Bluetooth low energy for indoor positioning: Challenges, algorithms and datasets

IF 11.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Automation in Construction Pub Date : 2025-06-12 DOI:10.1016/j.autcon.2025.106316

Mohammadali Ghaemifar, Sanaz Motie, Seyed Mehdi Moosaviun, Yasaman Nemati, Saeed Ebadollahi

{"title":"Bluetooth low energy for indoor positioning: Challenges, algorithms and datasets","authors":"Mohammadali Ghaemifar, Sanaz Motie, Seyed Mehdi Moosaviun, Yasaman Nemati, Saeed Ebadollahi","doi":"10.1016/j.autcon.2025.106316","DOIUrl":null,"url":null,"abstract":"<div><div>This review paper investigates a comprehensive review of Bluetooth Low Energy (BLE)-based indoor positioning systems (IPS), focusing on key techniques, challenges, and advancements. It categorizes IPS methods into geometric mapping and fingerprinting, analyzing their strengths and limitations. The integration of machine learning, deep learning, and reinforcement learning is explored to improve accuracy and address issues such as dynamic environments and Non-Line-of-Sight (NLoS) conditions. The paper also evaluates the use of various Kalman Filters to reduce signal noise and enhance positioning precision. Signal fading, multipath effects, and the importance of dataset availability are examined in depth. A detailed analysis of BLE datasets is provided, highlighting their characteristics, collection methods, and practical applications. The review also outlines the research methodology, including the PRISMA Flowchart and data extraction process. By synthesizing recent findings, the study identifies current trends and proposes future directions for enhancing BLE-based IPS through advanced algorithms and filtering methods.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"177 ","pages":"Article 106316"},"PeriodicalIF":11.5000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation in Construction","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0926580525003565","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

This review paper investigates a comprehensive review of Bluetooth Low Energy (BLE)-based indoor positioning systems (IPS), focusing on key techniques, challenges, and advancements. It categorizes IPS methods into geometric mapping and fingerprinting, analyzing their strengths and limitations. The integration of machine learning, deep learning, and reinforcement learning is explored to improve accuracy and address issues such as dynamic environments and Non-Line-of-Sight (NLoS) conditions. The paper also evaluates the use of various Kalman Filters to reduce signal noise and enhance positioning precision. Signal fading, multipath effects, and the importance of dataset availability are examined in depth. A detailed analysis of BLE datasets is provided, highlighting their characteristics, collection methods, and practical applications. The review also outlines the research methodology, including the PRISMA Flowchart and data extraction process. By synthesizing recent findings, the study identifies current trends and proposes future directions for enhancing BLE-based IPS through advanced algorithms and filtering methods.

Abstract Image

查看原文本刊更多论文

低功耗蓝牙室内定位：挑战、算法和数据集

本文对基于低功耗蓝牙（BLE）的室内定位系统（IPS）进行了全面的综述，重点介绍了关键技术、挑战和进展。将入侵防御方法分为几何映射和指纹识别，分析了它们的优点和局限性。探索机器学习、深度学习和强化学习的集成，以提高准确性并解决诸如动态环境和非视距（NLoS）条件等问题。本文还评价了各种卡尔曼滤波器在降低信号噪声和提高定位精度方面的应用。深入研究了信号衰落、多径效应和数据集可用性的重要性。详细分析了BLE数据集，重点介绍了它们的特点、收集方法和实际应用。该审查还概述了研究方法，包括PRISMA流程图和数据提取过程。通过综合最近的研究结果，本研究确定了当前的趋势，并提出了通过先进的算法和过滤方法增强基于ble的IPS的未来方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Automation in Construction 工程技术-工程：土木

CiteScore

19.20

自引率

16.50%

发文量

563

审稿时长

8.5 months

期刊介绍： Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities. The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.