for continuous network connectivity, making it suitable for long-term operation scenarios such as communities and parks, thereby upgrading civilized pet management from “passive persuasion” to “active identification.”

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