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: A comparative evaluation of the accuracy achieved by several server-side algorithms, including Kalman filtering, a look-back heuristic as well as a neural network-based approach, for indoor localization techniques developed for real-time monitoring of older adults.
Abstract: This paper details a number of indoor localization techniques developed for real-time monitoring of older adults. These were developed within the framework of the i-Light research project that was funded by the European Union. The project targeted the development and initial evaluation of a configurable and cost-effective cyber-physical system for monitoring the safety of older adults who are living in their own homes. Localization hardware consists of a number of custom-developed devices that replace existing luminaires. In addition to lighting capabilities, they measure the strength of a Bluetooth Low Energy signal emitted by a wearable device on the user. Readings are recorded in real time and sent to a software server for analysis. We present a comparative evaluation of the accuracy achieved by several server-side algorithms, including Kalman filtering, a look-back heuristic as well as a neural network-based approach. It is known that approaches based on measuring signal strength are sensitive to the placement of walls, construction materials used, the presence of doors as well as existing furniture. As such, we evaluate the proposed approaches in two separate locations having distinct building characteristics. We show that the proposed techniques improve the accuracy of localization. As the final step, we evaluate our results against comparable existing approaches.
2 citations
2 citations
09 Mar 2021
TL;DR: In this paper, the authors present node localization methods that employ a dual polarization receiver on a single node, or a virtual array when multiple nodes are capable of cooperating, and aim to minimize the economic cost associated with implementing localization methods, and can be done with simple hardware.
Abstract: The internet of things (IoT) currently has a large range of applications, from wearable to smart cities. Many of these applications require that the nodes inside the networks know their relative or absolute position. To this end, multiple positioning methods can be applied, among such methods are Global Positioning Systems (GPS) or methods that employ time delay of arrival (TDOA). This work presents node localization methods that employ a dual polarization receiver on a single node, or a virtual array when multiple nodes are capable of cooperating. The proposed approaches aim to minimize the economic cost associated with implementing localization methods, and can be done with simple hardware. The accuracy of the proposed methods is measured trough a set of numerical simulations.
2 citations
TL;DR: It is found that the dry paddy field gives less RSSI mean error and it is proved that humidity can contribute to the distance estimation error.
Abstract: This paper presents the use of the received signal strength indicator (RSSI) from the RF signal to estimate the distance from a point where the signal is transmitted to the point where the signal is received. This can be a challenge as in the paddy field, the watery and dry conditions, as well as the height of the paddy plant can affect signal transmission during this estimation process. Two low-cost ground beacons, Beacon1 and Beacon2 (The coordinator), are used and placed in a known location with a fixed distance across the paddy field, which becomes the reference point during the distance estimation for the unmanned aerial vehicle (UAV). These signals are analyzed by using the non-right-angle trigonometry computation, to estimate the distance between the transmitter and the receiver. The estimated distance is compared with the measured value to determine the efficiency of this approach. The calibration trendlines of these beacons in the open, watery and dry paddy fields are discussed and presented. It is found that the dry paddy field gives less RSSI mean error and proved that humidity can contribute to the distance estimation error.
2 citations
Cites methods from "RSSI-Based Indoor Localization With..."
...This technique integrates the wireless network with sensors and other embedded systems that can give valuable information [4] either for indoor [5-8] or outdoor environment [9, 10]....
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TL;DR: In this paper, an early and late fusion of RSSI and accelerometer features in room-level localization is presented. And the performance of the feature extraction from RSSI values is evaluated using different protocols applied to a public dataset.
Abstract: The continuing advancements in technology have resulted in an explosion in the use of interconnected devices and sensors. Internet-of-Things (IoT) systems are used to provide remote solutions in different domains, like healthcare and security. A common service offered by IoT systems is the estimation of a person’s position in indoor spaces, which is quite often achieved with the exploitation of the Received Signal Strength Indication (RSSI). Localization tasks with the goal to locate the room are actually classification problems. Motivated by a current project, where there is the need to locate a missing child in crowded spaces, we intend to test the added value of using an accelerometer along with RSSI for room-level localization and assess the performance of ensemble learning methods. We present here the results of this preliminary approach of the early and late fusion of RSSI and accelerometer features in room-level localization. We further test the performance of the feature extraction from RSSI values. The classification algorithms and the fusion methods used to predict the room were evaluated using different protocols applied to a public dataset. The experimental results revealed better performance of the RSSI extracted features, while the accelerometer’s individual performance was poor and subsequently affected the fusion results.
2 citations
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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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