Your CCTV Isn't Obsolete—It's Just Waiting for a Brain
Introduction: The Hardware Graveyard
Walk into any large enterprise, and you'll likely find a "hardware graveyard" hidden in the server room: racks of expensive NVRs and boxes of legacy cameras that were state-of-the-art only five years ago.
Most companies have millions of dollars sunk into their existing CCTV infrastructure. When they want to move into the world of AI—for person detection, number plate recognition, or behavioural analytics—they are often told the same thing: "Rip it all out and start over."
We disagree. At [Mikshi], we believe software is the upgrade, not hardware. You shouldn't have to replace a perfectly functional camera just to make it smarter.
The Universal Language of Video (RTSP & ONVIF)
The biggest barrier to digital transformation in security is brand "lock-in." Historically, different manufacturers used proprietary languages, making it almost impossible to build a unified intelligent system.
We use two industry standards to create a "universal translator" for your network:
ONVIF: This is the handshake. It allows our software to discover cameras on your network and understand their capabilities automatically.
RTSP (Real-Time Streaming Protocol): This is the pipeline. It is the gold standard for "pulling" a live video feed from almost any IP camera (Hik-vision, Dahua, Axis, etc.) and bringing it into our AI environment.
The Challenge: The Codec Mess
Even with a universal protocol, the "language" inside the stream varies. Some older cameras use H.264, while newer ones use H.265 (HEVC). Our integration layer handles this complexity in the background, normalising these chaotic streams so the AI receives a consistent, high-quality image every time.
The Ingestion Pipeline (The AI Translator)
Connecting to a camera is only half the battle. The real magic happens within [Mikshi]'s Media Server, which acts as a high-performance bridge between your raw network traffic and our neural networks.
How the Pipeline Works:
Packet Buffer & De-jittering: Network traffic can be "noisy." Our pipeline smooths out inconsistent bitrates to ensure the AI gets a continuous, frame-perfect stream.
Hardware-Accelerated Decoding: Instead of taxing the CPU, we leverage GPU-accelerated decoding (NVDEC/QuickSync). This allows the system to unpack streams in milliseconds.
Dynamic Rescaling: AI models require specific input dimensions. Our pipeline performs real-time aspect-ratio correction, ensuring cameras of different brands are processed with equal precision.
| Feature | Supported Standards | AI Optimization |
|---|---|---|
| Video Codecs | H.264 (AVC), H.265 (HEVC), MJPEG | Auto-detected & hardware-decoded |
| Protocols | RTSP, ONVIF | Sub-300ms glass-to-glass latency |
| Resolutions | 480p up to 1440p | Real-time bilinear downscaling |
| Frame Rates | 5 FPS to 60 FPS | VFR stabilisation |
Scalability: Enterprise-Grade Performance
We avoid the "performance wall" through Multi-Threading: every camera feed is isolated into its own execution thread. If one camera loses connection, it doesn't interrupt the rest. Our architecture allows for linear scaling—as you grow, you simply add "worker nodes" to the cluster.
Section 3: The Honesty Check: What We Can't Fix
We believe in "AI realism." While our software provides a massive intelligence boost, it isn't magic.
If your existing camera is a decade-old 720p model with a smudged lens, we can still run AI on it, but we cannot "zoom and enhance" it into a 4K image. Our goal is to maximize the value of your current hardware, but the results will always be defined by the quality of the optical data we receive.
Conclusion: Your Infrastructure Needs a Brain, Not a Replacement
Your current security infrastructure isn't a relic of the past; it's a massive data source that is currently underutilised. By using [Mikshi], you are turning "dumb" glass into an intelligent sensor network.
Stop Guessing. Start Seeing. Don't let your existing hardware sit idle. See exactly how [Mikshi] can turn your current CCTV feeds into an intelligent security powerhouse.
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