Proceedings of the 5th International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments

Ying Zhang, B. Priyantha, Alex Varshavsky
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引用次数: 6

Abstract

After a decade of research and development for GPS-less localization and tracking, there has been significant progress in location-awareness and location-based services around the world. Almost all cell phone platforms, Android, iPhone and Windows phones, have localization and tracking facilities. In addition, special hardware and infrastructure (e.g., RFID, UWB and BLE or sensor tags) have been developed and deployed for tracking people and merchandise. The advances in cameras and computer vision make it possible for cheap simultaneous localization and mapping (SLAM). However, there are still many challenging problems to be solved, such as accuracy, power management, effective sensor fusion with increasingly powerful embedded computation and resourceful parallel computing backend, learning, transmitting and storing individual trajectories and spatial environment representation, labor-less environmental survey or infrastructure establishment for location-awareness, crowd computing or collective intelligence for map creations, and big data analytics of real-time and historical semantic locations that helps improving efficiency for both consumers and businesses.
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第五届无gps环境下移动实体定位与跟踪国际研讨会论文集
经过十年对gps定位和跟踪的研究和发展,世界各地的位置感知和基于位置的服务已经取得了重大进展。几乎所有的手机平台,如Android、iPhone和Windows手机,都有定位和追踪功能。此外,已经开发和部署了用于跟踪人员和商品的特殊硬件和基础设施(例如,RFID, UWB和BLE或传感器标签)。相机和计算机视觉的进步使廉价的同时定位和绘图(SLAM)成为可能。然而,仍然有许多具有挑战性的问题需要解决,例如精度、电源管理、有效的传感器融合与日益强大的嵌入式计算和资源丰富的并行计算后端、学习、传输和存储个体轨迹和空间环境表示、用于位置感知的无劳动力环境调查或基础设施建设、用于地图创作的人群计算或集体智能。实时和历史语义位置的大数据分析有助于提高消费者和企业的效率。
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