Kinesis Video Streams is ideal for building media streaming applications for camera-enabled IoT devices and for building real-time computer vision-enabled ML applications that are becoming prevalent in a wide range of use cases such as the following: Q: What are common use cases for Kinesis Video Streams? ![]() Amazon Kinesis Video Streams is designed specifically for cost-effective, efficient ingestion, and storage of all kinds of time-encoded data for analytics and ML use cases. Other examples of time-encoded data include audio, RADAR, and LIDAR signals. Video is an example of time-encoded data, where each frame is related to the previous and next frames through spatial transformations. Time-encoded data is any data in which the records are in a time series, and each record is related to its previous and next records. Kinesis Video Streams also supports ultra-low latency two-way media streaming with WebRTC, as a fully managed capability. For live and on-demand playback, Kinesis Video Streams provides fully-managed capabilities for HTTP Live Streaming (HLS) and Dynamic Adaptive Streaming over HTTP (DASH). Kinesis Video Streams enables you to quickly build computer vision and ML applications through integration with Amazon Rekognition Video, Amazon SageMaker, and libraries for ML frameworks such as Apache MxNet, TensorFlow, and OpenCV. ![]() It durably stores, encrypts, and indexes media in your streams, and allows you to access your media through easy-to-use APIs. Kinesis Video Streams automatically provisions and elastically scales all the infrastructure needed to ingest streaming media from millions of devices. Amazon Kinesis Video Streams makes it easy to securely stream media from connected devices to AWS for storage, analytics, machine learning (ML), playback, and other processing.
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