An iBeacon-based indoor and outdoor positioning system for the fire emergency command

Li, Yu; Chi, Tianhe; Lin, Peng

doi:10.1109/cpgps.2017.8075148

Cited by 14 publications

(4 citation statements)

References 17 publications

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“…The datasets received by the mobile phone from the iBeacon can be found in the repository [ 42 ]. The datasets include the time (milliseconds), UUID, Minor number, Major number, and RSSI (dBm).…”

Section: Resultsmentioning

confidence: 99%

A Novel Optimized iBeacon Localization Algorithm Modeling

Chu

Shi

2023

Sensors

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The conventional methods for indoor localization rely on technologies such as RADAR, ultrasonic, laser range localization, beacon technology, and others. Developers in the industry have started utilizing these localization techniques in iBeacon systems that use Bluetooth sensors to measure the object’s location. The iBeacon-based system is appealing due to its low cost, ease of setup, signaling, and maintenance; however, with current technology, it is challenging to achieve high accuracy in indoor object localization or tracking. Furthermore, iBeacons’ accuracy is unsatisfactory, and they are vulnerable to other radio signal interference and environmental noise. In order to address those challenges, our study focuses on the development of error modeling algorithms for signal calibration, uncertainty reduction, and interfered noise elimination. The new error modeling is developed on the Curve Fitted Kalman Filter (CFKF) algorithms. The reliability, accuracy, and feasibility of the CFKF algorithms are tested in the experiments. The results significantly show the improvement of the accuracy and precision with this novel approach for iBeacon localization.

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Section: Resultsmentioning

confidence: 99%

A Novel Optimized iBeacon Localization Algorithm Modeling

Chu

Shi

2023

Sensors

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“…The traditional switching algorithm is realized by setting the parameters of fixed point switching [19], switching within the effective area [20] or judging the number of base stations of UWB system, the number of satellites of GNSS system [5], signal strength [21], etc. There are problems such as frequent switching or untimely switching, which do not achieve good results.…”

Section: Label Positioning Mode Switching Algorithm Designmentioning

confidence: 99%

“…The 𝐹 𝑈 and 𝐹 𝐺 in (20) denote the sample standard residuals of the UWB and GNSS systems, respectively, and 𝑛 is the power of the residual. The larger the value of 𝑛, the sharper the discriminative effect on the confidence of the two systems, and the more the confidence of the two systems converges to 0 or 1 after normalization, and the value interval of 𝑛 in this system is [0.5,1].…”

Section: Multi-system Joint Confidence Scheme Designmentioning

confidence: 99%

Indoor and outdoor seamless positioning algorithm based on UWB/GNSS

Wang

2023

Preprint

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This paper proposes a positioning mode switching algorithm for positioning tags based on the joint system confidence and motion trend. The algorithm is based on establishing the position estimation confidence of the UWB/GNSS system and the confidence fusion seamless positioning algorithm of particle filtering, which uses a combination of hard and soft switching to achieve seamless positioning. Through the experiment, the positioning accuracy of the positioning tag is measured to be 50.6cm and 56.4cm in the indoor area and the stationary state in the mixed area, with the standard deviation less than 32cm and less than 36cm, respectively; the walking trajectory is stable and clear in the indoor and outdoor dynamic test, and the positioning switching effect is obvious.

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“…Location models have been applied in many fields in recent years. For example, a positioning algorithm was used in a fire emergency command system [ 11 ]. A smart home system using the location method of discretized RSSI-binarization matching was designed by Xiong [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

An IBeacon-Based Location System for Smart Home Control

Liu

Yang

Deng

2018

Sensors

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Indoor location and intelligent control system can bring convenience to people’s daily life. In this paper, an indoor control system is designed to achieve equipment remote control by using low-energy Bluetooth (BLE) beacon and Internet of Things (IoT) technology. The proposed system consists of five parts: web server, home gateway, smart terminal, smartphone app and BLE beacons. In the web server, fingerprint matching based on RSSI stochastic characteristic and posture recognition model based on geomagnetic sensing are used to establish a more efficient equipment control system, combined with Pedestrian Dead Reckoning (PDR) technology to improve the accuracy of location. A personalized menu of remote “one-click” control is finally offered to users in a smartphone app. This smart home control system has been implemented by hardware, and precision and stability tests have been conducted, which proved the practicability and good user experience of this solution.

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An iBeacon-based indoor and outdoor positioning system for the fire emergency command

Cited by 14 publications

References 17 publications

A Novel Optimized iBeacon Localization Algorithm Modeling

A Novel Optimized iBeacon Localization Algorithm Modeling

Indoor and outdoor seamless positioning algorithm based on UWB/GNSS

An IBeacon-Based Location System for Smart Home Control

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