Quezada-Gaibor Darwin, Torres-Sospedra Joaquín, Nurmi Jari, Koucheryavy Yevgeni, Huerta Joaquín
Institute of New Imaging Technologies, Universitat Jaume I, 12071 Castellon, Spain.
Electrical Engineering Unit, Tampere University, 33720 Tampere, Finland.
Sensors (Basel). 2021 Dec 24;22(1):110. doi: 10.3390/s22010110.
Cloud Computing and Cloud Platforms have become an essential resource for businesses, due to their advanced capabilities, performance, and functionalities. Data redundancy, scalability, and security, are among the key features offered by cloud platforms. Location-Based Services (LBS) often exploit cloud platforms to host positioning and localisation systems. This paper introduces a systematic review of current positioning platforms for GNSS-denied scenarios. We have undertaken a comprehensive analysis of each component of the positioning and localisation systems, including techniques, protocols, standards, and cloud services used in the state-of-the-art deployments. Furthermore, this paper identifies the limitations of existing solutions, outlining shortcomings in areas that are rarely subjected to scrutiny in existing reviews of indoor positioning, such as computing paradigms, privacy, and fault tolerance. We then examine contributions in the areas of efficient computation, interoperability, positioning, and localisation. Finally, we provide a brief discussion concerning the challenges for cloud platforms based on GNSS-denied scenarios.
云计算和云平台因其先进的功能、性能和特性，已成为企业必不可少的资源。数据冗余、可扩展性和安全性是云平台提供的关键特性。基于位置的服务（LBS）通常利用云平台来托管定位和本地化系统。本文对当前全球导航卫星系统（GNSS）受限场景下的定位平台进行了系统综述。我们对定位和本地化系统的每个组件进行了全面分析，包括最新部署中使用的技术、协议、标准和云服务。此外，本文还指出了现有解决方案的局限性，概述了在现有室内定位综述中很少受到审查的领域（如计算范式、隐私和容错）的缺点。然后，我们研究了在高效计算、互操作性、定位和本地化领域的贡献。最后，我们简要讨论了基于GNSS受限场景的云平台面临的挑战。
