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Proposed Framework for Improving Localization Using Bluetooth Low Energy Beacons
Published in Monika Mangla, Ashok Kumar, Vaishali Mehta, Megha Bhushan, Sachi Nandan Mohanty, Real-Life Applications of the Internet of Things, 2022
Rakhi Akhare, Monika Mangla, Narendra Shekokar, Smita Sanjay Ambarkar
As shown in Figure 20.2, the database is connected to a smartphone. This database maintains the information about BLE tags IDs. Moreover, the calibrated readings of the BLE tags are also stored in the database with reference to different positions of the smartphones. Here, the smartphone acts as a receiver for iBeacons as well as BLE tags. Both these values with respect to predefined reference points are also maintained in the database. Thus, each recorded entry from beacon contains i) the beacon ID (the unique identifier of the beacon), (ii) the signal strength (RSSI) captured by smartphone application from the specific beacon. RSSI is used to determine the location of mobile from the iBeacon transmitter. Similarly, each recorded entry from tag consists of i) BLE tag ID and ii)RSSI to determine the distance of tag from mobile device. These entries play a crucial role in the localization. A single entry in the database stores the reading from iBeacons and tag. The key component of the proposed localization method is concrete calibrations of BLE tags and beacons.
Introduction
Published in Kaikai Liu, Xiaolin Li, Mobile SmartLife via Sensing, Localization, and Cloud Ecosystems, 2017
One key challenge in context-aware application is how to sense and interact with the real physical location in a fine-grained manner. To improve the location sensing accuracy of mobile device, Apple purchased WiFiSLAM in 2013, and Coherent Navigation in 2015. In 2013, Apple launched iBeacon, i.e., the Apple-certified version of a BLE beacon, which represents programming interface for proximity sensing for smartphone [5]. High-profile retailers such as Macy’s and American Eagle Outfitters, along with major league baseball and the National Football League, are actively testing them for location-aware services around local navigation, augmented reality, retail recommendation, proximity social networking, and location-aware advertising. However, most of these solutions only rely on proximity detection, and provide services like pushing coupon, indoor check-in, far from the augmented reality way.
Role of Real-Time Big Data Processing in the Internet of Things
Published in Kuan-Ching Li, Hai Jiang, Albert Y. Zomaya, Big Data Management and Processing, 2017
Miyuru Dayarathna, Paul Fremantle, Srinath Perera, Sriskandarajah Suhothayan
A practical example of the use of filtering is human trajectory processing. Consider the scenario of a person carrying an iBeacon sensor (e.g., a smartphone) walking in a field of iBeacons. The signals transmitted by the iBeacons are received by the iBeacon sensor. An approximation of the location of the person at a particular time is constructed by triangulating the locations of the iBeacons, which the iBeacon sensor detected (see Figure 12.7). However, the location P(x,y) obtained from such a triangulation is a rough approximation of the exact location of that person at a particular time. This is due to multiple reasons, such as signals emitted by different iBeacons are received by the iBeacon sensor with similar signal strength, at different times, low sampling frequency of iBeacon sensor, out-of-order arrival of events, etc. If the iBeacon sensors are operating with low sampling frequency, sudden changes made to the trajectory of the person are not properly captured (Figure 12.7).
Influential variables impacting the reliability of building occupancy sensor systems: A systematic review and expert survey
Published in Science and Technology for the Built Environment, 2022
Yiyi Chu, Debrudra Mitra, Zheng O’neill, Kristen Cetin
A fourth RF wireless sensor technology is Bluetooth, which uses short-wavelength radio transmissions in the range of 2400–2480 MHz, standardized in IEEE 802.15.1 (2005), to exchange data within short ranges from fixed and mobile devices. Using Bluetooth, smart devices need to be in discoverable mode for an initial registration to be connected. As long as the Bluetooth capability is enabled, there are no subsequent actions needed to change Bluetooth settings. One example is an iBeacon, which uses Bluetooth low-energy (BLE) wireless technology to provide location-based information. There are three main components used in the detection of occupancy using Bluetooth: beacon transmitters, which send uniquely identified beacon packets with a universally unique identifier (UUID), receivers who install a client mobile application on their smartphones to periodically scan signals to detect beacons in a building, and remote servers that gather and implement algorithms to identify whether there is a person in the space based on the information that the client mobile application receives from occupants’ smart phones. The main advantages of the use of Bluetooth sensor technologies include much lower power consumption compared to standard Bluetooth and Wi-Fi devices (Putra et al. 2017). However, a main disadvantage would be the potential interference of this system with Wi-Fi, which may disturb the connection if multiple Bluetooth devices are running at the same time.
A kind of fast Gaussian particle filter based on Artificial Fish School Algorithm
Published in Journal of Control and Decision, 2022
Zhaihe Zhou, Jingmin Ma, Qiqi Liu, Qingxi Zeng, Xiangrui Tian
The preliminary design plan is to use BLE and iBeacon technology. First, conduct experiments in a non-interference environment, installing four iBeacon nodes, numbered 1–4, respectively, equipped with a Bluetooth signal source, and calculate the corresponding point coordinates by collecting Bluetooth signal data. Finally, the given measurement model and the RSSI ranging weighted centroid algorithm can figure the node position’s the measured value. System overall architecture topology shows in Figure 9:
An intelligent indoor guidance and navigation system for the visually impaired
Published in Assistive Technology, 2022
As a more cost-effective alternative to RFID, many of the previously developed non-camera based systems rely on Bluetooth Low Energy (BLE) technology. Having relatively low-cost and long battery life, BLE beacons are used to communicate relevant information to nearby receiver devices in short ranges (Nair et al., 2018). Beacons act as signal transmitters which can be configured using a mobile app and are considered to be a highly accessible location technology. Using this technology, Ahmetovic et al. (2017) introduce a graph-based localization method and evaluate how beacons and Bluetooth samples affect the accuracy and cost of the navigation environment. In another study (Sato et al., 2019), the authors introduce NavCog3, a smartphone navigation assistant system that uses Bluetooth beacons to achieve localization accuracy in real-world scenarios. The developed system guides the user in the path while noting the points of interest and semantic features of the surroundings. Moreover, Leng et al. (2019) present an Unsighted Indoor Navigation System (UINS) using BLE beacons for trilateration and proximity ranging with an application that communicates with the beacons in the navigation process. In the study by Guerreiro et al. (2019), the authors equipped the Pittsburgh International Airport with BLEs so that visually impaired users are able to navigate through relevant routes. In addition, PERCEPT (Argueta et al., 2018) utilizes an optimal number of BLE tags to provide users with navigation instructions to reach a specified destination. 6 trials have been conducted in North Station, Boston resulting in high-satisfaction rates of the users. GuideBeacon (Cheraghi et al., 2017) on the other hand, is presented as an indoor wayfinding system to navigate users between any two points in an indoor environment where the users’ smartphones interact with BLE beacons placed strategically in the setting. Finally, the StaNavi system (Kim et al., 2016) is introduced to guide users through a train station utilizing smartphones and BLE technology without requiring additional devices . Even though beacons are more cost-effective than RFID’s, they are susceptible to suffer from interference. The range of the beacon depends on the ‘broadcasting signal power’ where the higher the signal power results in faster battery drain.