Wazo employs many advanced neural networks, each of which helps our system detect different objects or situations. Our system’s architecture optimizes the networks’ performance and usefulness. On top of the common neural networks used to detect humans, categorize vehicles, and identify faces, BASS has additional networks for certain inanimate objects, most notably, weapons and bags. The security benefit of weapon detection is obvious, and bag detection has both security and operational benefits.
BASS alerts security instantly if it detects a firearm. This is one of the most important security features of our system, because every second saved in a potential shooter situation could save lives. This alert can be turned off for system use by gun stores, shooting ranges, etc by using the state management tool. Roughly a third of gun homicides involve robbery, and a plurality of these are armed robberies of small and medium sized businesses. This, along with the string of senseless mass shootings that plague America, make weapon detection a key safety feature for any business. This feature is also potentially life-saving when used in schools, which are tragically one of the most common locations of mass shootings.
BASS’s highly accurate bag detection improves safety and operations. On top of being a good accessory to filter with in Smart Searches for witness descriptions, bags conceal information from the security system and the staff. It is useful to have the system keeping track of these potential threats constantly, so in the rare case of a bomb threat or some other threat of violence, all possible weapon hiding locations are accounted for. Bag detection is useful for hotel operations and airports as well. Users can set the system to alert them if a person leaves their bag unattended in a public location, as a theft prevention measure. The security team can monitor the situation to ensure the person who left the bag is also the person who picked it up.