Indoor Localization Techniques for Smart Building Environment

Turgut, Zeynep; Aydın, Gülsüm Zeynep Gürkaş; Sertbaş, Ahmet

doi:10.1016/j.procs.2016.04.242

Cited by 52 publications

(36 citation statements)

References 11 publications

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“…1 [6]. IPS is any system that gives a precise position inside of buildings, such as smart buildings [7], hospitals [8], airports [9], [10], subways [11], construction sites [12], industrial sites [13], and university campuses [14]. IPS utilizes many existing technologies such as radio frequencies (RFs) [15], images [16], magnetic fields [17], acoustic signals [18], as well as thermal [19], infrared [20], and optical [21]- [23] sensors together with other sensory information collected by a mobile device (MD) [24].…”

Section: Introductionmentioning

confidence: 99%

A Review of Hybrid Indoor Positioning Systems Employing WLAN Fingerprinting and Image Processing

Firdaus

Ahmad

Sahibuddin

2020

Int. j. electr. comput. eng. syst. (Online)

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Location-based services (LBS) are a significant permissive technology. One of the main components in indoor LBS is the indoor positioning system (IPS). IPS utilizes many existing technologies such as radio frequency, images, acoustic signals, as well as magnetic sensors, thermal sensors, optical sensors, and other sensors that are usually installed in a mobile device. The radio frequency technologies used in IPS are WLAN, Bluetooth, Zig Bee, RFID, frequency modulation, and ultra-wideband. This paper explores studies that have combined WLAN fingerprinting and image processing to build an IPS. The studies on combined WLAN fingerprinting and image processing techniques are divided based on the methods used. The first part explains the studies that have used WLAN fingerprinting to support image positioning. The second part examines works that have used image processing to support WLAN fingerprinting positioning. Then, image processing and WLAN fingerprinting are used in combination to build IPS in the third part. A new concept is proposed at the end for the future development of indoor positioning models based on WLAN fingerprinting and supported by image processing to solve the effect of people presence around users and the user orientation problem.

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Section: Introductionmentioning

confidence: 99%

A Review of Hybrid Indoor Positioning Systems Employing WLAN Fingerprinting and Image Processing

Firdaus

Ahmad

Sahibuddin

2020

Int. j. electr. comput. eng. syst. (Online)

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“…However, this method provides the lowest accuracy performance of these three mentioned approaches. It can only identify the approximate position of the target by successfully communicating with one or more transceivers [4,6]. e proximity is often applied in specific applications such as the exhibitor check-in process and information advertising for visitors in a museum [2,4].…”

Section: Introductionmentioning

confidence: 99%

RoC: Robust and Low-Complexity Wireless Indoor Positioning Systems for Multifloor Buildings Using Location Fingerprinting Techniques

Maneerat

Kaemarungsi

2019

Mobile Information Systems

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Most existing wireless indoor positioning systems have only success performance requirements in normal operating situations whereby all wireless equipment works properly. There remains a lack of system reliability that can support emergency situations when there are some reference node failures, such as in earthquake and fire scenarios. Additionally, most systems do not incorporate environmental information such as temperature and relative humidity level into the process of determining the location of objects inside the building. To address these gaps, we propose a novel integrated framework for wireless indoor positioning systems based on a location fingerprinting technique which is called the Robust and low Complexity indoor positioning systems framework (RoC framework). Our proposed integrated framework consists of two essential indoor positioning processes: the system design process and the localization process. The RoC framework aims to achieve robustness in the system design structure and reliability of the target location during the online estimation phase either under a normal situation or when some reference nodes (RNs) have failed. The availability of low-cost temperature and relative humidity sensors can provide additional information for the location fingerprinting technique and thereby reduce location estimation complexity by including this additional information. Experimental results and comparative performance evaluation revealed that the RoC framework can achieve robustness in terms of the system design structure, whereby it was able to provide the highest positioning performance in either fault-free or RN-failure scenarios. Moreover, in the online estimation phase, the proposed framework can provide the highest reliability of the target location under the RN-failure scenarios and also yields the lowest computational complexity in online searching compared to other techniques. Specifically, when compared to the traditional weighted k-nearest neighbor techniques (WKNN) under the 30% RN-failure scenario at Building B, the proposed RoC framework shows 74.1% better accuracy performance and yields 55.1% lower computational time than the WKNN.

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“…The determination of the position of a moving object is an essential part of many complex applications. While outdoor localization can be achieved with the help of global satellite networks including the Global Positioning System (GPS) and the Global Navigation Satellite System (GLONASS), an efficient indoor localization is still an open problem [1,2]. It can be defined as the process of obtaining the location of a moving object in an indoor environment [2].…”

Section: Introductionmentioning

confidence: 99%

Scan Matching by Cross-Correlation and Differential Evolution

et al. 2019

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Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them.

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Indoor Localization Techniques for Smart Building Environment

Cited by 52 publications

References 11 publications

A Review of Hybrid Indoor Positioning Systems Employing WLAN Fingerprinting and Image Processing

A Review of Hybrid Indoor Positioning Systems Employing WLAN Fingerprinting and Image Processing

RoC: Robust and Low-Complexity Wireless Indoor Positioning Systems for Multifloor Buildings Using Location Fingerprinting Techniques

Scan Matching by Cross-Correlation and Differential Evolution

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