Indoor Localization: Challenges and Opportunities

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft) Pub Date : 2016-05-14 DOI:10.1145/2897073.2897074

R. Melamed

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引用次数: 23

Abstract

Accurate indoor positioning can transform the retail, travel and transportation, and sports industries. For example, think of getting a mobile coupon for a shirt when you are standing near to it in a clothing store and turn-by-turn indoor navigation to the food booth with the shortest queue in airports and stadiums. While the Indoor Location market includes many new business opportunities (estimated around $4.5B by 2019), this emerging area suffers from shortcomings such as limited accuracy, complex maintenance of indoor sensing platforms and lack of data quality assessment tools. This talk will review existing indoor positioning technologies and will discuss their aforementioned limitations. We will present new directions for mitigating these limitations, and we will focus on novel data smoothing algorithms for cleansing noisy indoor data. These algorithms open market opportunities supporting new indoor use cases such detection of common customer paths, targeted/wanderer customers and queues length. Finally, we will discuss future trends in indoor localization and how these technologies will be able to pin point you to a small grocery product in a large supermarket.

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室内定位:挑战与机遇

准确的室内定位可以改变零售、旅游、交通和体育行业。例如，在服装店，当你站在一件衬衫的手机优惠券附近时，你可以获得它;在机场和体育场馆，你可以通过室内导航找到排队最短的食品摊位。虽然室内定位市场包含了许多新的商机(到2019年估计约为45亿美元)，但这一新兴领域仍存在精度有限、室内传感平台维护复杂以及缺乏数据质量评估工具等缺点。本讲座将回顾现有的室内定位技术，并讨论其上述局限性。我们将提出减轻这些限制的新方向，并且我们将重点关注用于清除噪声室内数据的新型数据平滑算法。这些算法打开了市场机会，支持新的室内用例，如检测常见客户路径、目标/漫游客户和队列长度。最后，我们将讨论室内定位的未来趋势，以及这些技术如何能够将您锁定到大型超市中的小型杂货产品。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2016 IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft)

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