A Review of Indoor Localization Techniques and Wireless Technologies

Obeidat, H. A.; Shuaieb, Wafa; Obeidat, Omar; Abd‐Alhameed, Raed A.

doi:10.1007/s11277-021-08209-5

Cited by 242 publications

(137 citation statements)

References 170 publications

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“…Several technologies were presented in [44], [45] for solving indoor localization problems. In [46], [47], ToA, the gap between the transmitter and the receiver was estimated using the signal's travel time and speed.…”

Section: B: Trilaterationmentioning

confidence: 99%

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

Ali¹,

Liu²,

He³

et al. 2021

IEEE Access

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Object identification and localization in indoor and outdoor environments are paramount issues in object-human interaction. Recent advancements in the data fusion capabilities of multi-sensor systems have paved the way for research on emerging object identification and positioning techniques. This review describes techniques and methods used in positioning technologies. State-of-the-art localization technologies are classified into range-based, range-free and AI-based categories. An in-depth analysis of localization approaches based on laser range finder, radio-frequency identification, ultra-wideband, inertial measurement unit, etc., are presented by providing a detailed comparison based on range, accuracy, measurement method, advantages, disadvantages, and their applications. Furthermore, we investigate stateof-the-art multimodal data fusion techniques that utilize probabilistic methods for the precise estimation of object identification in motion and its localization.INDEX TERMS Indoor and outdoor positioning systems; identification and localization; unstructured environment; multi-sensor system; multi-object; positioning and localization techniques.

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Section: B: Trilaterationmentioning

confidence: 99%

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

Ali¹,

Liu²,

He³

et al. 2021

IEEE Access

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“…However, Wi-Fi was not designed for indoor positioning purposes, and so the spread of a radio signal in indoor environments is very hard to predict. In general, this is due to the presence of furniture and walls in the environment which interact with the Wi-Fi signal [19].…”

Section: Previous Workmentioning

confidence: 99%

A Generative Method for Indoor Localization Using Wi-Fi Fingerprinting

Belmonte-Fernández

Sansano-Sansano

Miedes

et al. 2021

Sensors

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Indoor localization is an enabling technology for pervasive and mobile computing applications. Although different technologies have been proposed for indoor localization, Wi-Fi fingerprinting is one of the most used techniques due to the pervasiveness of Wi-Fi technology. Most Wi-Fi fingerprinting localization methods presented in the literature are discriminative methods. We present a generative method for indoor localization based on Wi-Fi fingerprinting. The Received Signal Strength Indicator received from a Wireless Access Point is modeled by a hidden Markov model. Unlike other algorithms, the use of a hidden Markov model allows ours to take advantage of the temporal autocorrelation present in the Wi-Fi signal. The algorithm estimates the user’s location based on the hidden Markov model, which models the signal and the forward algorithm to determine the likelihood of a given time series of Received Signal Strength Indicators. The proposed method was compared with four other well-known Machine Learning algorithms through extensive experimentation with data collected in real scenarios. The proposed method obtained competitive results in most scenarios tested and was the best method in 17 of 60 experiments performed.

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“…This technology is readily available in all types of the indoor environment such as office buildings, houses, educational institutions, etc. It has a greater range of about 100 m and now 1 Km [9]. A lot of work in the literature focus on using Wi-Fi for localization due to ease of availability.…”

Section: Wireless Standards a Wi-fimentioning

confidence: 99%

“…This technique is used because the Global Positioning System (GPS) is not able to determine the position of the object being tracked inside buildings. Indoor localization is used to track nodes/objects in those environments in which GPS does not operate and is often set up in outdoor environments and needs more energy to operate [9]. Moreover, GPS is only accurate up to 5 m [10] and needs a line of sight between the transmitter and the receiver to function properly.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Wireless Standards in IoT for Indoor Localization Using LoPy

et al. 2021

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There are surplus applications in modern smart cities where localization of indoor environments is critical ranging from surveillance and trailing in smart structures to the localized wireless distribution of advertising content in shopping malls. These applications are only successful if a robust and cost-effective real-time system is developed for precise localization. Another aspect considered for indoor localization is power consumption. Recent wireless standards such as Bluetooth Low Energy (BLE) and LoRa consume less power which makes them a perfect candidate for indoor localization. This work aims to carry out an experimental evaluation which would help to decide which wireless standard i.e., Wi-Fi, Bluetooth Low Energy (BLE), and LoRa are most suitable for indoor localization. Experiments are carried out using trilateration in three multiple environments. RSSI is used to calculate the coordinates of a sensor node. Results obtained from the experiment show that Wi-Fi is most accurate with an average error of 0.54 m. LoRa is second most accurate with an average error of 0.62 m and BLE is the least accurate with an average error of 0.82 m. These results can be used to decide which wireless standard is best suited for indoor localization.

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A Review of Indoor Localization Techniques and Wireless Technologies

Cited by 242 publications

References 170 publications

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

Systematic Review of Dynamic Multi-Object Identification and Localization: Techniques and Technologies

A Generative Method for Indoor Localization Using Wi-Fi Fingerprinting

A Comparison of Wireless Standards in IoT for Indoor Localization Using LoPy

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