8MP Turret Camera With Deep
Learning-based Image Analysis,
Ultra Low Light, Active Deterrence
Face Detection/Recognition,
License Plate Detection/Recognition,
Object Verification, Sound Detection,
2.8mm Fixed Lens (110°), 20m LED,
Built-in Microphone and Speaker.
KEY FEATURES
- Resolution: 8MP (3840x2160).
- Lens: FixedLens, f=2.8mm/F1.0 (110°).
- Min. Illumination: 0.0007lux.
- White LED illuminator, range up to 20m.
- 24/7 All-weather Color Images.
- Audio & Light alarm, Active deterrence.
- Two-way audio.
- Built-in microphone.
- Built-in speaker.
- AI Analytics based on deep learning:
Face Detection/Recognition,
AI Object Classification (Distinguishes Objects Such as Pedestrians and Vehicles) Perimeter Intrusion,
Line Crossing, Cross Counting, Heat Map, Crowd Density, Queue Length, License Plate Detection/Recognition, Rare Sound Detection, Intrusion, Object Detection,
Region Entrance, Region Exiting.
- Supports backlight compensation, strong light suppression, 3D digital noise reduction, suitable for different video environments.
- MicroSD card support (256Gb.
- ONVIF (Profile S/G/T/M).
- IP67 Protection.
- Two way power - when connected to a PoE switch,
it allows to power the low power receiver from the camera's power socket.
Face Detection/Recognition, AI Object Classification (Distinguishes Objects Such as Pedestrians and Vehicles) Perimeter Intrusion, Line Crossing, Cross Counting, Heat Map, Crowd Density, Queue Length, License Plate Detection/Recognition, Rare Sound Detection, Intrusion, Object Detection,
Region Entrance, Region Exiting.
it allows to power the low power receiver from the camera's power socket.
COMPATIBILITY
FUNCTIONS
DESCRIPTION
Equipped with a 2.8mm fixed lens, this 8MP turret camera is designed for short-distance surveillance (up to 20m) in indoor and outdoor scenarios.
With its hybrid capability, the white LED will enlighten the scene when humans being detected for full color image even in dark scenarios. The camera
offers outstanding Analytics, which can perform human and vehicle recognition. With various detection rules and
triggers. This model complies with NDAA demands. With its outstanding performance,
reliability, and affordable price, the camera is the perfect solution for any advance IP installation.
Equipped with a 2.8mm fixed lens, this 8MP turret camera is designed for short-distance surveillance (up to 20m) in indoor and outdoor scenarios. With its hybrid capability, the white LED will enlighten the scene when humans being detected for full color image even in dark scenarios. The camera offers outstanding Analytics, which can perform human and vehicle recognition. With various detection rules and triggers. This model complies with NDAA demands. With its outstanding performance, reliability, and affordable price, the camera is the perfect solution for any advance IP installation.
FUNCTIONALITIES
Active DeterrenceActive deterrence involves taking steps to keep intruders away from an area by signaling presence and alertness. When the camera detects something, it can light up, flash, or emit warning sounds or voice messages (the number and type of deterrent features vary by camera model, some even have red and blue flashing lights). The feature is designed to protect the area, deter intruders from moving forward, and scare them away without the need for direct intervention.
Cost saving:
By preventing breakage and damage, active deterrence can help reduce the costs of repairs and extra security.
Application example:
- Business area.
- Warehouses.
- Construction sites.
Sound Detection (Rare Sound)The sound detection function analyzes the sound level around the camera, such as dog barking, gunshots, breaking glass, and children screaming. When the sound level exceeds the set limit, the camera's video recording is activated and/or notifications are sent, enabling a quick response to potentially dangerous situations. If the sound level becomes too low, the function can also trigger a reaction. With this function, the camera becomes not only an observation tool, but also a way to monitor abnormal sounds in the environment.
Application example:
- Business area.
- Warehouses.
- Construction sites.
License Plate Detection andRecognitionLicense plate detection and recognition is a technology that uses cameras to automatically read and identify vehicle license plates. The technology is used in areas such as traffic monitoring, toll collection systems, and to find stolen or wanted vehicles. By sending the recognition information to a storage device (NVR), the response capabilities of the NVR can be expanded. Thanks to advanced algorithms, the recognition works effectively regardless of the time of day or weather conditions.
Application example:
- Strategic locations at entrances, for example.
- Traffic control is about monitoring and regulating traffic flow to ensure safety and efficiency on the roads.
- Tolls are fees charged for using certain roads, bridges or tunnels. The purpose is often to finance maintenance and operation or to reduce traffic congestion in certain areas.
- Logistics and transportation are about planning, organizing and implementing efficient flows of goods, services and information from one place to another.
Object ClassificationImage analysis based on deep learning enables the camera to see and identify what is happening in the image and categorize the objects. Instead of just recording raw video data, the system can automatically distinguish and classify different objects. The algorithm allows the camera to recognize shapes such as people, cars and bicycles/motorcycles, even if they make up as little as 1% of the image. The efficient analysis methods enable simultaneous classification and monitoring of up to 32 different objects.
Application example:
- Area surveillance involves monitoring and protecting a specific area, often using cameras, security personnel, or other technological solutions, to promote safety and security.
- Shops.
- Industrial environments are about factories, machines and production facilities where goods are manufactured or processed..
- Traffic control is about monitoring and regulating traffic to ensure safety and smooth operation on the roads.
- Public places.
Cross CountingImage analysis based on deep learning enables counting objects with recognizable shapes, such as human, cars, and bicycles/motorcycles, that pass a virtual line. The camera can then display the number of these objects in the image.
Line CrossingImage analysis based on deep learning makes it possible to trigger a local alarm, send an email, activate a relay or send a push message to the mobile application when an object (person, car or bicycle/motorcycle) crosses a predefined line (maximum four lines per camera).
Application example:
- Protection of the perimeter of the object.
IntrusionImage analysis based on deep learning enables triggering a local alarm, sending an email, activating a relay or sending a push message to the mobile app when an object (person, car or bicycle/motorcycle) passes the defined detection zone.
Application example:
- Protection of the perimeter of the object.
- Protection of strategically important objects is an important aspect of ensuring security and continuity of critical operations.
Heat MapImage analysis based on deep learning enables visual representation of activity captured by a security camera, where color gradients are used to show areas of high or low activity. Typically, warmer colors like red or orange represent areas of more activity, while cooler colors like blue or green show areas of less activity. A perfect tool for analyzing customer traffic flow, for example in a store.
Here's how it works:
Data collection:
Surveillance cameras with heat map capabilities record data, movements and activities within their field of view.
Generation of heat maps:
The processed data is then applied to the camera's live or recorded images in the form of a heat map.
Color codes:
Warmer colors show areas of higher activity, while cooler colors show areas of lower activity.
Application example:
- Retail, analyze customer traffic flow.
- Identify which products are popular and improve the store layout to maximize efficiency.
- Monitor pedestrian density in public areas.
- For example, airports or train stations.
Queue Length DetectionImage analysis based on deep learning enables the camera to analyze and determine the length of a queue, often in situations where people are waiting. The camera can activate an alarm when the queue length exceeds a certain number of people or when the service time exceeds a certain limit.
Some ways to implement queue length detection:
Video analysis:
Our NVRs analyze the video stream and identify queues based on movement, density and other visual factors.
AI-based detection:
Advanced AI algorithms are used to automatically identify and measure queue lengths in real time, providing more precise and reliable results.
Object tracking:
Using object tracking technology, the system can monitor individuals in the queue and thus measure their length.
Application example:
- Retail
- By keeping track of queue lengths, you can adjust resources and staff to reduce waiting times at checkouts.
- By reducing queues, you can increase both customer satisfaction and service efficiency.
Crowd Density DetectionImage analytics based on deep learning enables cameras to analyze crowds through video analytics and estimate the number of people in a specific area. The technology can be used for various purposes, such as security, crowd management, and customer behavior analysis.
Some ways to implement queue length detection:
Video analysis:
Our NVRs analyze the video stream and identify crowds based on movement, density and other visual factors.
Counting and density estimation:
These algorithms can accurately count the number of people in a scene and calculate the density (number of people per unit area).
Real-time data:
The system delivers real-time information about crowd levels, making it possible to act quickly in the event of changing conditions.
Warnings and messages:
The system can be set to activate alerts, such as flashing lights or alarms, when the population density exceeds a predefined limit.
Application example:
- Detect and track potential threats, such as suspicious behavior or prolonged stays in places with large crowds.
- Optimize people flow, reduce congestion, and improve safety in places like arenas, concerts, and shopping malls.
- Analysis of customer behavior, insights into customer movements, identification of key areas and optimization of store layouts.
- Traffic management involves adjusting traffic signal times and redirecting traffic based on information about traffic density.
- Increase safety by monitoring crowds and avoiding crowding in potentially risky situations.
- Store optimization is about store owners being able to use crowd density data to optimize product placement, staff planning, and the entire shopping experience.
Face Detection & RecognitionImage analysis based on deep learning makes it possible to use computer vision and machine learning to detect human faces within the camera's field of view. When a face is detected, the camera can trigger an alarm or, send data that allows identification of the detected face.
Image analysis:
Cameras use algorithms to analyze video streams and detect patterns that resemble human facial features.
Feature extraction:
These algorithms identify key features such as eyes, nose, and mouth to determine whether a face is present.
Notifications:
Once a face is recognized, the system can be set to send a notification or record a video in response.
Face detection:
Focuses on identifying the presence of a face, without necessarily determining who it belongs to.
Face recognition:
Aims to identify a specific person by matching detected faces with a database of known faces.
Application example:
- Facial detection can be used to send alerts when someone enters a restricted area.
- Facial recognition can be used to send alerts when a predefined face is detected by the camera.
- It can improve traditional motion detection by focusing on faces rather than any other movement in the scene.
- Data collection, even if not used to identify individuals, can still be used to track pedestrian traffic and overall activity in a monitored area.
Smart IR Via HardwareThe Smart IR feature allows the camera to automatically adjust the intensity of the infrared light depending on the distance to the subject. This prevents the subject from being overexposed and washed out at close range, while ensuring sufficient illumination at longer distances.
More detailed description:
Traditionel IR:
Regular IR cameras have a fixed IR illumination, which can cause subjects close to the camera to be overexposed and difficult to distinguish, while subjects further away may be insufficiently illuminated.
Smart IR:
With Smart IR technology, the camera automatically adjusts the strength of the IR light. When an object gets closer to the camera, the IR light is reduced, and when the object is further away, it is increased.
Advantages:
This provides clearer and more detailed images in the dark, both near and far, improving surveillance quality.
Application example:
- In environments where people and objects can come close to the camera, such as corridors.
- Close-range vehicle monitoring.
RxCamViewThe RXCamView mobile app makes it easy to remotely monitor SafeVision's camera system directly from a smartphone with Android or iOS. Basic settings for the recorder and cameras, as well as PTZ control, can be managed via the phone. The app allows you to connect to the recorder via P2P with a QR code, without additional network configuration. In addition, you can receive push notifications for selected alarm events.
Application example:
- Line rossing.
- Intrusion.
- Sabotage.
Supports the HTML5 StandardThe camera uses HTML5 (Hypertext Markup Language 5) to display images in the browser. This allows configuration and streaming from the camera not only via Internet Explorer but also in other popular browsers such as Opera, Firefox, Edge or Chrome. Thanks to HTML5, the user can securely and conveniently connect to the camera. The high performance of the HTML5 protocol allows high-definition video viewing without delay and with moderate use of computer resources.
Two Way PowerThe two-way power function allows the camera's DC connector (12V) to be used as an output when the camera is powered via PoE. With a maximum output power of 3W, this solution is best suited for active microphones, especially for cameras with audio input.
Camera ConfigurationFrom NVRThe recorder in combination with the cameras, in addition to the setting of basic parameters such as contrast and brightness, allows for a significantly more advanced level of camera settings. Depending on the functionality of the camera, this is possible from the recorder level.
Application example:
- Adjust the camera's network settings.
- Stream parameters.
- Adjust zoom and focus on a camera with a motorized zoom lens.
- Activate and set the image analysis function.
SD Card SlotThe camera has an SD card slot that allows for local recording of video material, making it resilient to interruptions in data transfer between the camera and the recorder. Saved material can be easily played back and exported directly via the browser.
H.265+H.265+ is an improved version of the H.265 (HEVC) video compression standard, designed to increase efficiency and reduce bandwidth and storage requirements, especially for surveillance video. This smart algorithm, developed by Hikvision, optimizes the encoding process to lower the bit rate while maintaining video quality at the same level as the original H.265.
H.265+ is based on three main techniques:
Predictive coding:
This technology analyzes and predicts changes in the video image, reducing the amount of data that needs to be recoded for each frame.
Noice reduction:
By reducing image noise, H.265+ can compress video more efficiently without losing important information.
Flexible bitrate control:
H.265+ can dynamically adapt the bitrate to the video content, ensuring that important information is compressed efficiently while less important parts are compressed more aggressively.
Cost saving:
By preventing breakage and damage, active deterrence can help reduce the costs of repairs and extra security.
Application example:
- Business area.
- Warehouses.
- Construction sites.
The sound detection function analyzes the sound level around the camera, such as dog barking, gunshots, breaking glass, and children screaming. When the sound level exceeds the set limit, the camera's video recording is activated and/or notifications are sent, enabling a quick response to potentially dangerous situations. If the sound level becomes too low, the function can also trigger a reaction. With this function, the camera becomes not only an observation tool, but also a way to monitor abnormal sounds in the environment.
Application example:
- Business area.
- Warehouses.
- Construction sites.
License plate detection and recognition is a technology that uses cameras to automatically read and identify vehicle license plates. The technology is used in areas such as traffic monitoring, toll collection systems, and to find stolen or wanted vehicles. By sending the recognition information to a storage device (NVR), the response capabilities of the NVR can be expanded. Thanks to advanced algorithms, the recognition works effectively regardless of the time of day or weather conditions.
Application example:
- Strategic locations at entrances, for example.
- Traffic control is about monitoring and regulating traffic flow to ensure safety and efficiency on the roads.
- Tolls are fees charged for using certain roads, bridges or tunnels. The purpose is often to finance maintenance and operation or to reduce traffic congestion in certain areas.
- Logistics and transportation are about planning, organizing and implementing efficient flows of goods, services and information from one place to another.
Image analysis based on deep learning enables the camera to see and identify what is happening in the image and categorize the objects. Instead of just recording raw video data, the system can automatically distinguish and classify different objects. The algorithm allows the camera to recognize shapes such as people, cars and bicycles/motorcycles, even if they make up as little as 1% of the image. The efficient analysis methods enable simultaneous classification and monitoring of up to 32 different objects.
Application example:
- Area surveillance involves monitoring and protecting a specific area, often using cameras, security personnel, or other technological solutions, to promote safety and security.
- Shops.
- Industrial environments are about factories, machines and production facilities where goods are manufactured or processed..
- Traffic control is about monitoring and regulating traffic to ensure safety and smooth operation on the roads.
- Public places.
Image analysis based on deep learning enables counting objects with recognizable shapes, such as human, cars, and bicycles/motorcycles, that pass a virtual line. The camera can then display the number of these objects in the image.
Image analysis based on deep learning makes it possible to trigger a local alarm, send an email, activate a relay or send a push message to the mobile application when an object (person, car or bicycle/motorcycle) crosses a predefined line (maximum four lines per camera).
Application example:
- Protection of the perimeter of the object.
Image analysis based on deep learning enables triggering a local alarm, sending an email, activating a relay or sending a push message to the mobile app when an object (person, car or bicycle/motorcycle) passes the defined detection zone.
Application example:
- Protection of the perimeter of the object.
- Protection of strategically important objects is an important aspect of ensuring security and continuity of critical operations.
Image analysis based on deep learning enables visual representation of activity captured by a security camera, where color gradients are used to show areas of high or low activity. Typically, warmer colors like red or orange represent areas of more activity, while cooler colors like blue or green show areas of less activity. A perfect tool for analyzing customer traffic flow, for example in a store.
Here's how it works:
Data collection:
Surveillance cameras with heat map capabilities record data, movements and activities within their field of view.
Generation of heat maps:
The processed data is then applied to the camera's live or recorded images in the form of a heat map.
Color codes:
Warmer colors show areas of higher activity, while cooler colors show areas of lower activity.
Application example:
- Retail, analyze customer traffic flow.
- Identify which products are popular and improve the store layout to maximize efficiency.
- Monitor pedestrian density in public areas.
- For example, airports or train stations.
Image analysis based on deep learning enables the camera to analyze and determine the length of a queue, often in situations where people are waiting. The camera can activate an alarm when the queue length exceeds a certain number of people or when the service time exceeds a certain limit.
Some ways to implement queue length detection:
Video analysis:
Our NVRs analyze the video stream and identify queues based on movement, density and other visual factors.
AI-based detection:
Advanced AI algorithms are used to automatically identify and measure queue lengths in real time, providing more precise and reliable results.
Object tracking:
Using object tracking technology, the system can monitor individuals in the queue and thus measure their length.
Application example:
- Retail
- By keeping track of queue lengths, you can adjust resources and staff to reduce waiting times at checkouts.
- By reducing queues, you can increase both customer satisfaction and service efficiency.
Image analytics based on deep learning enables cameras to analyze crowds through video analytics and estimate the number of people in a specific area. The technology can be used for various purposes, such as security, crowd management, and customer behavior analysis.
Some ways to implement queue length detection:
Video analysis:
Our NVRs analyze the video stream and identify crowds based on movement, density and other visual factors.
Counting and density estimation:
These algorithms can accurately count the number of people in a scene and calculate the density (number of people per unit area).
Real-time data:
The system delivers real-time information about crowd levels, making it possible to act quickly in the event of changing conditions.
Warnings and messages:
The system can be set to activate alerts, such as flashing lights or alarms, when the population density exceeds a predefined limit.
Application example:
- Detect and track potential threats, such as suspicious behavior or prolonged stays in places with large crowds.
- Optimize people flow, reduce congestion, and improve safety in places like arenas, concerts, and shopping malls.
- Analysis of customer behavior, insights into customer movements, identification of key areas and optimization of store layouts.
- Traffic management involves adjusting traffic signal times and redirecting traffic based on information about traffic density.
- Increase safety by monitoring crowds and avoiding crowding in potentially risky situations.
- Store optimization is about store owners being able to use crowd density data to optimize product placement, staff planning, and the entire shopping experience.
Image analysis based on deep learning makes it possible to use computer vision and machine learning to detect human faces within the camera's field of view. When a face is detected, the camera can trigger an alarm or, send data that allows identification of the detected face.
Image analysis:
Cameras use algorithms to analyze video streams and detect patterns that resemble human facial features.
Feature extraction:
These algorithms identify key features such as eyes, nose, and mouth to determine whether a face is present.
Notifications:
Once a face is recognized, the system can be set to send a notification or record a video in response.
Face detection:
Focuses on identifying the presence of a face, without necessarily determining who it belongs to.
Face recognition:
Aims to identify a specific person by matching detected faces with a database of known faces.
Application example:
- Facial detection can be used to send alerts when someone enters a restricted area.
- Facial recognition can be used to send alerts when a predefined face is detected by the camera.
- It can improve traditional motion detection by focusing on faces rather than any other movement in the scene.
- Data collection, even if not used to identify individuals, can still be used to track pedestrian traffic and overall activity in a monitored area.
The Smart IR feature allows the camera to automatically adjust the intensity of the infrared light depending on the distance to the subject. This prevents the subject from being overexposed and washed out at close range, while ensuring sufficient illumination at longer distances.
More detailed description:
Traditionel IR:
Regular IR cameras have a fixed IR illumination, which can cause subjects close to the camera to be overexposed and difficult to distinguish, while subjects further away may be insufficiently illuminated.
Smart IR:
With Smart IR technology, the camera automatically adjusts the strength of the IR light. When an object gets closer to the camera, the IR light is reduced, and when the object is further away, it is increased.
Advantages:
This provides clearer and more detailed images in the dark, both near and far, improving surveillance quality.
Application example:
- In environments where people and objects can come close to the camera, such as corridors.
- Close-range vehicle monitoring.
The RXCamView mobile app makes it easy to remotely monitor SafeVision's camera system directly from a smartphone with Android or iOS. Basic settings for the recorder and cameras, as well as PTZ control, can be managed via the phone. The app allows you to connect to the recorder via P2P with a QR code, without additional network configuration. In addition, you can receive push notifications for selected alarm events.
Application example:
- Line rossing.
- Intrusion.
- Sabotage.
The camera uses HTML5 (Hypertext Markup Language 5) to display images in the browser. This allows configuration and streaming from the camera not only via Internet Explorer but also in other popular browsers such as Opera, Firefox, Edge or Chrome. Thanks to HTML5, the user can securely and conveniently connect to the camera. The high performance of the HTML5 protocol allows high-definition video viewing without delay and with moderate use of computer resources.
The two-way power function allows the camera's DC connector (12V) to be used as an output when the camera is powered via PoE. With a maximum output power of 3W, this solution is best suited for active microphones, especially for cameras with audio input.
The recorder in combination with the cameras, in addition to the setting of basic parameters such as contrast and brightness, allows for a significantly more advanced level of camera settings. Depending on the functionality of the camera, this is possible from the recorder level.
Application example:
- Adjust the camera's network settings.
- Stream parameters.
- Adjust zoom and focus on a camera with a motorized zoom lens.
- Activate and set the image analysis function.
The camera has an SD card slot that allows for local recording of video material, making it resilient to interruptions in data transfer between the camera and the recorder. Saved material can be easily played back and exported directly via the browser.
H.265+ is an improved version of the H.265 (HEVC) video compression standard, designed to increase efficiency and reduce bandwidth and storage requirements, especially for surveillance video. This smart algorithm, developed by Hikvision, optimizes the encoding process to lower the bit rate while maintaining video quality at the same level as the original H.265.
H.265+ is based on three main techniques:
Predictive coding:
This technology analyzes and predicts changes in the video image, reducing the amount of data that needs to be recoded for each frame.
Noice reduction:
By reducing image noise, H.265+ can compress video more efficiently without losing important information.
Flexible bitrate control:
H.265+ can dynamically adapt the bitrate to the video content, ensuring that important information is compressed efficiently while less important parts are compressed more aggressively.
| IMAGE | |
| Image Sensor | 8MP Progressive CMOS sensor 1/1.8” |
| Number of Effective Pixels | 3840(H) x 2160(V) |
| Min. Illumination | Color 0.0007lux/F1.0 |
| Electronic Shutter | Auto/manual: 1/5s ~ 1/20000s |
| Digital Slow Shutter (DSS) | Up to 1/5s |
| Wide Dynamic Range (WDR) | Yes (double scan sensor) |
| Digital Noise Reduction (DNR) | 2D, 3D |
| Highlight Compensation (HLC) | Yes |
| Back Light Compensation (BLC) | Yes |
| Reduction of image flicker (Antiflicker) | Yes |
| LENS | |
| Lens Type | Fixed (M12) |
| Point of view | Horizontal: 110° Vertical: 59° Diagonal: 131° |
| Focal length (zoom ratio) | Fixed lens, f=2.8mm/F1.2 |
| Max. aperture ratio | F1.0 |
| Minimum Object Distance | 1.0m |
| DORI | Detection: 56m Observation: 22.4m Recognition: 11.2m Identification: 5.6m |
| DAY/NIGHT | |
| Switching Type | Mechanical IR cut filter |
| Switching Mode | Auto, manual, time |
| Switching Delay | 1 ~ 36s |
| NETWORK | |
| Stream Resolution | Main Stream: 3840x2160, 3072x1944, 2560x1440, 2592x1520, 2304x1296, 1920x1080, 1280x960, 1280x720 Sub Stream: 1920x1080, 1280x720, 640x480 Mobile Stream: 640x480, 320x240 |
| Frame Rate | 30fps for each resolution |
| Multistreaming Mode | 3 streams (main stream, sub stream & mobile stream) |
| Video/Audio Compression | H.264+, H.265+, H.264, H.265, MJPEG/G.711 |
| Number of Simultaneous Connections | Max. 3 connections, (max. 40 streams in total) |
| Bandwidth | 30Mb/s total |
| Video quality adjustment | 256Kbps ~ 16Mbps |
| Bitrate-kontrollmetod | CBR/VBR |
| IP | IPv4/v6 |
| Network Protocols Support | HTTP, TCP/IP, HTTPS, DHCP, DNS, DDNS, NTP, RTSP, RTP, SMTP, P2P |
| Security | Complex password; Authenticated username and password |
| Application programming interface | ONVIF (Profile S/G/T/M) |
| Camera Configuration | From Internet Explorer, Edge, Firefox, Chrome, Safari browser Languages: Swedish, English and others |
| Compatible Software | SafeVision VMS |
| Mobile applications | RxCamView (iPhone, Android) |
| OTHER FUNCTIONS | |
| Privacy Zones | 4 video mask type: single color |
| Motion Detection | Yes |
| AI Analytics | Face Detection,
AI Object Classification (Distinguishes Objects Such as Pedestrians and Vehicles) Perimeter Intrusion,
Line Crossing, Cross Counting, Heat Map, Crowd Density, Queue Length, Rare Sound Detection, Intrusion, Object Detection, Region Entrance, Region Exiting |
| Image setting | Full color mode, Day and night mode, Smart lighting |
| Image Processing | 180˚ image rotation, vertical flip, horizontal flip |
| Prealarm/Postalarm | Up to 5s/up to 30s |
| System Reaction to Alarm Events | E-mail with attachment, saving file on SD card, active deterrent functions |
| Action in case of alarm | White LEDs, steady/flashing light, red and blue LEDs, flashing light, Audio signaling device (siren) |
| Restoring default settings | Via web browser, using reset button |
| License Plate Recognition (ANPR) | |
| Autonomous operation mode | Yes - recognition function implemented in the camera |
| Capacity of License Plate Database | Up to 10000 license plates, on all lists |
| Types of recognized number plates | All countries of the European Union |
| Data recorded in the camera base | Recognition date/time, number of recognised licence plate, image of recognised licence plate, presence on the "white list" or "black list" |
| Reactions for the licence plate recognition | E-mail with attachment, saving file on FTP server, saving a file in the cloud |
| IR LED | |
| LED Number | - |
| Range | - |
| Smart IR | - |
| WHITE LIGHT ILLUMINATOR | |
| LED Number | 2pc, warm white color +(1 red & 1 blue) |
| Range | 20m |
| Smart Light | Yes (hardware support) |
| INTERFACES | |
| Alarm Input/Output | No |
| Audio Input/Output | Built-in microphone/speaker |
| Network Interface | 1 x Ethernet - RJ-45 interface, 10/100Mbit/s |
| Memory Card Slot | MicroSD - capacity up to 256GB |
| INSTALLATION PARAMETERS | |
| Dimensions | Ø115.5 x 97.9mm |
| Weight | 0.645kg |
| Degree of Protection | IP67 |
| Enclosure | Aluminium, white Enclosure type: MIG |
| Power Supply | 12VDC, PoE (IEEE 802.3af, Class 3) |
| Surge protection | TVS 4000V |
| Power Consumption | DC12V: max 6.17W PoE(48V): max 6.96W |
| Operating Temperature | -35°C ~ 60°C |
| Humidity | Max 90%, relative (non-condensing) |
SV-8MIG-ULLADFR/0020-28PW
8MP Turret Camera With Deep
Learning-based Image Analysis,
Ultra Low Light, Active Deterrence
Face Detection/Recognition,
License Plate Detection/Recognition,
Object Verification, Sound Detection,
2.8mm Fixed Lens (110°), 20m LED,
Built-in Microphone and Speaker.
Watch the camera live
Product Sheet
- Manufacturer: SafeVision
- Product Code: 30-224
- EAN: 7340213101785
- In Stock 14pcs
- Available 14pcs
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