Identifying and Tracking Individuals in a Smart Indoor Environment

The failure to rescue the people and sufficiently track victims in Grenfell Tower in London and the disaster of hurricane Katrina has been led to increase the interesting of identification and tracking individual's system, in order to support the indoor environmental services. Various solutions have been proposed making use different connectivity technologies and often a combination of more than one, such as Bluetooth, ZigBee or RFID, however, most of those technologies are limited in coverage and some solutions came up with limited in terms of cost and reliability, therefore, the needs for such a system are in demand. In this paper, we propose an identification and tracking solution that utilizes a combination of two technologies for identifying the individual which are Wi-Fi technology and facial recognition and makes use of Wi-Fi technology by applying the Trilateration algorithms RSSI based for the localization. The developing of the proposed system and data collecting has been achieved through two phases: offline phase and the online phase, also its data saved securely on a cloud-based server while the accuracy of the location estimation is enhanced by fixing enough low-cost Wi-Fi anchor nodes. Testing results have proven a location accuracy within a few centimetres while the identification process works with very high precision with a delay of only a couple of seconds.