论文标题
支持位置的物联网(LE-IOT):定位技术,错误来源和缓解措施的调查
Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
论文作者
论文摘要
物联网(物联网)已开始增强许多工业和大众市场应用的未来。本地化技术在没有人类的看法和干预的情况下将位置上下文添加到IoT数据中成为关键。同时,新出现的低功率宽面积网络(LPWAN)技术具有诸如远程,低功耗,低成本,大型连接以及在室内和室外地区进行通信的能力等优点。这些功能使LPWAN信号是大众市场本地化应用程序的强大候选者。但是,有多种错误来源通过使用此类物联网信号的本地化性能有限。本文通过以下序列回顾了IoT本地化系统:IoT本地化系统审查 - 本地化数据源 - 本地化算法 - 本地化错误源和缓解 - 本地化绩效评估。与相关的调查相比,本文对物联网本地化方法进行了更全面和最新的综述,对IoT本地化错误来源的原始评论和缓解措施,对IoT本地化绩效评估的原始评论以及对IoT本地化应用程序,机会,机会和挑战的更全面审查。因此,这项调查为有兴趣在现有的物联网系统中启用本地化能力的同行提供了全面的指导,使用IoT系统进行本地化或将物联网信号与现有本地化传感器集成在一起。
The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors.