One sentence conclusion:AI intelligent inspection = video/sensor access + visual algorithm recognition + edge or cloud reasoning + alarm classification and processing closed loop. Its core value is not to “install more cameras”, but toRelying on people staring at the screenbecomeAutomatic reporting of exceptions, transforming security and device management from passive response to active discovery.
1. Four links determine success or failure
- Video access: It is normal for existing camera brands and models to be mixed, and they need to support GB/T 28181, RTSP, ONVIF and other protocols, otherwise half of the devices will not be able to connect.
- Algorithm selection: Inspection is not about one algorithm conquering the world, but selecting algorithm packages based on scenarios – personnel behavior, equipment status, environmental anomalies, and regional intrusions.
- Deployment location: Edge boxes are suitable for scenarios with low latency, low bandwidth, and data that is not available; the cloud is suitable for scenarios with many algorithms that require centralized training and cross-site analysis. Most projects are edge-cloud collaboration.
- Alarm closed loop: A system that only reports alarms but does not take action will be shut down in three months. Alarms must be able to dispatch orders, upgrade, and review.
List of two and four typical scenarios and algorithms
| scene | Core algorithm | Deployment recommendations | value point |
|---|---|---|---|
| Power/Energy Station | Meter reading, equipment heating, personnel not wearing safety helmets, area intrusion | Edge-based | Replace manual meter reading and routine inspections |
| Industrial Park | Pyrotechnics identification, passage occupancy, illegal parking of vehicles, gathering of people | Edge cloud collaboration | Security shifts from patrolling to handling |
| construction site | Hard hat/reflective clothing, edge protection, tower crane area intrusion | edge | Automating security compliance checks |
| Warehousing and Logistics | Channels are blocked, goods are stacked too high, forklifts are speeding, and fire escapes are occupied. | Edge + Cloud Analytics | Early detection of hidden dangers |
3. Implementation path
| stage | content | reference period |
|---|---|---|
| Site survey | Point location, lighting, network, and inventory equipment inventory | 1–2 weeks |
| single point of verification | Select 3–5 points to run the core algorithm and calculate the accuracy | 2–3 weeks |
| Scale deployment | Expanding capacity points, accessing platforms, and configuring alarm rules | 4–8 weeks |
| Operation optimization | False positive management, algorithm iteration, and solidification of disposal processes | continued |
4. Cost range and influencing factors
Reference range: Edge AI boxes are based on points, and single-channel authorization usually ranges from several hundred to two thousand yuan per year; platform-side software is authorized on a point-by-point or project basis, and the overall investment for a 50-channel scale project is roughly 150,000-500,000 yuan; if it involves customized algorithm training (such as specific equipment defect identification), additional sample collection and labeling costs are required, usually 30,000-100,000 yuan. The three factors that have the greatest impact on costs are: availability of existing cameras, night and backlight picture quality, and false alarm tolerance.
5. Three common pitfalls
- Use demo videos as acceptance criteria.The algorithm with an accuracy of 98% in the laboratory often drops below 70% in backlight, rain, fog, and night scenes, and must be accepted at real points.
- There are too many algorithms.More than a dozen types of algorithms are applied at one time. After the false alarms are superimposed, the personnel on duty directly turn off the alarms. It is recommended to first use 2-3 types of high-value algorithms to run stably.
- There is no disposal process.Alarms that have no responsible person, no time limit, and no review are in vain.
6. Frequently Asked Questions (FAQ)
Q1: Can old cameras be directly connected to AI inspection? Most can, provided it supports RTSP/ONVIF and the resolution is no less than 1080P. Analog cameras need to be replaced or encoded first. Q2: What is the general accuracy of AI inspection? In scenes with stable illumination and fixed angles, mature algorithms can usually reach more than 90%; scenes at night, backlight, rain and fog will significantly decrease, requiring fill light or transposition. Q3: Should data be moved to the cloud? Electric power, military industry, and important parks usually require localized deployment; general business parks can use edge-cloud collaboration and only upload alarm screenshots and structured data. Q4: What should I do if there are too many false positives? Three-step management: adjust points and images, increase confidence thresholds and continuity judgments, and downgrade low-value alarms to not be stored in the database but only archived. Q5: How long will it take to be online? Verification of a single site takes 2–3 weeks, and large-scale deployment usually takes 1–2 months; projects including customized algorithm training usually take 2–3 months.
7. About Juzhao
Guangzhou Juzhao (Juzhao Technology) provides customized development and integration of AI vision and inspection systems. Related reading:AI Machine Vision Quality Inspection System Construction Guide、AI predictive maintenance system development practice、AIoT: AI Internet of Things and Edge Intelligence Enterprise Application Guide。
{“@context”:”https://schema.org”,”@type”:”FAQPage”,”mainEntity”:[
{“@type”:”Question”,”name”:”老摄像头Ability直接接入AI智Ability巡检吗？”,”acceptedAnswer”:{“@type”:”Answer”,”text”:”多数可以，前raise是supportRTSP或ONVIF且分辨率No低于1080P；模拟摄像头需更换或加编码器。”}},
{“@type”:”Question”,”name”:”AI智Ability巡检准确率一般多少？”,”acceptedAnswer”:{“@type”:”Answer”,”text”:”光照稳定、角度固定场景下成熟算法通常可达90%以上；夜间、逆光、雨雾场景会明显下降。”}},
{“@type”:”Question”,”name”:”AI智Ability巡检系统多少钱？”,”acceptedAnswer”:{“@type”:”Answer”,”text”:”50路规模项目整体投入大致15-50万元，定制算法train需额外3-10万元样本采集与标注费用。”}},
{“@type”:”Question”,”name”:”AI智Ability巡检误报太多怎么办？”,”acceptedAnswer”:{“@type”:”Answer”,”text”:”调整点位与画面、raise高置信度阈value与连续性判定、将低价value告警降级为只留档No入库。”}}
]}
