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作为关键基础设施的室内定位系统:对增强型基于位置服务的评估

Indoor Positioning Systems as Critical Infrastructure: An Assessment for Enhanced Location-Based Services.

作者信息

Hailu Tesfay Gidey, Guo Xiansheng, Si Haonan

机构信息

Department of Information and Communication Engineering, Addis Ababa Science and Technology University, Addis Ababa 16417, Ethiopia.

Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

出版信息

Sensors (Basel). 2025 Aug 8;25(16):4914. doi: 10.3390/s25164914.

Abstract

As the demand for context-aware services in smart environments continues to rise, Indoor Positioning Systems (IPSs) have evolved from auxiliary technologies into indispensable components of mission-critical infrastructure. This paper presents a comprehensive, multidimensional evaluation of IPSs through the lens of critical infrastructure, addressing both their technical capabilities and operational limitations across dynamic indoor environments. A structured taxonomy of IPS technologies is developed based on sensing modalities, signal processing techniques, and system architectures. Through an in-depth trade-off analysis, the study highlights the inherent tensions between accuracy, energy efficiency, scalability, and deployment cost-revealing that no single technology meets all performance criteria across application domains. A novel evaluation framework is introduced that integrates traditional performance metrics with emerging requirements such as system resilience, interoperability, and ethical considerations. Empirical results from long-term Wi-Fi fingerprinting experiments demonstrate the impact of temporal signal fluctuations, heterogeneity features, and environmental dynamics on localization accuracy. The proposed adaptive algorithm consistently outperforms baseline models in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), confirming its robustness under evolving conditions. Furthermore, the paper explores the role of collaborative and infrastructure-free positioning systems as a pathway to achieving scalable and resilient localization in healthcare, logistics, and emergency services. Key challenges including privacy, standardization, and real-world adaptability are identified, and future research directions are proposed to guide the development of context-aware, interoperable, and secure IPS architectures. By reframing IPSs as foundational infrastructure, this work provides a critical roadmap for designing next-generation indoor localization systems that are technically robust, operationally viable, and ethically grounded.

摘要

随着智能环境中对情境感知服务的需求持续增长,室内定位系统(IPS)已从辅助技术演变为关键任务基础设施中不可或缺的组件。本文从关键基础设施的角度对IPS进行了全面的多维评估,探讨了其在动态室内环境中的技术能力和操作局限性。基于传感方式、信号处理技术和系统架构,开发了IPS技术的结构化分类法。通过深入的权衡分析,该研究突出了准确性、能源效率、可扩展性和部署成本之间的内在矛盾,揭示了没有单一技术能在所有应用领域满足所有性能标准。引入了一个新颖的评估框架,将传统性能指标与诸如系统弹性、互操作性和伦理考量等新出现的要求相结合。长期Wi-Fi指纹识别实验的实证结果证明了时间信号波动、异质性特征和环境动态对定位准确性的影响。所提出的自适应算法在平均绝对误差(MAE)和均方根误差(RMSE)方面始终优于基线模型,证实了其在不断变化的条件下的稳健性。此外,本文探讨了协作式和无基础设施定位系统在医疗保健、物流和应急服务中实现可扩展和弹性定位途径方面的作用。识别了包括隐私、标准化和现实世界适应性在内的关键挑战,并提出了未来研究方向,以指导情境感知、可互操作和安全的IPS架构的发展。通过将IPS重新定义为基础基础设施,这项工作为设计技术上强大、操作上可行且符合伦理的下一代室内定位系统提供了关键路线图。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f2d/12390319/ca0f1e54d2d2/sensors-25-04914-g004.jpg

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