Real-time CCTV Insights at the Edge with AWS Outposts

Authors: Abeer Naffa, Sr SA-Hybrid Cloud and Sumeeth Siriyur Sr SA-Hybrid Cloud

Architecting for Real-time Insights from closed-circuit television (CCTV) Cameras at the Edge with AWS Outposts, which offers guidance and considerations for implementing Outposts-based solutions to optimize CCTV camera feeds and analyzing them at the edge for the "Smart City Surveillance" use case.

As cities become increasingly connected and intelligent, the demand for advanced video surveillance systems that provide real-time monitoring, analytics, and enhanced security is growing. By leveraging edge computing, local law enforcement and emergency responders gain immediate access to live video feeds and real-time analytics from cameras scattered throughout the city. This enables them to respond swiftly to incidents such as traffic accidents, public disturbances, or security breaches, enhancing overall community safety and resilience. Outposts helps smart cities meet data security, low latency, regulatory and compliance requirements while reaping the benefits of the cloud.

This post is about how to design and architect Video Management System (VMS) components directly at the edge, bringing data processing closer to the source and enabling you with hybrid architecture best practices. Unlock architecture best practices in a smart city context, as deploying VMS components at the edge with Outposts can enhance public safety and security

Understanding Outposts advantages

Outposts is a fully managed service that extends AWS infrastructure, services, and tools to virtually any data-center, co-location space, or on premises facility for a truly consistent hybrid experience. With Outposts, you can run some AWS services locally and connect to a broad range of services available in the local AWS Region. Outposts can be used for video surveillance to bring the benefits of cloud computing to on premises environments. Here are some use cases for Outposts in video surveillance:

Low-latency video processing: With Outposts, you can deploy video processing workloads closer to the edge, reducing latency for real-time video analysis. This is especially useful in scenarios where immediate action or response is required, such as security monitoring or threat detection.
Hybrid architecture: Outposts enables a hybrid architecture where some video surveillance workloads can run on premises while others can be processed in the Regions. This allows you to leverage the scalability and storage capabilities of the Regions for long-term data retention and analytics, while still keeping critical video processing tasks local.
Data residency and compliance: In certain industries or regions, data residency requirements or compliance regulations may necessitate keeping video surveillance data within the boundary of a geographic location. Outposts provides a consistent infrastructure and management experience with the AWS Regions. This helps you meet these requirements without sacrificing the benefits of cloud computing.
Edge analytics and machine learning: Outposts supports running AWS services on premises, enabling machine learning (ML) for computer vision tasks. This enables you to perform advanced analytics, object detection, and other AI-powered video analysis directly at the edge, thereby improving responsiveness and reducing bandwidth consumption.
Data privacy and security: Video surveillance often involves sensitive data that needs to be protected. Outposts allows you to maintain tight control over your video footage and data, keeping it within your own premises. At AWS, security is our top priority. With Outposts you can apply your security policies and access controls to the on premises infrastructure while still benefiting from AWS security features and services.
Bandwidth optimization: By processing video data on-site using Outposts, you can reduce the amount of video traffic that needs to be transmitted to AWS Regions.

Components of a VMS

A VMS is a crucial element in the surveillance ecosystem, responsible for managing, storing, and analysing video streams from cameras and sensors. Let's explore the key components of a VMS and how they can be deployed at the edge using Outposts:

Video recording: VMS components can capture and store video feeds from multiple cameras, providing a comprehensive archive of surveillance footage. With Outposts, video recording can be conducted locally, reducing the need for constant data transmission to a centralized server.
Live video monitoring: Real-time monitoring is essential for immediate response to potential security threats or incidents. By deploying VMS components at the edge, organizations can access live video feeds instantly, enabling rapid decision-making and response.
Video analytics: VMS platforms often incorporate intelligent video analytics, leveraging ML algorithms to detect anomalies, identify objects, or recognize patterns in video streams. Running video analytics at the edge using Outposts enables faster processing, making real-time insights and actionable data possible.
User management and access control: VMS components facilitate user management, defining roles, and access control to making sure that only authorized personnel can view and interact with the video feeds. Edge deployment enhances data privacy and security by keeping access restricted within the local network.

Architecture

The hybrid architecture for the VMS is designed to combine the strengths of both edge and region-based capabilities, offering a powerful and scalable video surveillance solution, as shown in the following figure.

Edge components

Web client: The edge-based web client allows users to access live streams and recorded footage from the local network. This enables low-latency and real-time access to video feeds, even in situations with limited or intermittent internet connectivity.
Alerting: The alerting component at the edge utilizes local processing power to detect events and trigger immediate notifications. This minimizes response times and reduces dependency on cloud connectivity for critical event alerts.
ML processing: ML processing enables quick and efficient analysis of video content directly on the cameras or local servers. This reduces the need to transmit large amounts of video data to the Region, optimizing bandwidth usage, and preserving privacy.
Database (DB): A Video Management System (VMS) database is a crucial component of video surveillance and management solutions. It's a centralized repository that stores various data related to video content, cameras, users, configurations, and more.
Amazon S3 on Outposts: Amazon Simple Storage Service (Amazon S3) delivers object storage to your on premises Outposts environment to help you meet local data processing and data residency needs.

Region components:

VMS management: The Region-based VMS management component offers a unified interface to configure and manage the entire video surveillance system. It allows remote access to camera settings, user permissions, and system configurations from any location.
Core analytics: AWS Region-based core analytics leverage the computational power of the cloud to perform advanced analytics when needed. This can include complex AI-based tasks like object detection, object tracking, and behavior analytics, which require substantial processing resources.
Amazon S3: is an object storage service offering industry-leading scalability, data availability, security, and performance.
AWS Key Management Service (AWS KMS): Lets you create, manage, and control cryptographic keys across your applications and AWS services.
Amazon CloudWatch: Using CloudWatch, you can effectively monitor and manage the Outposts resources as you would in the Region, levereging cloud-native tools such as CloudWatch dashboards. Check how to automate building CloudWatch dashboards for Outposts.

Benefits of hybrid VMS components at the edge with Outposts

This centralized management approach with AWS Outposts simplifies the complexities associated with scaling VMS operations, offering enhanced visibility and security across different environments. The architecture not only enhances operational efficiency but also ensures consistent performance and security as you expand from one site to many.

Reduced Latency: Edge deployment minimizes data transit times, enabling real-time video monitoring and faster response to security events.
Bandwidth Optimization: Processing video data locally reduces the burden on the network, thereby optimizing bandwidth usage and making sure of smoother video transmission.
Security: AWS Outposts offers the same security features and controls available in the AWS Region. You can leverage AWS security services and best practices to protect your video data and the infrastructure it runs on.
Enhanced Data Privacy: Sensitive video footage remains within the organization's premises, thereby reducing the risk of data exposure to external entities.
High Availability: AWS Outposts supports high availability configurations and the tools required to architect resilient applications, ensuring that your video surveillance system remains operational even in the case of hardware failures.
Scalability and Flexibility of the Cloud: Outposts provide the scalability of the cloud, allowing organizations to expand their surveillance infrastructure as needed without significant infrastructure changes.
AWS AI and Analytics Capabilities: AWS Region based core analytics leverage the computational power of the cloud to perform advanced analytics and complex AI-based workloads.
Centralize VMS Management: a centralized hub at the Region to manage multisite for VMS solution at the edge when needed.

Disclaimer: Many factors are involved in Outposts sizing for this hybrid architecture, such as the number of cameras, feed resolution, throughput required, and desired processing capabilities, to achieve optimal resource allocation and scalability. This must be addressed as part of Outposts technical discussions with your implementation partner.

Conclusion

In this post, you learned the VMS architecture and the different components that can be installed on Outposts. The integration of VMS components with Outposts heralds a new era in surveillance technology. By harnessing edge computing, organizations can unleash the full potential of their surveillance systems, with reduced latency, optimized bandwidth, and enhanced data privacy. From enterprises to smart cities, the possibilities of edge-powered VMS are limitless.

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.

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