Journal Article10.1109/MCE.2017.2714719
Indoor Localization with Smartphones: Harnessing the Sensor Suite in Your Pocket
60
TL;DR: The capabilities of these sensors are explored along with the benefits and drawbacks of each for localization and the major challenges that are being faced in current research on indoor localization with smartphones are described.
read more
Abstract: The need for indoor localization systems that can provide reliable access to location information in areas that are not serviced sufficiently by a global positioning system (GPS) has continued to grow. There are a wide variety of use cases for this localization data and increasing interest from industry, academia, and government agencies that has fueled research in this area. Smartphones are uniquely positioned to be a critical part of a localization solution based on the proliferation of these devices and the diverse array of sensors and radios that they contain. In this article, the capabilities of these sensors are explored along with the benefits and drawbacks of each for localization. Various methods for employing these sensors are surveyed. Many localization systems currently being explored utilize a combination of complimentary methods to enhance accuracy and reliability and decrease energy consumption of the overall system. Several of these localization frameworks are also explored. Finally, we describe the major challenges that are being faced in current research on indoor localization with smartphones, as they are critical for charting the path for future advances in indoor localization.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Accurate and Direct GNSS/PDR Integration Using Extended Kalman Filter for Pedestrian Smartphone Navigation
TL;DR: The fusion results show that the prospective method explores the possibility to use smartphone navigation in any case when GNSS or PDR information is not available, and corroborate that the schemed method is sturdier to use in a harsh environments.
24
What is next for Indoor Localisation? Taxonomy, protocols, and patterns for advanced Location Based Services
Francesco Furfari,Antonino Crivello,Paolo Barsocchi,Filippo Palumbo,Francesco Potortì +4 more
- 01 Sep 2019
TL;DR: This is a first high-level attempt at defining a taxonomy of indoor positioning systems, at outlining the main phases of a protocol for the utilisation of different cooperating indoor localisation systems, and at drawing a vision of services and applications in the close future.
22
EchoSpot: Spotting Your Locations via Acoustic Sensing
Jie Lian,Jiadong Lou,Li Chen,Xu Yuan +3 more
- 14 Sep 2021
TL;DR: In this article, a novel indoor localization solution via inaudible acoustic sensing, called EchoSpot, which relies on only one speaker and one microphone that are readily available on audio devices at households, is presented.
22
PortLoc: A Portable Data-Driven Indoor Localization Framework for Smartphones
Saideep Tiku,Sudeep Pasricha +1 more
TL;DR: A portable lightweight fingerprinting framework is described that can be used for indoor navigation and localization while improving localization accuracy and overcoming the challenge of device heterogeneity.
20
Incentive Mechanism for Cooperative Localization in Wireless Networks
TL;DR: Analytical and numerical results show that agents with better network conditions are more likely to join the cooperation under the proposed incentive mechanism, leading to an improved localization performance.
16
References
A New Approach to Linear Filtering and Prediction Problems
Tamer Basar
- 01 Jan 2001
TL;DR: In this paper, the clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the?stat-tran-sition? method of analysis of dynamic systems.
22.7K
RADAR: an in-building RF-based user location and tracking system
Paramvir Bahl,Venkata N. Padmanabhan +1 more
- 26 Mar 2000
TL;DR: RADAR is presented, a radio-frequency (RF)-based system for locating and tracking users inside buildings that combines empirical measurements with signal propagation modeling to determine user location and thereby enable location-aware services and applications.
Estimation of IMU and MARG orientation using a gradient descent algorithm
Sebastian Madgwick,Andrew Harrison,Ravi Vaidyanathan +2 more
- 12 Aug 2011
TL;DR: This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications, applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity sensor arrays that also include tri- axis magnetometers.
2.2K
Indoor localization without the pain
Krishna Chintalapudi,Anand Padmanabha Iyer,Venkata N. Padmanabhan +2 more
- 20 Sep 2010
TL;DR: Despite the absence of any explicit pre-deployment calibration, EZ yields a median localization error of 2m and 7m in a small building and a large building, which is only somewhat worse than the 0.7m and 4m yielded by the best-performing but calibration-intensive Horus scheme from prior work.