Managing Data Transmission To Improve Lifetime of Wireless Sensor Network

Abbas, Safana Hyder; Khanjar, Israa M.

doi:10.1109/cas47993.2019.9075466

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…To mitigate this, an absolute positioning system is often required for prolonged use. For outdoor navigation, cellular networks and GNSS are typically used to assist PDR, whereas indoor navigation often employs Bluetooth [11], Wi-Fi [12,13], ultrasonic ranging, or ultrawideband (UWB) [14,15]. When building map information is available, map-matching may also be used [16,17].…”

Section: Introductionmentioning

confidence: 99%

Enhancing Indoor Navigation Accuracy with a Smartphone-Based Pedometer System

Abdulateef,

Makki

2023

ISI

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The prominence of Indoor Navigation Systems (INS) has been on an upward trajectory in recent years. While the Global Positioning System (GPS) commonly utilizes radio waves from artificial satellites for positioning information, its precision is compromised indoors due to potential radio wave obstruction by buildings. In contrast, pedometers, a critical component of INS, can provide invaluable insights into health, exercise, and user itineraries by detecting the number of steps and pinpointing optimal indoor positions. This paper proposes the development of a high-accuracy pedometer system. The proposed tracking system capitalizes on data harvested from accelerometers, sensors integrated into mobile devices, to furnish indoor tracking predicated on a straightforward pedometer approach. Online measurements and tests were conducted in residential settings, and the recorded tests were subsequently simulated offline via MATLAB. The performance of the system was evaluated in a real-world indoor residential scenario using an iPhone6 mobile device, with the discussion encompassing potential usability aspects of the approach. The devised system mitigated the drift of sensor readings by amalgamating the data from the gyroscope and accelerometer. The experimental results revealed a percentage error of 4.33% for the proposed method, translating to an error of 0.65 meters from an average walking distance of approximately 3 meters, out of 15 meters. Future research endeavors will concentrate on enhancing the accuracy of the approach by implementing data filtering and interference reduction techniques.

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