Gun and Active Threat Detection Technology
Statistics show that the issue of gun violence in the United States of America remains a major problem. According to the Gun Violence Archive, the number of gun-related homicides in the US has been steadily rising, reaching 20,200 deaths in 2022, compared to 15,509 in 2019.
There is also an increase in mass shootings nationwide. In 2022, there were 647 incidents reported by the Gun Violence Archive, up from 417 in 2019. With this in mind, we have developed a powerful Gun Detection Technology to help you reduce response time and be more proactive in critical situations.
Gun Detection System
AI utilizes your existing security infrastructure and transforms it into a proactive surveillance system searching for potential physical security risks. Both in real-time and forensically.
The proprietary AI-powered Gun Detection technology effectively helps you automate your response and improve situational awareness.
With the impressive 0.1 false-positive rate per day per camera, Gun Detection Module is one of the most accurate and sensitive AI technologies used for weapon recognition.
Visible Weapon Detection For Schools
With increasing rates of gun violence, schools need every edge they can to increase the warning time before an attack. Mere seconds can make the difference between life and death.
By harnessing advanced video algorithms and artificial intelligence, we can now use cameras to detect most visible firearms and trigger a response: issue text alerts to security staff or emergency personnel, sound audible alarms, lockdown doors, or even connect with an existing system through open API integration.
- Augments standalone access control solutions with a fully integrated workflow.
- Adds vast safety and security capabilities like visible firearm detection to camera systems.
- Increases warning time and allows schools to better react before tragedy occurs.
Anomaly Detection and Behavior Recognition
Optimized to work on multiple video streams using a single GPU and provide real-time event tracking.
Once an anomalous event has been recognized based on the series of frames given to the model, AI sends alerts to all assigned endpoints.
The module supports real-time multiple stream processing as well as offline analysis of video recordings.
The models are trained on a large amount of anomalous and normal videos. This allows the system to operate in versatile environments and scenarios to immediately react and send alerts in case of an anomaly.
The system continuously self-learns, that’s why it can be adjusted specifically for your case, if the current dataset is not fully capturing the peculiarities of the environment at your premises.
- Abnormal shopping behavior
- Slip & fall