How Edge AI is Transforming Video Surveillance Performance
How AI at the Edge Is Transforming Video Surveillance Artificial intelligence has been part of video surveillance for years. What’s changed is where that intelligence lives. As edge hardware becomes more capable, AI processing is moving closer to where video originates—a shift that’s reshaping system performance, resilience, and the overall user experience. Shifting AI to the edge reduces reliance on centralized infrastructure. Instead of streaming all video to a server or cloud for analysis, cameras can detect events, generate metadata, and surface insights in real time. This lowers latency, reduces bandwidth consumption, and keeps systems operational even when [...]
The Power of Hybrid Storage Strategies
Storage has traditionally been one of the most rigid parts of video surveillance. For many integrators, legacy architectures forced a choice between local retention or centralized storage - a decision that often led to oversizing, unnecessary cost, or systems that were harder to manage than they needed to be. Hybrid storage strategies change that. In modern edge‑to‑cloud architectures, storage becomes policy‑driven rather than fixed. Local storage at the edge provides immediate resilience and fast access, ensuring continuous recording even during network disruptions. Cloud storage then supports long‑term retention, centralized visibility, and regulatory compliance - without the burden of oversized [...]
How AI at the Edge Is Transforming Video Surveillance Artificial intelligence has been part of video surveillance for years. What’s changed is where that intelligence lives. As edge [...]
Storage has traditionally been one of the most rigid parts of video surveillance. For many integrators, legacy architectures forced a choice between local retention or centralized storage - a [...]
