Personalized Real-Time Detection of Unsafe Boundary Transgression

Abstract

Older adults are more prone to experience disorientation or even get lost, which has a negative impact on their independent living. To prevent an older adult from walking away from the safety area where she or he lives and thus from getting lost, this paper proposes an approach that is able to construct personalized safety geofencing for each individual based on her or his outdoor traces. And a real-time detection algorithm is developed to recognize the outlying trajectories caused by boundary transgression behavior of the elderly. First, this paper models each individual??s safety geofencing as an irregular polygon, in which every vertex denotes the physical location where she or he frequently visits and every edge denotes the path between any two physical locations. Second, this paper instantiates the constructed safety geofencing using each individual??s historical GPS trajectories via partitioning her or his region of interest into cells and mapping trajectories into the partitioned region of interest. Third, this paper proposes the real-time detection algorithm for differentiating boundary transgression behavior from the normal ones by introducing the deviation degree of outlying trajectories into the traditional point in polygon detection algorithm. At last, experimental results conducted on a group of individuals?? GPS trajectories demonstrate that the proposed method is feasible to recognize boundary transgression behavior of older adults, obtaining an AUC value of more than 0.995 for all datasets. The prototype system also has good response time and detection performance.

Keywords

• geofencing
• gps trajectory mining
• intelligent assistive technology
• real-time detection algorithm