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AWS Panorama

AWS Panorama is a set of machine learning (ML) devices and a software development kit (SDK) that provides computer vision (CV) to on-premises internet protocol (IP) cameras, according to the company.

Why AWS Panorama?

Computer vision at the edge can help you improve your operations. AWS Panorama devices, which interface easily with your local area network, are a cost-effective way to add computer vision (CV) to your existing fleet of cameras. Make predictions locally with high accuracy and low latency using a single management interface, which allows you to examine video feeds in milliseconds and make predictions with high accuracy and low latency. Process video feeds at the edge, giving you complete control over where your data is stored and operating with restricted internet access.

How it Works

 

Image sourced from Amazon Web Services

Use Cases

  • Improve the logistics of the supply chain:

Throughput may be tracked and optimized while parts or products or text on labels or barcodes can be recognized.

  • Improve the efficiency of traffic management:

Traffic lanes are being monitored for concerns such as stopped vehicles, and real-time alerts are being sent to personnel to keep traffic flowing.

  • Evaluate the manufacturing process’s overall performance.:

Manufacturing irregularities should be identified as soon as possible so that the user can take remedial action and reduce expenses.

Features 

  • Quick and simple set-up

The AWS Panorama device connects to the AWS Management Console after being deployed and linked to your network. From there, you can register your AWS Panorama device, add video feeds from onsite cameras, train machine learning models, and run apps in minutes.

  • IP cameras should be connected.

RTSP-enabled IP cameras can be used with AWS Panorama devices, and you can also add IP cameras that support the ONVIF standard to your account.

  • Support for several models and streams in parallel

AWS Panorama devices are capable of connecting to numerous camera streams at the same time, as well as running several machine learning models on each stream.

  • Inference on the periphery

AWS Panorama enables you to deploy CV applications to the edge, allowing you to execute cloud-based machine learning in areas where low latency, data privacy, and restricted internet speed are important considerations, such as healthcare. In addition, AWS Panorama provides a customizable alternative for including CV to automate processes that would otherwise require human inspection and supervision, such as data collection.

  • GPU (graphics processing unit) computation

AWS Panorama devices are equipped with a built-in NVIDIA Xavier GPU, allowing familiar programming and quick machine learning computation at the edge.

  • Managed service from the edge to the cloud

Using a single management interface in the AWS console, you can easily discover existing fleets of IP cameras at the edge, create and deploy computer vision applications across AWS Panorama devices, manage the versioning and lifecycle of those applications as they are used for a variety of use cases, and perform other analytics to drive process improvements across multiple sites.

  • CV deployment options that are adaptable

AWS Web Services Panorama (AWS Panorama) supports an expanding community of pre-built apps from AWS cloud computing and third-party (3P) developers. As a result, customers with no prior machine learning knowledge may get up and running quickly with apps from AWS development services and 3Ps that enable people counting, vehicle classification, license plate recognition, and other capabilities. As a bonus, AWS Panorama enables developers to train their machine learning models in the cloud using frameworks before swiftly optimizing them to run efficiently and accurately at the edge.

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Management of the API Lifecycle

Faster development of computer vision applications

  • SDK for application development

With a Python-based software development kit, you can easily gather camera frames and make machine learning (ML) inferences on image data without programming knowledge (SDK).

  • Case studies in the application

With working sample code, you’ll learn how to create applications for common scenarios.

  • Test Utility

Allows you to test and debug AWS Panorama apps without the need for a physical device to be present.

  • Large-scale support for machine learning frameworks

Consider using TensorFlow, PyTorch, or MxNet to train models and algorithms. Using Nvidia TensorRT, Amazon SageMaker Neo, or your machine learning runtime, test models and see how they perform.

  • Networking on a local level

Create a direct connection between AWS Panorama apps and systems on the local area network to receive event triggers or publish findings without going to the cloud.

  • Monitoring of applications and devices

Alarms can be set up in Amazon CloudWatch to alert you when your AWS Panorama application or device faces problems.

  • APIs for administration

Use application programming interfaces (APIs) to automate workflows in the control of devices, cameras, and software applications.

  • The use of end-to-end encryption

AWS Panorama simplifies securing your application by encrypting models, passwords, and assets while they are in transit and at rest.

AWS Panorama Devices

 The AWS Panorama Appliance and the Lenovo ThinkEdge SE70, both powered by AWS Panorama, are two possibilities for AWS Panorama devices. Depending on your specific use case, you can choose from various hardware alternatives that vary in both price and performance. In addition, regardless of which device you select, you may work with AWS Panorama Partners to develop a bespoke CV application or deploy pre-defined solutions such as boosting supply chain logistics, optimizing traffic management, or analyzing manufacturing quality.

Lenovo ThinkEdge SE70 laptop computer

The Lenovo ThinkEdge SE70 is intended to fulfill the growing demand for intelligent transformation in various industries, including logistics, transportation, smart cities, and retail, healthcare, and manufacturing environments. The new Lenovo edge solution was developed in collaboration with AWS, and it is powered by the NVIDIA® JetsonTM XavierTM NX platform, which NVIDIA Corporation developed.

AWS Panorama Appliance

The AWS Panorama Appliance is another hardware device option that can be integrated smoothly into your local area network and can run several computer vision (CV) models on numerous concurrent video streams. In addition, the AWS Panorama Appliance is a ruggedized IP62 certified edge appliance, which makes it appropriate for deployment in various situations due to its dustproof and water-resistant design.

It features one HDMI connection for connecting to a video monitor to view inference output and two GigE Ethernet ports for redundancy, connecting to two subnets, or load balancing. The AWS Panorama Appliance also has a USB connector connecting to a computer. The device is approximately half a rack unit wide, which means that two units can be placed side by side on a regular rack shelf on a server rack and secured to the rack with the screws included with the device.

AWS Panorama Device SDK

Manufacturers can create new edge appliances and smart cameras that can run computer vision (CV) models at the edge using the AWS Panorama Device Software Development Kit (SDK). The AWS Panorama Device SDK enables device manufacturers to integrate AWS Panorama with a wide range of edge gateways and smart cameras, among other things. Edge gateways and smart cameras from major device manufacturers, powered by AWS Panorama, will enable clients in the transportation and logistics, travel, manufacturing, and other industries to meet their specific edge computer vision use cases on the edge of the network. Build Panorama devices with the AWS Panorama Device SDK, which is being used by companies including Lenovo, ADLINK Technology, Axis Communications, Basler AG, STANLEY Security, and VIVOTEK.

This SDK for AWS Panorama Devices provides device makers with a computer vision device software stack, sample code, APIs, and tools to enable and test their particular devices for use with the AWS Panorama service. After completing their preparations, device manufacturers will collaborate with the AWS Panorama team to finalize the integration of the AWS Panorama Device SDK and conduct certification tests before launching their commercial products, giving them a competitive advantage in terms of time-to-value.

AWS Panorama Device SDK now supports the NVIDIA Jetson product line, available for download here.

Need help on AWS?

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Pricing

AWS Panorama devices extend the capabilities of your existing on-premises cameras by incorporating computer vision (CV). You pay for the physical gadget upfront, and then you are paid a monthly fee based on the amount of unique camera video streams processed on the device by the device. Charges for cloud storage of application assets delivered to the device, such as machine learning (ML) models and business logic, are in addition to the device’s monthly fee.

For AWS Panorama Devices and Usage Devices, the following pricing is available: You will be required to pay a one-time fee for the gadget.

Device usage:

TYou will be charged $8.33 per month for each camera video stream processed on the device by the device.

In the AWS Panorama cloud storage service, versioned copies of application assets (including machine learning models and business logic) that have been deployed to devices are stored in the cloud. You will be charged $0.10 per GB per month, calculated every month for this storage.

Charges in addition to the base rate

If the business logic delivered to your AWS Panorama device uses other AWS services, you may be subject to additional charges. For example, you will be charged individually by Amazon S3 for any storage charges incurred if your business logic uploads ML predictions to Amazon Simple Storage Service (Amazon S3) for offline analysis. For further information, please see the Amazon S3 pricing page and the pricing sites for the other relevant AWS computing services.

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