The SkyLoc Floor Localization System

Varshavsky, Alex; LaMarca, Anthony; Hightower, Jeffrey; Lara, Eyal de

doi:10.1109/percom.2007.37

Cited by 105 publications

(87 citation statements)

References 12 publications

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“…• Vertical Positioning: Cellular-based solutions in academic and industrial research [138]- [143] as well as commercial 3D location systems [144]- [146], WLAN-based approaches [147]- [153], and sensor-based solutions [154]- [165].…”

mentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

354

171

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Abstract-Location information for events, assets, and individuals, mostly focusing on two dimensions so far, has triggered a multitude of applications across different verticals, such as consumer, networking, industrial, health care, public safety, and emergency response use cases. To fully exploit the potential of location awareness and enable new advanced location-based services, localization algorithms need to be combined with complementary technologies including accurate height estimation, i.e., three dimensional location, reliable user mobility classification, and efficient indoor mapping solutions. This survey provides a comprehensive review of such enabling technologies. In particular, we present cellular localization systems including recent results on 5G localization, and solutions based on Wireless Local Area Networks (WLAN), highlighting those that are capable of computing 3D location in multi-floor indoor environments. We overview range-free localization schemes, which have been traditionally explored in Wireless Sensor Networks (WSN) and are nowadays gaining attention for several envisioned Internet of Things (IoT) applications. We also present user mobility estimation techniques, particularly those applicable in cellular networks, that can improve localization and tracking accuracy. Regarding the mapping of physical space inside buildings for aiding tracking and navigation applications, we study recent advances and focus on smartphone-based indoor Simultaneous Localization and Mapping (SLAM) approaches.The survey concludes with service availability and system scalability considerations, as well as security and privacy concerns in location architectures, discusses the technology roadmap, and identifies future research directions.

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mentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

354

171

View full text Add to dashboard Cite

show abstract

“…In this paper, due to lack of space, we only discuss our fingerprinting-based location algorithm (that is a client-based solution similar to others previously proposed -e.g. RADAR [2], SkyLoc [15]). …”

Section: Location Modulementioning

confidence: 99%

“…Taking advantage of the technologies available in mobile devices, several location systems have been proposed in literature [1,2,15,13,5]. An approach that became popular is to determine the location using information obtained from the existing wireless radio infrastructures.…”

Section: Introductionmentioning

confidence: 99%

“…Some works have also explored the use of this approach with the existing cellular networks [3,15]. In contrast with Wi-Fi networks that are only available in limited areas, cellular networks tend to be available everywhere.…”

Section: Introductionmentioning

confidence: 99%

“…In SkyLoc [15], the authors present a fingerprinting-based location system that relies on GSM signals. The system works only with a specific phone able of providing to the applications the signal strengths of multiple GSM towers.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Collaborative Cellular-Based Location System

Navalho

Preguiça

2010

Euro-Par 2010 - Parallel Processing

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Abstract. A large number of techniques for location estimation relying on the existing wireless radio infrastructures have been proposed in the last few years. Solutions relying on the use of cellular networks can be used almost everywhere, but tend to have low precision. In this paper, we propose the use of information sharing among nearby mobile phones for improving accuracy of cellular-based location. Our information sharing solution was developed in the context of UCLS, a modular location system. This mechanism allows a mobile phone to use additional signal-strength information obtained from nearby devices, that can be connected to different cells of the same or of a different operator. Results show that this additional information helps improving results, with accuracy over 94.8% when using only 2 mobile phones connected to different cell towers when locating the user at the room-level.

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THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

Jalali

Kheirabadi

2023

Int J Communication

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Summary The Internet of Things (IoT) is a novel paradigm that consists of a wide network of machines and intelligent devices with the capability of communication and interaction with each other. One of the significant issues for the IoT is its healthcare applications. The positioning systems based on their environment can be classified into two main categories: Indoor and outdoor. Recently, IoT indoor positioning attracts too much attention among researchers for patient monitoring. Hence, in this paper, a stress‐free floor plan indoor positioning algorithm for patient monitoring is proposed, called THIP. The history of the patient's movement is stored in a trajectory history, and this information is employed to estimate the patient's more accurate position. The proposed THIP algorithm is simulated in MATLAB software. Several experiments are conducted to evaluate the performance of the proposed algorithm. Simulation results show that the proposed THIP algorithm raises patient positioning accuracy and declines the distance error cumulative compared to LiFS by about 4.68% and 60.6 m, respectively. Moreover, it can identify the floor level of the moving user.

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The SkyLoc Floor Localization System

Cited by 105 publications

References 12 publications

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Collaborative Cellular-Based Location System

THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

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