iBeacon

Abstract: To increase the efficiency in the emergency room, the goal of this research is to implement a mobile-based indoor positioning system using mobile applications (APP) with the iBeacon solution based on the Bluetooth Low Energy (BLE) technology. We use the Received Signal Strength (RSS) based localization method to estimate the patients' locations. Our positioning algorithm achieves 97.22% (95% Confidence Interval = 95.90% – 98.55%) accuracy of classification. As the result, our mechanism is reliable enough to satisfy the need for medical staff to track the locations of their patients.

Abstract: Backscatter communication promises significant power and complexity advantages for Internet of Things devices such as radio frequency identification (RFID) tags and wireless sensor nodes. One perceived disadvantage of backscatter communication has been the requirement for specialized hardware such as RFID readers to receive backscatter signals. In this paper, we show how backscatter signals can be designed for compatibility with the Bluetooth 4.0 low energy (BLE) chipsets already present in billions of smart phones and tablets. We present a prototype microcontroller-based “BLE-Backscatter” tag that produces bandpass frequency-shift keying modulation at 1 Mb/s, enabling compatibility with conventional BLE advertising channels. Using a +23-dBm equivalent isotropically radiated power continuous wave (CW) carrier source, we demonstrate a range of up to 13 m between the tag and an unmodified Apple iPad Mini as well as a PC with the Nordic Semiconductor nRF51822 chipset. With the tag 1 m from the receiver, we demonstrate a range of up to 30 m between the CW carrier source and the tag. In both cases, the existing Bluetooth stack was used, with no modifications whatsoever to hardware, firmware, or software. The backscatter tag consumes only 1.56 nJ/b, over $6\times $ less than the lowest power commercial Bluetooth transmitters.

Abstract: A new generation of low-cost devices is allowing marketers to track the exact location of consumers via their mobile devices. This article explains how the technology works and proposes a number of ways in which marketers might leverage the proximity and triggers that beacons will make possible.

Abstract: In this paper, we propose a robust and accurate indoor localization and tracking system using smartphone built-in inertial measurement unit (IMU) sensors, WiFi received signal strength measurements and opportunistic iBeacon corrections based on particle filter. We utilize Pedestrian Dead Reckoning (PDR) approach which leverages smartphone equipped accelerometers, gyroscope and magnetometer to estimate the walking distance and direction of user. The position estimated by WiFi fingerprinting based approach is fused with PDR to reduce its drifting error. Since the number of WiFi routers is usually limited for localization in large-scale indoor environment, we employ the emerging iBeacon technology to occasionally correct the drifting error of PDR in poor WiFi coverage area. Extensive experiments have been conducted and verified the superiority of the proposed system in terms of localization accuracy and robustness.