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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TL;DR: In this article , a generalized student t kernel adaptive filter (SGStKAF) is proposed for indoor positioning under the Internet of Things (IoT) framework, where the L 1-norm penalty is applied to embed the GSt kernel into the neural network.
4 citations
TL;DR: In this paper, a hybrid approach between a fingerprint and a model-based indoor positioning system is proposed, which uses synthetic, simulated datasets combined with data fusion techniques to eliminate the fingerprint collection cost.
Abstract: Indoor Positioning Systems (IPSs) are used to estimate the position of mobile devices in indoor environments. Fingerprinting is the most used technique because of its higher accuracy. However, this technique requires a labor-intensive training phase that measures the Received Signal Strength Indicator (RSSI) at all Reference Points (RPs) locations. On the other hand, model-based IPSs use signal propagation models to estimate distances from RSSI. Thus, they do not require expensive training but result in higher positioning errors. In this work, we propose SynTra-IPS (Synthetic Training Indoor Positioning System), a hybrid approach between a fingerprint and a model-based IPS that uses synthetic, simulated datasets combined with data fusion techniques to eliminate the fingerprint collection cost. In our solution, we use the map of the scenario, with known anchor nodes’ positions and the log-distance signal propagation model, to generate several synthetic, model-based, fingerprint training datasets. In the online phase of our solution, the positions estimated by the several synthetic datasets using K-Nearest Neighbors (KNN) are combined using data fusion techniques into a single, more accurate position. We evaluated the performance of our SynTra solution in a real-world, large-scale environment using mobile devices with Bluetooth Low Energy (BLE) technology, and we compared our solution to classic approaches from the literature. Our results show that SynTra can locate mobile devices with an average error of only 2.36 m while requiring no real-world environment training.
4 citations
04 Jul 2019
TL;DR: Through repeated trials of experimentation, the proposed occupancy monitoring design is found to be a possible solution to save power and automate education institutions over certain limitations.
Abstract: The surging energy costs has urged the need to minimize power consumption, especially in large education institutions where most of the power is consumed in providing well lit and air-conditioned classrooms, seminar halls, laboratories and corridors. A lot of power can be saved if we could control electrical appliances through automation, completely removing the possibility of a power loss, that is found to occur in cases where (i) classrooms are unoccupied, yet running with power, or (ii) occupancy of even a small part of the classroom involves all appliances to be turned on, due to a centralized power system. To overcome such cases of power losses, this paper pro-poses an efficient, cost effective and low-cost architecture model that consists of an occupancy monitoring system (subsystem I) integrated with a localized power system. To create such a low-cost system, the usage of Node MCU, a cheaply available microcontroller, as a wireless sensor network(WSN) node is experimented and tested for performing localization using the RSSI. The efficiency of NodeMCV as a sensor node, is measured by the accuracy of detection, which uses a mean algorithm, over a specified period of time. Additionally, to contribute to the automation of a classroom, a second subsystem is integrated with this model, which provides control over the door lock of every classroom. It also provides the means to indicate the status of occupancy in a room, to its clients, the teachers, and allots a free room if requested through an SMS message. Through repeated trials of experimentation, the proposed occupancy monitoring design is found to be successful in detecting the presence of a person(s) in Line of Sight(LOS), when limited up to 3 meters of detection region, with an accuracy of 95%(1 error every 20 min). Beyond this regions, the accuracy dips arbitrarily below an appreciable level due to multipath propagation. Secondly, results show that subsystem II functions smoothly with a maximum latency of 23s and an average latency of 14s before receiving the corresponding response action. Hence the proposed system is found to be a possible solution to save power and automate education institutions over certain limitations.
4 citations
Cites background or methods from "RSSI-Based Indoor Localization With..."
...The protocol used in [19], also includes an authorization function for each received packet by the base node, which can be...
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...In [19], a comparison model on the different modes of wireless technology for RSSI detection is conducted and they have shown that WiFi signals, have been more accurate for Indoor localization, than BLE 4....
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01 Feb 2022
TL;DR: In this article, the authors proposed a 2-phase cell localization algorithm based on trilateration, where the first phase finds the path loss exponent for each anchor node using RSSIs and the second phase divides the available space into virtual cells and finds the location of the cell in which the object is present.
Abstract: Exact location of an object is not required in some scenarios of indoor localization and all we need to know is the area or a cell where the object is present in a room or a hall. For instance, the object to be located is large and we are interested in knowing the locations of the cell in which the object lies, or we want to find the quadrant of a room in which the object of interest lies. For such cases, in this paper, we propose a novel 2-phase cell localization algorithm based on trilateration. In the first phase we find the path loss exponent for each anchor node using RSSIs and in second phase we divide the available space into virtual cells and find the location of the cell in which the object is present. We have conducted real testbed experiments using Wi-Fi and LoRa with different transmission powers and calculated the error. Results show that the proposed algorithm successfully performs cell localization and Wi-Fi based localization is better than that of LoRa. Moreover, we have also studied how the accuracy of localization is affected by cell size in both of the wireless protocol.
4 citations
TL;DR: This paper built prototype wearable localization edge devices designed for first responders and characterize both ranging and localization accuracy and precision using alternative transceivers including Bluetooth Low Energy, 433 MHz, 915 MHz, and ultra-wide band.
Abstract: Recent advances in techniques to improve indoor localization accuracy for personnel and asset tracking challenges has enabled wide-spread adoption within the retail, manufacturing, and health care industries. Most currently deployed systems use distance estimates from known reference locations to localize a person or asset using geometric lateration techniques. The distances are determined using one of many radio frequency (RF) based ranging techniques. Unfortunately, such techniques are susceptible to interference and multipath propagation caused by obstructions within buildings. Because range inaccuracies from known locations can directly lead to incorrect position estimates, these systems often require careful upfront deployment design to account for site-specific interference sources. However, the upfront system deployment requirements necessary to achieve high positioning accuracy with RF-based ranging systems makes the use of such systems impractical, particularly for structures constructed of challenging materials or dense configurations. In this paper, we evaluate and compare the accuracy and precision of alternative RF-based devices within a range of indoor spaces composed of different materials and sizes. These spaces range from large open areas such as gymnasiums to confined engineering labs of traditional buildings as well as training buildings at the local Fire Department Training Facility. Our goal is to identify the impact of alternative RF-based systems on localization accuracy and precision specifically for first responders that are called upon to traverse structures composed of different materials and configurations. Consequently, in this study we have specifically chosen spaces that are likely to be encountered by firefighters during building fires or emergency medical responses. Moreover, many of these indoor spaces can be considered hostile using RF-based ranging techniques. We built prototype wearable localization edge devices designed for first responders and characterize both ranging and localization accuracy and precision using alternative transceivers including Bluetooth Low Energy, 433 MHz, 915 MHz, and ultra-wide band. Our results show that in hostile environments, using ultra-wide band transceivers for localization consistently outperforms the alternatives in terms of precision and accuracy.
4 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]....
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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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