RSSI-Based Indoor Localization With the Internet of Things
TL;DR: Four wireless technologies for indoor localization: Wi-Fi (IEEE 802.11n-2009 at the 2.4 GHz band), Bluetooth low energy, Zigbee, and long-range wide-area network are compared in terms of localization accuracy and power consumption when IoT devices are used.
Abstract: In the era of smart cities, there are a plethora of applications where the localization of indoor environments is important, from monitoring and tracking in smart buildings to proximity marketing and advertising in shopping malls. The success of these applications is based on the development of a cost-efficient and robust real-time system capable of accurately localizing objects. In most outdoor localization systems, global positioning system (GPS) is used due to its ease of implementation and accuracy up to five meters. However, due to the limited space that comes with performing localization of indoor environments and the large number of obstacles found indoors, GPS is not a suitable option. Hence, accurately and efficiently locating objects is a major challenge in indoor environments. Recent advancements in the Internet of Things (IoT) along with novel wireless technologies can alleviate the problem. Small-size and cost-efficient IoT devices which use wireless protocols can provide an attractive solution. In this paper, we compare four wireless technologies for indoor localization: Wi-Fi (IEEE 802.11n-2009 at the 2.4 GHz band), Bluetooth low energy, Zigbee, and long-range wide-area network. These technologies are compared in terms of localization accuracy and power consumption when IoT devices are used. The received signal strength indicator (RSSI) values from each modality were used and trilateration was performed for localization. The RSSI data set is available online. The experimental results can be used as an indicator in the selection of a wireless technology for an indoor localization system following application requirements.
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12 Jan 2019
TL;DR: A new BLE RSS database that was created to aid in the development of new Ble RSS-based positioning methods and to encourage their reproducibility and comparability is presented.
Abstract: RSS-based indoor positioning is a consolidated research field for which several techniques have been proposed. Among them, Bluetooth Low Energy (BLE) beacons are a popular option for practical applications. This paper presents a new BLE RSS database that was created to aid in the development of new BLE RSS-based positioning methods and to encourage their reproducibility and comparability. The measurements were collected in two university zones: an area among bookshelves in a library and an area of an office space. Each zone had its own batch of deployed iBKS 105 beacons, configured to broadcast advertisements every 200 ms. The collection in the library zone was performed using three Android smartphones of different brands and models, with beacons broadcasting at −12 dBm transmission power, while in the other zone the collection was performed using of one those smartphones with beacons configured to advertise at the −4 dBm, −12 dBm and −20 dBm transmission powers. Supporting materials and scripts are provided along with the database, which annotate the BLE readings, provide details on the collection, the environment, and the BLE beacon deployments, ease the database usage, and introduce the reader to BLE RSS-based positioning and its challenges. The BLE RSS database and its supporting materials are available at the Zenodo repository under the open-source MIT license.
39 citations
TL;DR: The results show that practical UDNs can provide sub–meter positioning accuracy of mobile users by employing ULAs with at least four antennas per TRP and by taking into account the non–idealities of the ULAs' phase and magnitude response.
Abstract: Cellular systems are undergoing a transformation toward the fifth generation (5G). Envisioned applications in 5G include intelligent transport system (ITS), autonomous vehicles, and robots as a part of future roads, factories, and society. These applications rely to a great extent on accurate and timely location information of connected devices. This paper proposes a practical scheme for acquiring precise and timely position information by means of a user–centric ultra–dense network (UDN) architecture based on an edge cloud. The considered solution consists of estimating and tracking the azimuth angle–of–arrival (AoA) of the line–of–sight (LoS)–path between a device and multiple transmission–reception points (TRPs), each having a uniform linear antenna array (ULA). AoA estimates from multiple TRPs are fused into position estimates at the edge cloud to obtain timely position information. The extensive measurements have been carried out using a proof–of–concept software–defined–radio (SDR) testbed in order to experimentally assess the achievable positioning accuracy of the proposed architecture. A realistic UDN deployment scenario has been considered in which TRPs consist of antenna arrays mounted on lamp posts. Our results show that practical UDNs can provide sub–meter positioning accuracy of mobile users by employing ULAs with at least four antennas per TRP and by taking into account the non–idealities of the ULAs' phase and magnitude response.
38 citations
Cites methods from "RSSI-Based Indoor Localization With..."
...One such method of obtaining location information is based on the received signal strength (RSS) of radio signals exchanged among base stations (BSs) and mobile devices [5]–[8]....
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TL;DR: This paper presents a novel, working, reliable, low-cost, scalable solution for asset tracking, supporting global asset management for Industry4.0.
Abstract: Revolutionizing logistics and supply chain management in smart manufacturing is one of the main goals of the Industry 40 movement Emerging technologies such as autonomous vehicles, Cyber-Physical Systems and digital twins enable highly automated and optimized solutions in these fields to achieve full traceability of individual products Tracking various assets within shop-floors and the warehouse is a focal point of asset management; its aim is to enhance the efficiency of logistical tasks Global players implement their own solutions based on the state of the art technologies Small and medium companies, however, are still skeptic toward identification based tracking methods, because of the lack of low-cost and reliable solutions This paper presents a novel, working, reliable, low-cost, scalable solution for asset tracking, supporting global asset management for Industry40 The solution uses high accuracy indoor positioning-based on Ultra-Wideband (UWB) radio technology-combined with RFID-based tracking features Identifying assets is one of the most challenging parts of this work, so this paper focuses on how different identification approaches can be combined to facilitate an efficient and reliable identification scheme
37 citations
TL;DR: The letter proposes a novel BLE-based tracking framework, referred to as the STUPEFY, which incorporates set-valued information within box particle filtering context, and results illustrate significant potentials in terms of improving overall Ble-based achievable tracking accuracy.
Abstract: With the rapid emergence of Internet of Things (IoT), we are more and more surrounded by smart connected devices with integrated sensing, processing, and communication capabilities. Bluetooth Low Energy (BLE), referred to as Bluetooth Smart, is considered as the main-stream technology to perform identification and localization/tracking in IoT applications. While single-model BLE-based tracking has been investigated from different aspects, application of multi-model (hybrid) solutions are still in their infancy. In this regard, the letter proposes a novel BLE-based tracking framework, referred to as the STUPEFY, which incorporates set-valued information within box particle filtering context. More specifically, the proposed multiple-model STUPEFY framework consists of three integrated modules, i.e., an intriguing Smoothing Module based on Kalman filtering to reduce the Received Signal Strength Indicator (RSSI) fluctuations and facilitate comparison of Gaussian models of the RSSI values in distribution with the learned ones; A learning-based model (Coordination Module) utilized in an intuitive fashion to provide/construct a coarse estimate of the target's location together with the smallest axes-aligned box containing the ellipsoid associated with each zone's learned RSSI distribution, and; A novel set-valued box particle filtering (SBPF) approach (Micro-Localization Module). The proposed STUPEFY framework is evaluated based on real BLE datasets and results illustrate significant potentials in terms of improving overall BLE-based achievable tracking accuracy.
36 citations
Additional excerpts
...Experimental dataset [6]: (a) Fingerprinting data....
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...5 m) low-noise meeting room environment [6]....
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TL;DR: In this article, two memoryless positioning techniques, $K$ -nearest neighbor (KNN) and Naive Bayes, were compared with simple trilateration, in terms of accuracy, precision, and complexity.
Abstract: In recent years, the Internet of Things (IoT) has grown to include the tracking of devices through the use of indoor positioning systems (IPSs) and location-based services (LBSs). When designing an IPS, a popular approach involves using wireless networks to calculate the approximate location of the target from devices with predetermined positions. In many smart building applications, LBS is necessary for efficient workspaces to be developed. In this article, we examine two memoryless positioning techniques, $K$ -nearest neighbor (KNN) and Naive Bayes, and compare them with simple trilateration, in terms of accuracy, precision, and complexity. We present a comprehensive analysis between the techniques through the use of three popular IoT wireless technologies: 1) ZigBee; 2) Bluetooth low energy (BLE); and 3) WiFi (2.4-GHz band), along with three experimental scenarios to verify results across multiple environments. According to experimental results, KNN is the most accurate localization technique as well as the most precise. The received signal strength indicator data set of all the experiments is available online.
34 citations
References
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TL;DR: This paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.
Abstract: The Internet of Things (IoT) shall be able to incorporate transparently and seamlessly a large number of different and heterogeneous end systems, while providing open access to selected subsets of data for the development of a plethora of digital services. Building a general architecture for the IoT is hence a very complex task, mainly because of the extremely large variety of devices, link layer technologies, and services that may be involved in such a system. In this paper, we focus specifically to an urban IoT system that, while still being quite a broad category, are characterized by their specific application domain. Urban IoTs, in fact, are designed to support the Smart City vision, which aims at exploiting the most advanced communication technologies to support added-value services for the administration of the city and for the citizens. This paper hence provides a comprehensive survey of the enabling technologies, protocols, and architecture for an urban IoT. Furthermore, the paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.
4,335 citations
"RSSI-Based Indoor Localization With..." refers background in this paper
...These devices are capable of communicating with the IoT to allow for smart buildings to poses a greater amount of control that could never have been achieved before [1], [2]....
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01 Nov 2007
TL;DR: Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
4,123 citations
"RSSI-Based Indoor Localization With..." refers background or methods in this paper
...AoA systems use an array of antennae to determine the angle, from which the signal propagated [8], [19], [20]....
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...The most common technologies are: WiFi, Bluetooth, Radio Frequency Identification (RFID), Ultra-Wide Band (UWB) and cellular [8]....
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...So far, a standard model for indoor localization has not been developed due to obstacles, floor layouts, and reflections of signals that can occur [8]....
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...other methods need to be used in order to determine a device’s location [8]–[10]....
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...For instance, there are many more obstacles indoors, including furniture, walls, and people, which can reflect the signals produced, increasing multipath effects [7], [8], [15]....
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TL;DR: The authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity for smart objects, describing activity-, policy-, and process-aware smart objects and demonstrating how the respective architectural abstractions support increasingly complex application.
Abstract: The combination of the Internet and emerging technologies such as nearfield communications, real-time localization, and embedded sensors lets us transform everyday objects into smart objects that can understand and react to their environment. Such objects are building blocks for the Internet of Things and enable novel computing applications. As a step toward design and architectural principles for smart objects, the authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity. In particular, they describe activity-, policy-, and process-aware smart objects and demonstrate how the respective architectural abstractions support increasingly complex application.
1,459 citations
"RSSI-Based Indoor Localization With..." refers background in this paper
...These devices are capable of communicating with the IoT to allow for smart buildings to poses a greater amount of control that could never have been achieved before [1], [2]....
[...]
TL;DR: This paper aims to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time ofFlight (RTOF), and received signal strength (RSS) based on technologies that have been proposed in the literature.
Abstract: Indoor localization has recently witnessed an increase in interest, due to the potential wide range of services it can provide by leveraging Internet of Things (IoT), and ubiquitous connectivity. Different techniques, wireless technologies and mechanisms have been proposed in the literature to provide indoor localization services in order to improve the services provided to the users. However, there is a lack of an up-to-date survey paper that incorporates some of the recently proposed accurate and reliable localization systems. In this paper, we aim to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time of flight (RTOF), and received signal strength (RSS); based on technologies, such as WiFi, radio frequency identification device (RFID), ultra wideband (UWB), Bluetooth, and systems that have been proposed in the literature. This paper primarily discusses localization and positioning of human users and their devices. We highlight the strengths of the existing systems proposed in the literature. In contrast with the existing surveys, we also evaluate different systems from the perspective of energy efficiency, availability, cost, reception range, latency, scalability, and tracking accuracy. Rather than comparing the technologies or techniques, we compare the localization systems and summarize their working principle. We also discuss remaining challenges to accurate indoor localization.
1,447 citations
"RSSI-Based Indoor Localization With..." refers background in this paper
...to ToA in that it requires devices to have synchronized clocks, but it uses the signal propagation time to multiple receivers to find the absolute signal propagation time [20]....
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...AoA systems use an array of antennae to determine the angle, from which the signal propagated [8], [19], [20]....
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...Through the use of synchronized clocks, the signal propagation time between the transmitter and receiver can be determined [19], [20]....
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TL;DR: This work provides a detailed study of BLE fingerprinting using 19 beacons distributed around a ~600 m2 testbed to position a consumer device, and investigates the choice of key parameters in a BLE positioning system, including beacon density, transmit power, and transmit frequency.
Abstract: The complexity of indoor radio propagation has resulted in location-awareness being derived from empirical fingerprinting techniques, where positioning is performed via a previously-constructed radio map, usually of WiFi signals. The recent introduction of the Bluetooth Low Energy (BLE) radio protocol provides new opportunities for indoor location. It supports portable battery-powered beacons that can be easily distributed at low cost, giving it distinct advantages over WiFi. However, its differing use of the radio band brings new challenges too. In this work, we provide a detailed study of BLE fingerprinting using 19 beacons distributed around a $\sim\! 600\ \mbox{m}^2$ testbed to position a consumer device. We demonstrate the high susceptibility of BLE to fast fading, show how to mitigate this, and quantify the true power cost of continuous BLE scanning. We further investigate the choice of key parameters in a BLE positioning system, including beacon density, transmit power, and transmit frequency. We also provide quantitative comparison with WiFi fingerprinting. Our results show advantages to the use of BLE beacons for positioning. For one-shot (push-to-fix) positioning we achieve $30\ \mbox{m}^2$ ), compared to $100\ \mbox{m}^2$ ) and < 8.5 m for an established WiFi network in the same area.
736 citations
"RSSI-Based Indoor Localization With..." refers background in this paper
...With the recent emergence of BLE and beacons, it has becomemore feasible to place inexpensive beacons around an environment than it is to rearrange existing hardware and use that for localization [17], [18]....
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