DESCRIPTION

Equipped with a 5-125mm motorized lens, this 8MP PTZ dome camera is designed for short-distance surveillance (up to 100m) in indoor and outdoor 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

Object Classification and

Autotracking of The Selected

Objekt

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. The camera classify and is able to autotrack selected type of object.

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.

License Plate Detection and

Recognition

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.

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Cross Counting

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.

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Line Crossing

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.

Intrusion

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.
 

Heat Map

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.

Queue Length Detection

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.

 

Crowd Density Detection

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.

 

Face Detection

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, if connected to a recorder (NVR) with facial recognition, 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.

Facial recognition (done in the NVR):
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 Hardware

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.

       

RxCamView

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.
 

Supports the HTML5 Standard

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.

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Camera Configuration

From NVR

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.

SD Card Slot

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.

                

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.

PoE

Power over Ethernet technology allows you to power an IP camera directly from the recorder or an external PoE switch, without the need for any additional power supplies.
This camera only has PoE.

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