A combination of algorithms powered by neural networks in Kaspersky Antidrone software ensures unparalleled accuracy and high-speed operation in automatic mode.
the AI-powered system combines data from various sensors and controls the hardware
recording and gathering of incident data provide evidence for the security team
a graphical user interface with an interactive map helps to configure the system and control it in real time
all gathered data is available via APIs for SOC, SIEM and other security systems to provide further comprehensive protection
the software can be installed offline to ensure the integrity of corporate information and prevent data leaks
The Kaspersky Neural Networks system continuously searches for airborne objects. The processing server relies on neural networks to instantly process data received from the hardware modules, which allows automatic tracking of the target. Precise information on the drone model and position is displayed on the map and stored in the archive.
For better usability, only UAV alerts are displayed; false alarms are processed by the system without the user’s involvement, which makes the interface and use of the system easy and intuitive.
The Kaspersky Antidrone software controls the hardware modules, continuously monitoring the airspace and instantly responding to incidents through the use of computer vision and neural networks.
This module classifies an object at any time of day thanks to thermal imaging cameras, determines the distance to the object and performs targeting, waiting for a command to be sent to the jamming device.
Basic airspace scanning technology, effective on small scale sites as well as in areas with varying building heights.
This type of camera is used for specific areas of a site perimeter where high-precision monitoring and a high detection range are required.
Module with thermal imaging cameras providing highly accurate detection of airborne objects day and night.
RF scanning is suitable for large sites, including those in urban areas, regardless of time of day or weather conditions, with the ability to determine the location of the pilot.
The microphone module improves the efficiency of primary detection by using audio sensors.
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