Bandwidth Reduction with Anomaly Detection

We experiment with visual anomaly detection to develop techniques for reducing bandwidth consumption in streaming IoT applications. There seems to be no avoiding the tradeoff of spending compute to save bandwidth but we also want to spend it intelligently so we want to take advantage of the context. [With] visual anomaly detection, we stream ONLY infrequent anomalous images [and] explore unsupervised methods of reducing bandwidth by learning the context of a scene in order to filter redundant content from streaming video.