Journal of Frontiers of Computer Science and Technology ›› 2020, Vol. 14 ›› Issue (6): 1017-1027.DOI: 10.3778/j.issn.1673-9418.1906038

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Personalized Real-Time Detection of Unsafe Boundary Transgression

LIN Qiang, ZHANG Linjun, XIE Ailing, WANG Weilan   

  1. 1. School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou 730124, China
    2. Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education, Northwest Minzu University, Lanzhou 730030, China
  • Online:2020-06-01 Published:2020-06-04



  1. 1. 西北民族大学 数学与计算机科学学院,兰州 730124
    2. 西北民族大学 中国民族语言文字信息技术教育部重点实验室,兰州 730030


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.

Key words: geofencing, GPS trajectory mining, intelligent assistive technology, real-time detection algorithm



关键词: 地理围栏, GPS轨迹挖掘, 智能辅助技术, 实时检测算法