| System |
| Main processor | 2 Intel Xeon Silver 4114T |
| Operating system | CentOS Linux release 7.4.1708 (Core) |
| Intelligent card | 1 Dahua DH-AIX3000 self-researched standard half-height intelligent card |
| Memory | 8 16GB DDR4 memory, maximum 24 slots. |
| Disk | 4 3.5” 4T disks which can be extended to maximum 32T (each disk is 4T), and maximum 8 slots.
7.2K RPM SATA 6Gbps 512n 3.5” |
| Structuring Intelligent Analysis |
| Target classification | Classify targets, including humans, motor vehicles and non-motor vehicles. Make intelligent structured analysis on the live video, historical video (supported by platform) and the offline uploaded video files, and then abstract structured information about the moving targets |
| Motor vehicle detection | Detect vehicles by vehicle type, color, brand, model, year, plate number, and plate type. Detect sunshield, safety belt, phone call and inside decorations (pendant and tissue box). |
| Non-motor vehicle detection | Detect non-motor vehicles by driver's gender, age, hair style, wearing (hat), belongings (umbrella, backpack and handbag), top clothes, top color, and non-motor vehicle type. |
| Pedestrian detection | Detect pedestrians by gender, age, hair style, wearing (hat), belongings (umbrella, backpack and handbag), top clothes, top color, bottom clothes, and bottom color. |
| Region detection | Support detection area and exclusion area settings. |
| Real-time display | Display the analysis results in real time, and display humans, motor vehicles and non-motor vehicles in real time with tracking boxes. |
| Search by attribute | Support intelligent search of humans, motor vehicles and non-motor vehicles according to their attributes. |
| Search by picture | Select one picture manually, filter by time and channel, compare with historical data, thus find the qualified humans, motor vehicles and non-motor vehicles, and arrange them according to the similarity. |
| Target comparison | Compare 1V1 target quickly, and return target similarity in two pictures. |
| Video recording task | Make intelligent structured analysis on the historical video (supported by platform), and then abstract structured information about the moving targets. And then, search the analysis results by pictures and attributes. |
| Local task | Make intelligent structured analysis on the offline uploaded local video files, and abstract structured information about the moving targets. And then, search the analysis results by pictures and attributes. |
| Deploy attributes | Platforms |
| Structuring picture storage | Local storage or external cloud storage. |
| Display tracks on the map | Platforms |
| Computing node cluster | Support cluster and management of 2-XX structured analysis servers. |
| Structuring Intelligent Analysis Attribute Dictionary |
| Pedestrians | Age: Child, adult, senior citizen
Backpack: Yes, no
Umbrella: Yes, no
Handbag: Yes, no
Top color: Black, white, gray, red, green, blue, yellow, orange, purple, pink and brown. 11 colors in total.
Bottom color: Black, white, gray, red, green, blue, yellow, orange, purple, pink and brown. 11 colors in total.
Top style: Short sleeves, long sleeves
Bottom style: Shorts, pants
Gender: Male, female
Hat: No hat, hat, helmet
Hair style: Short hair, long hair, ponytail, updo, head covered. |
| Non-motorized vehicles | Age: Child, adult, senior citizen
Backpack: Yes, no
Umbrella: Yes, no
Handbag: Yes, no
Top color: Black, white, gray, red, green, blue, yellow, orange, purple, pink and brown. 11 colors in total.
Top style: Short sleeves, long sleeves
Gender: Male, female
Hat: No hat, hat, helmet
Hair style: Short hair, long hair, ponytail, updo, head covered.
Non-motor vehicle type: Two-wheeled vehicle, tricycle |
| Motor vehicles | Vehicle color: Gray, black, white, silver gray, blue, green, purple, red, orange, pink, brown and yellow. 12 colors in total.
At least 86 logos and brands in the front can be recognized. At least 55 logos and brands in the rear can be recognized. Vehicle type: Passenger vehicle, heavy truck, medium truck, car, van, light truck, medium bus, SUV, MPV, bus, pickup and minicar
Attributes inside the window: Pendant, tissue box, sunshield, telephone call, and safety belt.
Number plate color: Blue, yellow, white, green and black.
Recognize the number plates of 47 countries in the world. |
| Structuring Analysis Performance |
| Structuring analysis performance | Each intelligent card can analyze moving targets in 20-channel 1080p live video or 40 pictures/second. One device supports maximum 6 intelligent cards. |
| Search by picture performance | Compare 10 million pictures in the passenger database quickly. During hot search, operator time is 4 million pictures/second, and total search time is no more than 5 s. |
| Region detection quantity | Support 1 detection region in one image, and at least 10 exclusion regions in one detection region. |
| Moving target detection rate | With normal light in the day and normal fill light at night, resolution ≥40 × 80, clear, distinguishable and no blocking:
Detection rate of pedestrians: ≥95%;
Detection rate of non-motor vehicles: ≥95%;
With normal light in the day and normal fill light at night, resolution ≥120 × 120, clear, distinguishable and no blocking:
Detection rate of motor vehicles: ≥95%. |
| Recognition accuracy of pedestrians | With normal light in the day and normal fill light at night, resolution ≥80×160, clear and distinguishable pedestrians:
Gender accuracy: ≥90%;
Hair style accuracy: ≥85%;
Clothes style and color accuracy: ≥85%;
Wearing accuracy: ≥80%;
Belongings accuracy: ≥80%. |
| Recognition accuracy of non-motor vehicles | With normal light in the day and normal fill light at night, resolution ≥80×160, clear and distinguishable non-motor vehicles:
Gender accuracy: ≥90%;
Hair style accuracy: ≥90%;
Clothes style and color accuracy: ≥90%;
Wearing accuracy: ≥80%;
Belongings accuracy: ≥70%;
Non-motor vehicle type accuracy: ≥90%. |
| Recognition accuracy of motor vehicles | With normal light in the day and normal fill light at night, resolution ≥240×240, clear, distinguishable, no blocking motor vehicles whose inclined angle is no more than 25°:
Motor vehicle type accuracy: ≥92%;
Motor vehicle color accuracy: ≥90%;
Motor vehicle brand accuracy: ≥85%;
Driver and passengers’ safety belt accuracy: ≥95%;
Driver and passengers’ phone call accuracy: ≥90%;
With normal light in the day and normal fill light at night, resolution width ≥120, clear, distinguishable number plate:
Number plate accuracy: ≥96%;
Number plate color accuracy: ≥90%. |
| Port |
| Network port | Two 10000/1000Mb self-adaptive network ports |
| USB port | 2 front USB3.0 ports and 3 rear USB3.0 ports |
| VGA port | 2 VGA ports |
| Other ports | 1 RJ-45 management network port |
| General parameter |
| Power supply mode | 100–127V/200–240V, 50/60Hz, 10A/5A |
| Power redundancy | Dual power redundancy |
| Power consumption | ≤ 800W |
| Operating temperature | 10°C to 35°C (50°F to 95°F) |
| Operating humidity | 35%–80% RH, maximum relative humidity during operation is 90% RH (40°C). |
| Storage temperature | -40°C to 60°C (-40°F to 140°F) |
| Storage humidity | 20%–93%RH |
| Gross weight | 35 kg (77.2 lb) |
| Net weight | 27.5 kg (60.6 lb) |
| Dimensions | 87.00 mm × 447.60 mm × 735.60 mm (3.43'' × 17.62'' × 28.96'') |
| Package dimensions | 273.00 mm × 754.00 mm × 1069.00 mm (10.75'' × 29.68'' × 42.09'') |
| Mounting | Standard 19'' rack installation with guide rail. |
