Wireless Indoor Localization Systems and Techniques: Survey and Comparative Study

<p>The popularity, great influence and huge importance made wireless indoor localization has a unique touch, as well its wide successful on positioning and tracking systems for both human and assists also contributing to take the lead from outdoor systems in the scope of the recent research works. In this work, we will attempt to provide a survey of the existing indoor positioning solutions and attempt to classify different its techniques and systems. Five typical location predication approaches (triangulation, fingerprinting, proximity, vision analysis and trilateration) are considered here in order to analysis and provide the reader a review of the recent advances in wireless indoor localization techniques and systems to have a good understanding of state of the art technologies and motivate new research efforts in this promising direction. For these reasons, existing wireless localization position systems and location estimation schemes are reviewed. We also made a comparison among the related techniques and systems along with conclusions and future trends to identify some possible areas of enhancements. </p>

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Recent Advances in Wireless Indoor Localization Techniques and System

Journal of Computer Networks and Communications ◽

10.1155/2013/185138 ◽

2013 ◽

Vol 2013 ◽

pp. 1-12 ◽

Cited By ~ 228

Author(s):

Zahid Farid ◽

Rosdiadee Nordin ◽

Mahamod Ismail

Keyword(s):

Indoor Localization ◽

Location Estimation ◽

Wireless Localization ◽

Recent Advances ◽

Global Positioning ◽

Real Time Tracking ◽

New Research ◽

Application Requirements ◽

Closed Environment ◽

Wireless Indoor Localization

The advances in localization based technologies and the increasing importance of ubiquitous computing and context-dependent information have led to a growing business interest in location-based applications and services. Today, most application requirements are locating or real-time tracking of physical belongings inside buildings accurately; thus, the demand for indoor localization services has become a key prerequisite in some markets. Moreover, indoor localization technologies address the inadequacy of global positioning system inside a closed environment, like buildings. Based on this, though, this paper aims to provide the reader with a review of the recent advances in wireless indoor localization techniques and system to deliver a better understanding of state-of-the-art technologies and motivate new research efforts in this promising field. For this purpose, existing wireless localization position system and location estimation schemes are reviewed, as we also compare the related techniques and systems along with a conclusion and future trends.

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Tag Localization with Asynchronous Inertial-Based Shifting and Trilateration

Sensors ◽

10.3390/s19235204 ◽

2019 ◽

Vol 19 (23) ◽

pp. 5204

Author(s):

Alma’aitah ◽

Eslim ◽

Hassanein

Keyword(s):

Low Power ◽

Indoor Localization ◽

State Of The Art ◽

Location Estimation ◽

Object Localization ◽

Personal Area Networks ◽

Matlab Simulation ◽

Tag Localization ◽

Simulation Results ◽

Localization Data

Personal Area Networks (PAN) are key topologies in pervasive Internet of Things (IoT) localization applications. In the numerous object localization techniques, centralization and synchronization between the elements are assumed. In this paper, we leverage crowdsourcing from multiple fixed and mobile elements to enhance object localization. A cooperative crowdsourcing scheme is proposed to localize mobile low power tags using distributed and mobile/fixed readers for GPS assisted environments (i.e., outdoor) and fixed readers for indoors. We propose Inertial-Based Shifting and Trilateration (IBST) technique to provide an accurate reckoning of the absolute location of mobile tags. The novelty in our technique is its capability to estimate tag locations even when the tag is not covered by three readers to perform trilateration. In addition, IBST provides scalability since no processing is required by the low power tags. IBST technique is validated through extensive simulations using MATLAB. Simulation results show that IBST consistently estimates location, while other indoor localization solutions fail to provide such estimates as the state-of-the-art techniques require localization data to be available simultaneously to provide location estimation.

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A Survey of Crowd Sensing Opportunistic Signals for Indoor Localization

Mobile Information Systems ◽

10.1155/2016/4041291 ◽

2016 ◽

Vol 2016 ◽

pp. 1-16 ◽

Cited By ~ 29

Author(s):

Ling Pei ◽

Min Zhang ◽

Danping Zou ◽

Ruizhi Chen ◽

Yuwei Chen

Keyword(s):

Indoor Localization ◽

State Of The Art ◽

Low Cost ◽

Academic Community ◽

Future Trends ◽

Crowd Sensing ◽

Practical System ◽

Novel Approach ◽

Fingerprint Database

Sensor-rich smartphone enables a novel approach to training the fingerprint database for mobile indoor localization via crowd sensing. In this survey, we discuss the crowd sensing based mobile indoor localization in terms of foundational knowledge, signals of fingerprints, trajectory of obtaining fingerprints, indoor maps, evolution of a fingerprint database, positioning algorithms, state-of-the-art solutions, and challenges. The survey concludes that the crowd sensing is a low cost solution of generating and updating an organic fingerprint database. Although the crowd sensing concept is widely accepted by the academic community in these years, there are a lot of unsolved problems which hinder the concept of transferring into a practical system. We address the challenges and predict future trends in the end.

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Metaphor research in the 21st century: A bibliographic analysis

Computer Science and Information Systems ◽

10.2298/csis201109059z ◽

2020 ◽

pp. 59-59

Author(s):

Dongyu Zhang ◽

Minghao Zhang ◽

Ciyuan Peng ◽

Jason Jung ◽

Feng Xia

Keyword(s):

21St Century ◽

Web Of Science ◽

State Of The Art ◽

Future Trends ◽

Human Communication ◽

Research Topics ◽

Bibliographic Analysis ◽

Current State ◽

Using Data ◽

New Research

Metaphor is widely used in human communication. The cohort of scholars studying metaphor in various fields is continuously growing, but very few work has been done in bibliographical analysis of metaphor research. This paper examines the advancements in metaphor research from 2000 to 2017. Using data retrieved from Microsoft Academic Graph and Web of Science, this paper makes a macro analysis of metaphor re search, and expounds the underlying patterns of its development. Taking into consideration sub-fields of metaphor research, the internal analysis of metaphor research is carried out from a micro perspective to reveal the evolution of research topics and the inherent relationships among them. This paper provides novel insights into the current state of the art of metaphor research as well as future trends in this field, which may spark new research interests in metaphor from both linguistic and interdisciplinary perspectives.

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PET Radiochemistry Automation: State of the Art and Future Trends in 18F-nucleophilic Fluorination

Current Organic Chemistry ◽

10.2174/13852728113179990102 ◽

2013 ◽

Vol 17 (19) ◽

pp. 2097-2107 ◽

Cited By ~ 18

Author(s):

Raisa Krasikova

Keyword(s):

State Of The Art ◽

Future Trends ◽

Nucleophilic Fluorination

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Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey

Energies ◽

10.3390/en14164776 ◽

2021 ◽

Vol 14 (16) ◽

pp. 4776

Author(s):

Seyed Mahdi Miraftabzadeh ◽

Michela Longo ◽

Federica Foiadelli ◽

Marco Pasetti ◽

Raul Igual

Keyword(s):

Machine Learning ◽

Power Systems ◽

Smart Grids ◽

State Of The Art ◽

Smart Cities ◽

Power Grids ◽

Machine Learning Techniques ◽

Learning Techniques ◽

New Research ◽

Traditional Approaches

The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The review revealed that, when compared to traditional approaches, ML algorithms can handle massive quantities of data with high dimensionality, by allowing the identification of hidden characteristics of (even) complex systems. In particular, even though very different techniques can be used for each application, hybrid models generally show better performances when compared to single ML-based models.

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Application of Microextraction-Based Techniques for Screening-Controlled Drugs in Forensic Context—A Review

Molecules ◽

10.3390/molecules26082168 ◽

2021 ◽

Vol 26 (8) ◽

pp. 2168

Author(s):

Samir M. Ahmad ◽

Oriana C. Gonçalves ◽

Mariana N. Oliveira ◽

Nuno R. Neng ◽

José M. F. Nogueira

Keyword(s):

Environmental Sustainability ◽

Illicit Drugs ◽

State Of The Art ◽

Cost Benefit ◽

Future Trends ◽

Present Contribution ◽

Controlled Drugs ◽

Related Compounds ◽

Innovative Techniques ◽

Great Simplicity

The analysis of controlled drugs in forensic matrices, i.e., urine, blood, plasma, saliva, and hair, is one of the current hot topics in the clinical and toxicological context. The use of microextraction-based approaches has gained considerable notoriety, mainly due to the great simplicity, cost-benefit, and environmental sustainability. For this reason, the application of these innovative techniques has become more relevant than ever in programs for monitoring priority substances such as the main illicit drugs, e.g., opioids, stimulants, cannabinoids, hallucinogens, dissociative drugs, and related compounds. The present contribution aims to make a comprehensive review on the state-of-the art advantages and future trends on the application of microextraction-based techniques for screening-controlled drugs in the forensic context.

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