Abstract
The last two decades have witnessed a rich variety of indoor positioning and localization research. Starting with Microsoft Research pioneering the fingerprint approach based RADAR, MIT’s Cricket, and then moving towards beacon-based localization are few among many others. In parallel, researchers looked into other appealing and promising technologies like radio frequency identification, ultra-wideband, infrared, and visible light-based systems. However, the proliferation of smartphones over the past few years revolutionized and reshaped indoor localization towards new horizons. The deployment of MEMS sensors in modern smartphones have initiated new opportunities and challenges for the industry and academia alike. Additionally, the demands and potential of location-based services compelled the researchers to look into more robust, accurate, smartphone deployable, and context-aware location sensing. This study presents a comprehensive review of the approaches that make use of data from one or more sensors to estimate the user’s indoor location. By analyzing the approaches leveraged on smartphone sensors, it discusses the associated challenges of such approaches and points out the areas that need considerable research to overcome their limitations.
Highlights
The current decade is marked by the inception and vast expansion of modern mobile devices.A majority of these mobile devices are smartphones which are replacing personal computers today.Equipped with increased processing capabilities, such smartphones can perform more complex tasks than those of personal computers a few decades ago
The rapid expansion and wide acceptance of smartphones led to the inception and introduction of new service industries during the last decade or so
With an increase in the number and processing capabilities of the embedded sensors, smartphones can perform the tasks that personal computers could do a couple of decades ago
Summary
The current decade is marked by the inception and vast expansion of modern mobile devices. Modern smartphones are provided with a variety of sensors that can be adapted for indoor location estimation. Other systems that establish a position using installed specialized hardware (like IR, RF tags, UWB, iBeacon, etc.) can get a refined localization Such systems involve the expansive placement of infrastructure in the area where localization service needs to be provided. Many systems can be founded on the subsisting infrastructure (like Wi-Fi) and benefit from Commercial-Off-The-Shelf (COTS) hardware to estimate the user’s indoor position. They mainly rely on the fingerprinting approach and offers an inexpensive solution to the localization problem.
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