AI Intelligent Vision Recognition

From “detect” to “understand”—AI that truly reads surveillance scenes. Beyond fixed YOLO classes to semantic scene understanding.

All-scene recognition

Multimodal LLMs manage near-unlimited categories via cameras—accidents, road anomalies, obstacles, traffic, property, product inspection, and more.

Core breakthroughs

Open-vocabulary detection Unlimited classes, instant recognition, no retraining

Scene semantic understanding Understand relations and interactions among objects

Dual-layer AI synergy YOLO fast precheck + LLM deep analysis

Low false-alarm rate Semantic filter cuts false alarms to 5–10%

8 Core advantages

64 Camera channels

<50ms Response latency

30+ Event types

Real-scene intelligent recognition

From “detect” to “understand”—see how AI LLMs achieve precise recognition and semantic analysis in real surveillance

Pavement damage recognition

Automatically finds road anomalies—potholes, damage, cracks—from road cameras.

Pavement anomaly Damage recognition Auto alert

Auto-find road defects; speed inspection and maintenance response

Vehicle fire event recognition

Detects vehicle fire risk—flame, heavy smoke, abnormal burning—from video.

Fire recognition Risk early warning Emergency response

Spot high-risk fire fast, trigger linked alerts, support emergency decisions

Traditional YOLO vs AI LLM

From “detect” to “understand”—why traditional stacks fail modern smart surveillance

Dimension	Traditional YOLO system	AI Intelligent Vision Recognition
Detection ability	Can only detect “there is a car”	Recognizes “two cars collided; sedan front severely deformed”
Output content	car: 0.92, car: 0.88	Accident report: type, severity, likely causes
Response time	Needs human confirmation	Auto-triggers alerts—no human needed
False alarms	Normal side-by-side parking may false-alarm	Semantic understanding, precise recognition
Class expansion	Fixed 80 classes; needs retraining	Unlimited classes, instant recognition

Fixed classes, cannot expand Limitation

YOLO only knows training classes; new targets need weeks of data, labeling, and retraining

Knows “what is there,” not “what happened” Limit

Output is class + box + score—no relations, interactions, or abnormal behavior judgment

High false-alarm rate Issue

No context—cannot tell normal vs illegal parking, or crossing vs intrusion

Rule dependence Bottleneck

Anomaly judgment depends on hand-written rules that never cover all cases and cost to maintain

Eight core advantages

From “detect” to “understand”—a new era of AI vision recognition

Open-vocabulary detection

Recognize any target—unlimited classes, instant, no retraining

Scope: unlimited classes
New targets: 0s instant recognition
Special targets: describe with prompts

Scene semantic understanding

Know what happened; understand relations and interactions

Full scene description
Risk assessment & advice
Event class & severity judgment

Complex event recognition

Scenes YOLO cannot handle—zero-shot generalization

Wrong-way driving, illegal parking
Traffic accidents, debris
Roadwork, landslide/collapse

Natural language interaction

Flexibly customize analysis focus in natural language

Smart surveillance scene custom
Campus security scene custom
Industrial safety scene custom

Low false-alarm rate

Semantic filter cuts false alarms to 5–10%

Normal parking lot: correctly recognized
Bus-stop waiting: correctly recognized
Construction barriers: correctly recognized

Explainable AI decisions

Every alert has a full reasoning chain

Full observation record
Detailed analysis process
Clear judgment basis

Zero-shot generalization

No retraining; strong scene transfer

Day→night: auto adapt
Clear→rain/snow: auto adapt
China→abroad: use directly

Dual-layer AI synergy

YOLO fast precheck + LLM deep analysis

Efficient: only 5–10% suspicious frames
Low latency: normal scenes <50ms
Low cost: controllable GPU use

System features in detail

A complete intelligent video surveillance analytics solution

Multi-protocol video intake

USB/V4L2, RTSP, ONVIF, HTTP—compatible with Hikvision, Dahua, Uniview, and more

64-channel camera support

Multi-process 8×8 concurrent monitor, heartbeats, auto-restart, load balance

Multi-view monitoring

1/4/1+5/9/16 layouts; auto switch on alert

Event management center

Full lifecycle ACTIVE→ACKNOWLEDGED→RESOLVED with complete traceable info

Smart snapshot

Raw frame + AI report, YOLO boxes, timestamp/camera/event fully recorded

Alert notification system

SMS, email, WeChat—rules by department and event type

Technical architecture

Dual-layer AI synergy—efficient and precise

YOLO fast pre-detection

→

Anomaly pre-judge

→

Trigger decision

Normal scene (skip)

Suspicious scene (trigger)

↓

Multimodal LLM deep analysis

→

Scene understanding

→

Behavior analysis

→

Report generation

Supported models

Flexible choice for different scenes

Model type	Model name	Traits	Best for
Cloud API	GPT-4o	Strongest understanding	Complex scene analysis
Cloud API	GPT-4o-mini	High cost-performance	Daily monitoring
Cloud API	Gemini Pro Vision	Google multimodal	General analysis
Cloud API	Qwen-VL	Chinese-optimized	Domestic deploy
Local deploy	LLaVA	Open-source free	Offline environments

Camera channels

<50ms

Response latency

5-10%

False-alarm rate

30+

Event types

Start a new era of AI vision recognition

Let AI truly understand surveillance—from “detect” to “understand,” from “alarm” to “analyze”