Many see digital video technology as disruptive technology, and now that it has taken root in our industry, we are beginning to see an emerging ripple effect from the technology in the form of disruptive trends. New players are challenging preconceived notions of how video surveillance should work and as such, are reshaping the industry. These business trends are proving to be just as disruptive as the technology that precipitated them.
A prime example to illustrate this disruptive trend is the move toward smart video surveillance systems. In the analog video surveillance days, a typical scenario for a physical security system would consist of security video cameras, time lapsed video recorders, an access control/alarm system, motion detection devices, a bank of video monitors and the ubiquitous security guard(s). This kind of classic video surveillance system was designed to record and store, regardless of the application (i.e. banks, commercial buildings, parking structures, schools, etc.) and to give it its due; it served the purpose and worked well for its time.
But having to search through hours and hours of recorded video tape to locate an incident, or trying to watch live activity from multiple cameras on a bank of monitors proved to be less than efficient or effective. The implementation of digital video and the move to network systems in security and surveillance applications changed all of that and video data is now in the same format as other sensor data. In other words, a disruptive trend is occurring in that video surveillance is evolving from a reactive to a proactive application that can process and identify suspicious behavior and objects, and intelligently alert proper authorities to people and events, which require an immediate response.
Additionally, smart surveillance systems have the sophisticated capability to manage recorded video using analytics technologies that allow the search of data according to a broad range of parameters, including time, date, alarm notification, object, size, location and color. For instance, footage of a parking lot from several banks that were robbed can be searched specifically according to the time of the robbery to determine if a constant factor occurs. In this case, the same blue colored automobile is always present and this information, quickly and easily obtained, allows police to focus their search.