As AI-powered video analytics becomes increasingly accessible, many businesses face a crucial decision: Should video data be processed in the cloud or at the edge? Both architectures offer benefits—but understanding the differences is essential for choosing the right solution for your security and surveillance needs.
Cloud Video Analysis: Scalability Meets Limitations
Cloud-based video analytics typically involves uploading raw video footage from cameras to a centralized data center for processing. This model benefits from massive compute power and is easy to scale across locations.
Pros:
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Centralized data access and management
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Easier integration with cloud-based dashboards and AI models
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Scalable infrastructure—pay as you grow
Cons:
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High bandwidth usage: Uploading continuous video streams can quickly saturate internet connections, especially with multiple cameras.
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Latency issues: Delays in processing and sending alerts reduce the value of real-time insights.
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Privacy & compliance risks: Regulatory requirements like Singapore’s PDPA may restrict transmitting or storing sensitive footage in the cloud.
Edge Video Analysis: Real-Time Intelligence at the Source
Edge analytics processes video streams locally, using AI-enabled hardware like the NVIDIA Jetson platform. Instead of sending full video to the cloud, only important event data or snapshots are transmitted—minimizing bandwidth and latency.
Pros:
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Real-time detection: Get instant alerts with minimal delay—crucial for security incidents.
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Reduced bandwidth costs: Only snapshots or event metadata are sent to the cloud or server.
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Improved privacy: Video stays on-site, supporting compliance with PDPA and other data protection laws.
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Offline capability: Even without internet, edge devices can continue operating autonomously.
Cons:
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Limited hardware resources may constrain complex AI workloads
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May require more technical setup at each site
Why Edge is the Smarter Choice for CCTV Enhancement
For most CCTV installations—especially in security, construction, and smart building environments—edge-based analytics delivers the best of both worlds: real-time response and efficient resource usage.
At Grep Tech, our GT-AiVision system is built around this principle. Powered by NVIDIA Jetson edge computing, it works seamlessly with your existing RTSP cameras, performs AI video analysis on-site, and sends instant alerts via Telegram—without requiring cloud uploads or heavy bandwidth.
Whether you’re detecting unauthorized access, counting people, or monitoring restricted zones, GT-AiVision helps you “let AI do the watching”, so your team can focus on the response.
Want to learn more about how edge video analytics can work for your business?