Self-supervised collaborative approach to machine learning by models deployed on edge devices

A surveillance system comprising:

• a server system that is configured to—
• obtain images that are labelled to indicate that a given object is contained therein,
• train a model to detect instances of the given object by providing the images to the model as training data, and
• cause transmission of the trained model to a camera to be deployed in an environment to be surveilled;
• and
• the camera that is configured to—
• generate a first series of images of the environment, and
• tune parameters of the trained model based on an analysis of the first series of images so as to create a local version of the trained model that is adapted for the environment,
• wherein the camera is configured to tune the parameters of the trained model in response to a determination that a predetermined number of images of the environment have been captured since the local version of the trained model was last tuned.