Comparison of 2.4 GHz WiFi FTM- and RSSI-Based Indoor Positioning Methods in Realistic Scenarios

Bullmann, Markus; Fetzer, Toni; Ebner, Frank; Ebner, Markus; Deinzer, Frank; Grzegorzek, Marcin

doi:10.3390/s20164515

Cited by 56 publications

(46 citation statements)

References 28 publications

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“…As the foundation of indoor path planning in a fire scenario, indoor positioning refers to the process of understanding the position and orientation of people or objects in an indoor environment, determining the spatial relationship between evacuees and GNM. Since it is formidable to receive GNSS signals in an indoor environment [31], various technologies are applied to achieve indoor positioning, including radio frequency identification (RFID), Bluetooth, wireless LAN, and visible light, which require the deployment of related infrastructure [11][12][13][14]. In terms of indoor positioning integrated with BIM/IFC, Ma et al (2018) [32] applied the Wi-Fi and geomagnetic fingerprint matching positioning method and integrated it into the BIM construction quality management system to solve the problems of missed inspection and secondary data recording during construction acceptance.…”

Section: Indoor Positioning and Computer Visionmentioning

confidence: 99%

“…However, these active indoor positioning techniques, which are relatively less reliable in a fire scenario, are relatively complex and expensive. The ability of BIM for providing rich prior information has been underutilized [ 12 , 13 , 14 ]. Furthermore, as for conducting indoor navigation, most of the existing research studies adopted global shortest path planning method, which is widely applied in normal indoor navigation, ignoring the safety performance of the generated rescue route [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

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BIM and Computer Vision-Based Framework for Fire Emergency Evacuation Considering Local Safety Performance

Deng

Zhang

et al. 2021

Sensors

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Fire hazard in public buildings may result in serious casualties due to the difficulty of evacuation caused by intricate interior space and unpredictable development of fire situations. It is essential to provide safe and reliable indoor navigation for people trapped in the fire. Distinguished from the global shortest rescue route planning, a framework focusing on the local safety performance is proposed for emergency evacuation navigation. Sufficiently utilizing the information from Building Information Modeling (BIM), this framework automatically constructs geometry network model (GNM) through Industry Foundation Classes (IFC) and integrates computer vision for indoor positioning. Considering the available local egress time (ALET), a back propagation (BP) neural network is applied for adjusting the rescue route according to the fire situation, improving the local safety performance of evacuation. A campus building is taken as an example for proving the feasibility of the framework proposed. The result indicates that the rescue route generated by proposed framework is secure and reasonable. The proposed framework provides an idea for using real-time images only to implement the automatic generation of rescue route when a fire hazard occurs, which is passive, cheap, and convenient.

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Section: Indoor Positioning and Computer Visionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BIM and Computer Vision-Based Framework for Fire Emergency Evacuation Considering Local Safety Performance

Deng

Zhang

et al. 2021

Sensors

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“…The ubiquitous availability of Wi-Fi networks prompted the design and development of several Wi-Fi-based ranging and positioning techniques [31, 32, 34-36, 50, 59, 61, 63]. After the introduction of Wi-Fi FTM into IEEE 802.11-2016 and several studies [10,26,62] indicating meter-level accuracy in low-multipath environments [24,26], Wi-Fi FTM has seen adoption in numerous systems [8,21,27,29,48,51,64], with notable applications such as indoor positioning [10,30,37,62] and vehicular positioning [27]. Furthermore, positioning requirements for next-generation wireless networks [28] are currently being defined based on Wi-Fi FTM.…”

Section: Related Workmentioning

confidence: 99%

Here, there, and everywhere

Schepers

Singh

Ranganathan

2021

Proceedings of the 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks

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Today, an increasing number of applications rely on location and proximity information to deliver services. With the introduction of Wi-Fi Fine Timing Measurement (FTM) in the IEEE 802.11-2016 standard, Wi-Fi derived location and proximity information will play a key role in many safety-and security-critical applications. For example, Wi-Fi FTM is adopted in Wi-Fi Aware where it enables geo-fencing and mobile identification. In this paper, we perform the first security analysis of Wi-Fi FTM and analyze its security guarantees across the logical and physical layers. We find various weaknesses that enable an attacker to introduce distance reductions and enlargements to any arbitrary attacker-chosen value, requiring commodity hardware only. We perform an evaluation using commercial access points, smartphones, and off-the-shelf Wi-Fi cards, and show that an attacker can manipulate distances with meter-level precision. Furthermore, we highlight the distance manipulation attacks which are independent of any higher-layer cryptographic protection, exposing fundamental limitations to achieving secure distance measurements in the current standard. Finally, we present security recommendations for the design and implementation of Wi-Fi FTM and next-generation positioning protocols. CCS CONCEPTS• Networks → Mobile and wireless security.

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“…Table 2 differentiates FTM-and UWB-based approaches. From Figure 5, RTT is calculated for an FTM message as [104,105] RTT…”

Section: Csi and Rttmentioning

confidence: 99%

A Survey of Smartphone-Based Indoor Positioning System Using RF-Based Wireless Technologies

Subedi

Pyun

2020

Sensors

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In recent times, social and commercial interests in location-based services (LBS) are significantly increasing due to the rise in smart devices and technologies. The global navigation satellite systems (GNSS) have long been employed for LBS to navigate and determine accurate and reliable location information in outdoor environments. However, the GNSS signals are too weak to penetrate buildings and unable to provide reliable indoor LBS. Hence, GNSS’s incompetence in the indoor environment invites extensive research and development of an indoor positioning system (IPS). Various technologies and techniques have been studied for IPS development. This paper provides an overview of the available smartphone-based indoor localization solutions that rely on radio frequency technologies. As fingerprinting localization is mostly accepted for IPS development owing to its good localization accuracy, we discuss fingerprinting localization in detail. In particular, our analysis is more focused on practical IPS that are realized using a smartphone and Wi-Fi/Bluetooth Low Energy (BLE) as a signal source. Furthermore, we elaborate on the challenges of practical IPS, the available solutions and comprehensive performance comparison, and present some future trends in IPS development.

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Comparison of 2.4 GHz WiFi FTM- and RSSI-Based Indoor Positioning Methods in Realistic Scenarios

Cited by 56 publications

References 28 publications

BIM and Computer Vision-Based Framework for Fire Emergency Evacuation Considering Local Safety Performance

BIM and Computer Vision-Based Framework for Fire Emergency Evacuation Considering Local Safety Performance

Here, there, and everywhere

A Survey of Smartphone-Based Indoor Positioning System Using RF-Based Wireless Technologies

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