Metadata, artificial intelligence, and video surveillance: do you know the relationship between them?

Metadata is information that describes and provides context about other data. In other words, it’s a way to outline the characteristics or properties of data, which can include images, videos, documents, music, and more. Metadata is used in many fields, such as scientific research, libraries, and also in video surveillance with the support of Artificial Intelligence (AI).

How metadata works with AI in video surveillance:

The combination of metadata and AI is extremely important for video surveillance. The main advantage of analyzing recordings through metadata is the ability to simplify the search for captured images, enabling event searches based on specific descriptions and behaviors—for example, clothing color, age, gender, car model, license plate, abandoned objects, or violent actions.

Once metadata is collected, AI—through deep learning and machine learning—can make predictions and take actions based on this data. These actions may include sending notifications without generating false alerts, which is highly valuable in public and private security. AI also learns from behaviors and characteristics, delivering increasingly personalized and intelligent results.

• PRESENCE OF ANIMALS AND PEOPLE

The equipment can also detect the presence of children, dogs, cats, or even rodents in the monitored areas, as well as specific vehicle features, such as a rear tire. The cameras can even assist in locating missing children if the child’s image is stored in the database.

• PERIMETER PROTECTION

The platform allows the configuration of a virtual protective barrier in areas where entry or presence is prohibited. The cameras can detect people or objects approaching or entering this area, triggering an audible alarm if the boundary is crossed. Additionally, the analysis helps reduce false alarms caused by animals, rain, snow, or other environmental factors, greatly improving alarm accuracy.

• FACIAL RECOGNITION

  The equipment is also capable of performing facial recognition, as well as identifying hair color, approximate age range, use of hats or glasses, and the color of the clothing the individual is wearing at the time. Captured faces are compared with images already stored in the database, allowing each individual to be identified. It is also possible to later search for images based on these records.

• LICENSE PLATE READING

  The analytics also perform license plate recognition, including identifying the color of the vehicle and whether seat belts are being used. All of this is carried out with high precision, whether the vehicles are moving at high or low speeds.

Where else can metadata be used?

Another important aspect is trend analysis, in which analytics identify traffic patterns and behaviors in specific areas over time. This helps companies organize their operations more efficiently. For example, if someone is near valuable items or in sensitive areas that pose a risk, an alert is triggered.

These functions further enhance security in environments such as airports, bus stations, retail stores, and more, due to their ability to profile each individual and situation.

How to manage this metadata?

Dahua offers three video surveillance management platforms: DSS Express (free for up to 64 cameras), DSS Pro (commonly used for medium to large-scale projects), and DSS City, a big data platform with no camera limit.

These platforms read metadata and generate reports with filters and tables for searching. This automation simplifies the operation of video monitoring centers, partially reducing the need for humans to identify events. However, human intervention is still required to analyze dashboards, charts, reports, and any alarms triggered by the cameras.