AWS Announces General Availability of the AWS Panorama Appliance

Today, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), announced the general availability of the AWS Panorama Appliance, a new device that customers can install in their facilities to run applications that analyze multiple video streams from existing on-premises cameras. The AWS Panorama Appliance enables customers to use computer vision technology to quickly and easily perform visual inspections of production lines (e.g. spot defects in manufactured parts), enhance customer experiences at quick service restaurants (e.g. monitor drive-through queues), or optimize the layout of physical retail stores (e.g. improve product placement, inventory checks, etc.). The AWS Panorama Appliance is one of four AWS products (along with Amazon Monitron, Amazon Lookout for Equipment, and Amazon Lookout for Vision) that form the most comprehensive suite of cloud-to-edge industrial machine learning services available. To get started with AWS Panorama, visit aws.amazon.com/panorama.

Customers in industrial, hospitality, logistics, retail, and other industries want to use computer vision to make decisions faster and optimize their operations. These organizations typically have cameras installed onsite to support their businesses, but they often resort to manual processes like watching video feeds in real time to extract value from their network of cameras, which is tedious, expensive, and difficult to scale. While some smart cameras can provide real-time visual inspection, replacing existing cameras with new smart cameras can be cost prohibitive. Even then, smart cameras are often ineffective because they are limited to specific use cases and require additional effort to fine-tune. For example, updating a smart camera because of a simple change in the environment (e.g. lighting, camera placement, or production line speed) means that a customer often has to contact their vendor for support, which can be costly and time consuming. Alternatively, some customers send video feeds from existing on-premises cameras to third-party servers, but often the required internet bandwidth is costly or facilities are in remote locations where internet connectivity can be slow, all of which degrades the usefulness and practicality of the analysis. Consequently, most customers are stuck using slow, expensive, error-prone, or manual processes for visual monitoring and inspection tasks that do not scale and can lead to missed defects or operational inefficiencies.