Cloud based passive building occupancy characterization for attack and disaster response

In the moments following natural disasters and terrorist attacks, rescue personnel are often deployed to evacuate all occupants from commercial buildings with hundreds, if not, thousands of tenants. Without a comprehensive estimate of the building occupancy, the rescue personnel are subjected to great risk with little assurance that a given search area is populated. As cloud based computing becomes more ubiquitous, commercial building occupants are utilizing cloud based solutions for managing work schedules. Consequently, the opportunity exists to exploit these whole building occupant schedules to infer occupancy levels throughout the building. In addition, when combined with data from directional passive infrared sensors, and a knowledge of the number of mobile users on Wi-Fi access points, the occupancy profiles can be adjusted based on actively sensed occupancy. This paper discusses an Inferred Occupancy Characterization (IOC) Architecture, which aims to effectively determine occupancy levels within various zones of a multi-zone structure.