Flexible indoor localization and tracking system based on mobile phone

Du, Yuanfeng; Yang, Dongkai; Hui-lin, Yang; Xiu, Chundi

doi:10.1016/j.jnca.2016.02.023

Cited by 24 publications

(9 citation statements)

References 27 publications

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“…To recognize walking patterns, the random forest algorithm (RF) with additional features and classifier proofing (CP) were applied in [15]. The Maximum Likelihood algorithm can revise the moving direction from sensors [73].…”

Section: Methodsmentioning

confidence: 99%

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Smartphone-Based Indoor Localization Systems: A Systematic Literature Review

et al. 2023

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These recent years have witnessed the importance of indoor localization and tracking as people are spending more time indoors, which facilitates determining the location of an object. Indoor localization enables accurate and reliable location-based services and navigation within buildings, where GPS signals are often weak or unavailable. With the rapid progress of smartphones and their growing usage, smartphone-based positioning systems are applied in multiple applications. The smartphone is embedded with an inertial measurement unit (IMU) that consists of various sensors to determine the walking pattern of the user and form a pedestrian dead reckoning (PDR) algorithm for indoor navigation. As such, this study reviewed the literature on indoor localization based on smartphones. Articles published from 2015 to 2022 were retrieved from four databases: Science Direct, Web of Science (WOS), IEEE Xplore, and Scopus. In total, 109 articles were reviewed from the 4186 identified based on inclusion and exclusion criteria. This study unveiled the technology and methods utilized to develop indoor localization systems. Analyses on sample size, walking patterns, phone poses, and sensor types reported in previous studies are disclosed in this study. Next, academic challenges, motivations, and recommendations for future research endeavors are discussed. Essentially, this systematic literature review (SLR) highlights the present research overview. The gaps identified from the SLR may assist future researchers in planning their research work to bridge those gaps.

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Section: Methodsmentioning

confidence: 99%

“…Wi-Fi [2,6,[12][13][14]17,25, RFID [19,20,93] IMU [5,9,15,17,20,[27][28][29][66][67][68][69][70][71][72][73]83,[93][94][95][96][97][98][99][100][101][102] BLU [9,10,18,74,75,82,86,89,92,95,96,[103][104][105][106][107]…”

Section: Type Of Technology Articlesmentioning

confidence: 99%

Smartphone-Based Indoor Localization Systems: A Systematic Literature Review

et al. 2023

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“…GPS signals work on a frequency which finds it difficult to travel through solid objects such as rooftops and walls, therefore there is no guarantee of it working inside buildings [20]. Wi-Fi -Wi-Fi Positioning System (WPS) makes use of Wi-Fi access points to measure a mobile Wi-Fi signal intensity [13,32]. This system is useful in large urban areas where Wi-Fi signals are common however are less than useful in rural areas that are often Wi-Fi dead zones.…”

Section: Call System Issuesmentioning

confidence: 99%

Smart hospital emergency system

Al-Khafajiy

Kolivand

Baker

et al. 2019

Multimed Tools Appl

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In recent years, the UK's emergency call and response has shown elements of great strain as of today. The strain on emergency call systems estimated by a 9 million calls (including both landline and mobile) made in 2014 alone. Coupled with an increasing population and cuts in government funding, this has resulted in lower percentages of emergency response vehicles at hand and longer response times. In this paper, we highlight the main challenges of emergency services and overview of previous solutions. In addition, we propose a new system call Smart Hospital Emergency System (SHES). The main aim of SHES is to save lives through improving communications between patient and emergency services. Utilising the latest of technologies and algorithms within SHES is aiming to increase emergency communication throughput, while reducing emergency call systems issues and making the process of emergency response more efficient. Utilising health data held within a personal smartphone, and internal tracked data (GPU, Accelerometer, Gyroscope etc.), SHES aims to process the mentioned data efficiently, and securely, through automatic communications with emergency services, ultimately reducing communication bottlenecks. Live video-streaming through real-time video communication protocols is also a focus of SHES to improve initial communications between emergency services and patients. A prototype of this system has been developed. The system has been evaluated by a preliminary usability, reliability, and communication performance study.

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“…For example, Fernandez-Liatas et al [ 2 ] 2015 investigated how radio frequency identification (RFID) technology is used in a variety of healthcare processes. Yuanfang et al [ 3 ] 2016 were able to determine the locations of users who were inside a restricted space by using signals that were sent to users' mobile phones from Wi-Fi. These signals were delivered to users' phones when the users were within a limited area.…”

Section: Introductionmentioning

confidence: 99%

Assessing indoor positioning system: A q-spherical fuzzy rough TOPSIS analysis

Bin Azim,

Ali,

Khan

et al. 2024

Heliyon

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Flexible indoor localization and tracking system based on mobile phone

Cited by 24 publications

References 27 publications

Smartphone-Based Indoor Localization Systems: A Systematic Literature Review

Smartphone-Based Indoor Localization Systems: A Systematic Literature Review

Smart hospital emergency system

Assessing indoor positioning system: A q-spherical fuzzy rough TOPSIS analysis

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