AI gateway devices bridge legacy security cameras and cloud platforms, enabling real-time analytics, hybrid storage, and compliance-ready data protection with Micron’s high-performance SSDs for seamless AI-driven video security
The rapid adoption of cloud-based video security has revolutionised real-time video security, AI-driven analytics, and scalable storage, empowering businesses with deeper insights and faster response times. AI-powered insights, real-time alerts, and remote access enhance security operations, yet many legacy and third-party cameras lack cloud connectivity and AI capabilities.
These limitations hinder cloud-based video security, creating inefficiencies in data processing and storage. AI gateway devices (AI boxes) bridge this gap, enabling seamless cloud integration for video security systems. By extending the lifespan of existing infrastructure, AI boxes unlock advanced analytics, edge processing, and hybrid storage, enhancing operational efficiency and security resilience.
Connecting Legacy Cameras to the Cloud
Cloud-based video security services (VSaaS) offer remote access, centralised and decentralised analytics, and scalable storage, yet many third-party cameras lack native cloud compatibility. AI gateway devices bridge this gap, ensuring seamless integration between existing video security infrastructure and cloud platforms.
By acting as an intermediary, AI boxes transmit video feeds to the cloud, eliminating costly camera replacements while modernising security systems. They also support multiple cloud platforms, giving businesses flexibility in storage and analytics.
AI-Enabled Video Processing at the Edge
Beyond connectivity, AI gateway devices also play a crucial role in enhancing the intelligence of non-AI cameras. Many video security cameras still function as passive recording devices, capturing video without any built-in analytics. AI boxes introduce powerful edge processing capabilities, enabling features such as facial recognition, object detection, and real-time threat analysis.
Edge-based AI processing reduces latency and minimises the need to transmit vast amounts of video data to the cloud, conserving bandwidth and enabling real-time decision-making. For instance, an AI gateway device can analyse a video feed locally, detect an unauthorised individual, and send an immediate alert, rather than relying on cloud-based analytics that might introduce delays.
“For organisations managing diverse camera setups, AI gateway devices serve as a critical enabler of modern security, providing AI-driven functionality without requiring costly hardware replacements,” says David Henderson, Senior Director of Industrial Segment at Micron. “These solutions ensure seamless cloud integration while also supporting real-time, local analytics.”
Balancing On-Premise and Cloud
Another significant advantage of AI gateway devices is their ability to support hybrid cloud storage solutions. While cloud storage offers scalability and remote accessibility, some security applications often require local storage solutions in addition to reduce bandwidth consumption and internet disconnection. AI boxes provide local storage options, allowing critical data to be retained on-site while also facilitating cloud uploads when necessary.
This hybrid approach ensures continuous operation even in the event of connectivity disruptions, reducing reliance on cloud bandwidth while maintaining a secure, redundant backup.
Storage Requirements for AI Gateways
The deployment of AI processing within video security systems places unique demands on storage. Unlike traditional security solutions that primarily manage video footage, AI-enabled security systems also generate significant amounts of metadata, requiring storage solutions capable of handling both sequential and random data access. This metadata, which includes object classification, facial recognition markers, and behavioural analysis insights, must be processed and stored efficiently to ensure smooth AI operations.
AI gateway devices require storage solutions that can sustain high-intensity workloads over extended periods without failure. Traditional HDDs often struggle under these conditions, making SSDs the superior choice due to their faster read/write speeds and higher durability. Additionally, AI-powered security systems often require sustained, low-latency performance to prevent bottlenecks in data access, making the reliability of storage solutions critical.
Moreover, the need for secure storage solutions is increasing, with encryption and secure boot features becoming standard requirements for AI security applications. This is particularly important in sectors with strict compliance regulations, such as finance, healthcare, and critical infrastructure, where sensitive video data must be protected from unauthorised access. As AI security deployments continue to scale, storage must not only handle vast volumes of data but also integrate advanced security measures to ensure data integrity, privacy, and long-term sustainability.
“AI boxes rely on storage solutions optimised for both video and AI metadata,” Henderson explains. “High-performance SSDs are essential in ensuring the seamless operation of these devices, delivering the speed and endurance required for modern security deployments.”…
Read the full article in our April issue of Security Buyer.
