Enabling Technologies and Techniques for Floor Identification

Author:

Ashraf Imran1ORCID,Zikria Yousaf Bin2ORCID,Garg Sahil3ORCID,Hur Soojung1ORCID,Park Yongwan1ORCID,Guizani Mohsen4ORCID

Affiliation:

1. Information and Communication Engineering, Yeungnam University, Gyeongsan, Republic of Korea

2. Victorian Institute of Technology, Melbourne, Australia and The Institute of International Studies (TIIS), Sydney, Australia

3. Electrical Engineering Department, Ecole de technologie superieure, Montreal, Canada and Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, India

4. Qatar Univ, Doha, Qatar

Abstract

Location information has initiated a multitude of applications such as location-based services, health care, emergency response and rescue operations, and assets tracking. A plethora of techniques and technologies have been presented to ensure enhanced location accuracy, both horizontal and vertical. Despite many surveys covering horizontal localization technologies, the literature lacks a comprehensive survey incorporating up-to-date vertical localization approaches. This article provides a detailed survey of different vertical localization techniques such as path loss models, time of arrival, received signal strength, reference signal received power, fingerprinting utilized by WiFi, radio-frequency identification (RFID), global system for mobile communications (GSM), long-term evolution (LTE), barometer, inertial measurement unit (IMU) sensors, and geomagnetic field. The article primarily aims at human localization in indoor environments using smartphones in essence. Besides the localization accuracy, the presented approaches are evaluated in terms of cost, infrastructure dependence, deployment complexity, and sensitivity. We highlight the pros and cons of these approaches and outline future research directions to enhance the accuracy to meet the future needs of floor identification standards set by the Federal Communications Commission.

Funder

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

Publisher

Association for Computing Machinery (ACM)

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