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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01 Apr 2019
TL;DR: This paper introduces a low-power and low-cost substitute founded on Long Range (LoRa) to realize similar localization capabilities, based on the Received Signal Strength Indicator (RSSI) techniques.
Abstract: The introduction of Global Positioning Systems (GPS) to the public has provided millions of people with navigation and positioning services around the globe. However, it is known that no matter the improvements to accuracy, fundamentally, GPS cannot provide location information in extreme environments, such as underwater and underground. Hence, there is a growing need for alternative technologies and methodologies of providing localization in such extreme or GPS-less environments. This paper introduces a low-power and low-cost substitute founded on Long Range (LoRa) to realize similar localization capabilities, based on the Received Signal Strength Indicator (RSSI) techniques. LoRa transceivers support swift deployment in GPS-less emergency scenarios, providing emergency teams with critical location and sensing data. According to outdoor experimental results, LoRa is a promising solution for wireless localization systems at GPS-less environments.
20 citations
Cites background or methods from "RSSI-Based Indoor Localization With..."
...RSSI measurements are known to be dependent on the environment, as discussed in [3]....
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...The final solution is the overlap of all the anchor nodes which can be fully realized by calculating the three equations 3, 4, and 5, similar to [3]:...
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...However, its transmission range is over 1000 times greater than Bluetooth 4.0 or Wi-Fi, making it more suitable for large outdoor regions....
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...LoRa technology can be exploited for localization purposes, similar to other technologies like Wi-Fi and Bluetooth [3]....
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...LoRa still employs the same localization principals as the alternatives, where RSSI techniques can be used in conjunction with trilateration in order to determine an estimated position [3]....
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TL;DR: This paper presents a decentralized BLE-based positioning protocol that does not require training before positioning estimation and is adaptive to environmental changes, and its implementation is simple and practical.
20 citations
TL;DR: The proposed feature extraction method uses the continuous wavelet transform to extract the joint time-frequency representation of each raw RSSI data which provides more discriminative information and can be used with a generic deep neural network model to increase the performance where the computing node is not powerful.
Abstract: The performance of localization methods based on the receiver signal strength (RSS) is significantly affected by the signal strength indicator's (RSSI) instability. To date, there is no adequate approach which significantly reduces the impact of such an instability on the localization accuracy. Hence, in this paper, we propose a continuous wavelet transform (CWT)-based feature extraction method for convolutional neural network (CNN)-based indoor fingerprinting localization method. The proposed feature extraction method uses the continuous wavelet transform to extract the joint time-frequency representation of each raw RSSI data which provides more discriminative information. The extracted features are used with a CNN model to efficiently predict the closest reference points (RPs). Then, a K-nearest neighbors (KNN) model is used to compute the target location. The proposed feature extraction method can be used with a generic deep neural network model to increase the performance where the computing node is not powerful. The proposed method has been evaluated on different datasets and has achieved good performance compared with other well-known existing methods. The experimental results also demonstrated that the proposed approach reduces the influence of RSSI variation.
19 citations
TL;DR: An intelligent health monitoring framework using wearable Internet of Things (IoT) and Geo-fencing for COVID-19 susceptible and patient monitoring, and isolation and quarantine management to control the pandemic is proposed.
Abstract: The epidemic disease of Severe Acute Respiratory Syndrome (SARS) called COVID-19 has become a more frequently active disease. Managing and monitoring COVID-19 patients is still a challenging issue for advanced technologies. The first and foremost critical issue in COVID-19 is to diagnose it timely and cut off the chain of transmission by isolating the susceptible and patients. COVID-19 spreads through close interaction and contact with an infected person. It has affected the entire world, and every country is facing the challenges of having adequate medical facilities along with the availability of medical staff in rural and urban areas that have a high number of patients due to the pandemic. Due to the invasive method of treatment, SARS-COVID is spreading swiftly. In this paper, we propose an intelligent health monitoring framework using wearable Internet of Things (IoT) and Geo-fencing for COVID-19 susceptible and patient monitoring, and isolation and quarantine management to control the pandemic. The proposed system consists of four layers, and each layer has different functionality: a wearable sensors layer, IoT gateway layer, cloud server layer, and client application layer for visualization and analysis. The wearable sensors layer consists of wearable biomedical and GPS sensors for physiological parameters, and GPS and Wi-Fi Received Signal Strength Indicator acquisition for health monitoring and user Geo-fencing. The IoT gateway layer provides a Bluetooth and Wi-Fi based wireless body area network and IoT environment for data transmission anytime and anywhere. Cloud servers use Raspberry Pi and ThingSpeak cloud for data analysis and web-based application layers for remote monitoring based on user consent. The susceptible and patient conditions, real-time sensor’s data, and Geo-fencing enables minimizing the spread through close interaction. The results show the effectiveness of the proposed framework.
19 citations
20 May 2019
TL;DR: The optimal number of Bluetooth Low Energy (BLE) beacons to be used for indoor localization to optimize localization accuracy is examined and nine different types of systems were developed and compared in terms of accuracy and precision.
Abstract: Location Based Services (LBS) and Proximity Based Services (PBS) can play an important role in our daily life by simplifying tasks. Functions such as turning on and off lights can occur automatically or locking and unlocking doors can be done using LBS. By knowing the location of a user, appliances can be automated to function once the user is near them. Through the use of indoor localization, a user's position can be calculated. When designing an indoor localization system the density of transmitters plays an important role in maximizing the accuracy obtained. Increasing the number of references can improve the accuracy by providing additional information that the system can use in calculating a location. However, placing too many transmitters in the area can create interference in signals and negatively impact the localization results, while not having enough transmitters will hinder localization as not enough information is available. In this paper, we examine the optimal number of Bluetooth Low Energy (BLE) beacons to be used for indoor localization to optimize localization accuracy. Two algorithms were compared: trilateration and nonlinear least squares applying two types of filtering: moving average, and Kalman. Nine different types of systems were developed and compared in terms of accuracy and precision. According to experimental results placing six beacons in an environment will produce the optimal results. Using a nonlinear least squares algorithm with the three closest references with a moving average filter produced the lowest error of 1.149 meters with a standard deviation of 0.698 meters.
19 citations
Cites methods from "RSSI-Based Indoor Localization With..."
...The environment used for these experiments was the same as the one used during previous experiments performed in [4]....
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...When calculating using trilateration a similar process as in [4] was followed....
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...When performing localization indoors, wireless technologies such as WiFi, Bluetooth Low Energy (BLE), Zigbee, Long Range (LoRa), Radio Frequency Identification (RFID), and Ultra-Wide Band (UWB) are most commonly used [4]–[6]....
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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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