A prediction method that estimates the real-time position of a mobile device based on previously observed data is provided. The present invention can be used in real-time navigation, including providing real-time alerts of an upcoming destination and notifications of emergency events in close geographic proximity. The prediction method utilizes neural networks and/or functions generated using genetic algorithms in estimating the mobile device's real-time position. The prediction method provides reliable Location-Based Services (LBS) in events where traditional positioning technologies become unreliable. It is also seamless, as the user remains unaware of any interruption in accessing the positioning technology.
Barbeau, Sean J.; Winters, Philip L.; Perez, Rafael; Labrador, Miguel; and Georggi, Nevine, "System for pattern recognition in real-time location-based services applications" (2014). USF Patents. 126.
University of South Florida