期刊文献+

Multi-Floor Indoor Trajectory Reconstruction Using Mobile Devices

下载PDF
导出
摘要 An indoor trajectory is the path of an object moving through corridors and stairs inside a building.There are various types of technologies that can be used to reconstruct the path of a moving object and detect its position.GPS has been used for reconstruction in outdoor environments,but for indoor environments,mobile devices with embedded sensors are used.An accelerometer sensor and a magnetometer sensor are used to detect human movement and reconstruct the trajectory on a single floor.In an indoor environment,there are many activities that will create the trajectory similar to an outdoor environment,such as passing along the corridor,going from one room to another,and other activities.We need to analyse trajectories to obtain the movement patterns,understand themost frequently visited places or paths used aswell as the least frequented ones.Furthermore,we can utilize movement patterns to obtain a better building design and layout.The latest studies focus on reconstructing the trajectory on a single floor.However,actual indoor environments are comprised of multi-floors and multibuildings.The purpose of this paper is to reconstruct a trajectory in an indoor multi-floor environment.We have conducted extensive experiments to evaluate the performance of our proposed algorithms in a campus building.The result of our experiment shows that the height of the building can be detected using a barometer sensor that gives an atmospheric pressure reading which is then transformed by setting the range value according to the number of floors,enabling the sensors to detect activity in a multi-floor building.The readings obtained from the magnetometer sensor can be used to reconstruct the trajectory similar to the real path based on the direction and degree of direction.The system accuracy in recognizing steps in a multi-floor building is about 84%.
出处 《Computer Modeling in Engineering & Sciences》 SCIE EI 2021年第9期927-948,共22页 工程与科学中的计算机建模(英文)
基金 This research was supported by the Scientific Research Deanship,Saudi Electronic University(7732-CAI-2019-1-2-r).
  • 相关文献

参考文献1

二级参考文献3

共引文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部