Snis896mp4 -

| Connection | Steps | |------------|-------| | PoE | Plug an Ethernet cable from the camera’s RJ45 port directly into a PoE‑enabled switch or injector. Power and data travel on the same cable. | | DC Power (if not PoE) | Connect the 12 V DC barrel jack to the supplied power adapter, then plug the adapter into a wall outlet. | | Network | If you need a dedicated LAN, connect the Ethernet cable to a non‑PoE port on your router/switch (you’ll still need a separate power source). |

Figure 2 shows BD‑Rate savings relative to HEVC (Main). SNIS‑896MP4 achieves –45 % at VMAF = 85, outperform

Feature Proposal: “Smart Clip‑Maker + AI Highlights” for snis896mp4 snis896mp4

| Layer | Recommended Tech | |-------|-------------------| | Frontend | React + Tailwind CSS (responsive UI), FFmpeg.wasm for client‑side preview trimming. | | Backend | Python FastAPI service; GPU‑enabled inference (NVIDIA T4 or A100). | | AI Models | • Scene detection: OpenCV + PySceneDetect
• Action/Emotion: ViViT‑base + AudioSentiment (HuggingFace)
• Speech‑to‑text: OpenAI Whisper (large‑v2). | | Video Processing | FFmpeg (server‑side) for final encoding, bitrate optimization, and format conversion. | | Storage | MinIO (S3‑compatible) for raw & derived assets; Redis cache for job status. | | Queue | Celery + RabbitMQ for asynchronous processing. | | Analytics | ClickHouse for event storage; Grafana dashboards. |

| Scenario | Recommended Settings | |----------|----------------------| | Home security (continuous recording) | 4 MP @ 15 fps, H.265, constant loop on SD, motion alerts via email. | | Retail shop (people counting) | Enable analytics → Object Counting, set line‑crossing at entrance, store data on NVR. | | Warehouse (low‑light) | Enable IR LEDs, set IR cut filter off, use 8 MP @ 10 fps, enable night‑mode auto‑switch. | | Remote monitoring (mobile) | Sub‑stream 1080p @ 5 fps, H.264, stream over cellular VPN, disable audio to save bandwidth. | | Connection | Steps | |------------|-------| | PoE

The MPEG‑4 Part 14 (ISO‑BMFF) container is extended with two custom boxes:

| Box | Purpose | Contents | |-----|---------|----------| | snis (base) | Base‑layer header | Frame dimensions, MFE config, C‑EAM table | | snis (enh) | Enhancement‑layer header | Offsets to L1 latents, scaling factors | | Layer | Recommended Tech | |-------|-------------------| |

Both boxes are placed before the standard mdat atom, enabling progressive fetching: a player can download the base snis and mdat for a low‑quality preview, then request the enhancement snis and additional mdat bytes when bandwidth permits.

Both datasets are split 80 % train / 10 % validation / 10 % test. All frames are converted to YUV‑420 and normalized to ([0,1]).