2,102 research outputs found
Position Estimation of Robotic Mobile Nodes in Wireless Testbed using GENI
We present a low complexity experimental RF-based indoor localization system
based on the collection and processing of WiFi RSSI signals and processing
using a RSS-based multi-lateration algorithm to determine a robotic mobile
node's location. We use a real indoor wireless testbed called w-iLab.t that is
deployed in Zwijnaarde, Ghent, Belgium. One of the unique attributes of this
testbed is that it provides tools and interfaces using Global Environment for
Network Innovations (GENI) project to easily create reproducible wireless
network experiments in a controlled environment. We provide a low complexity
algorithm to estimate the location of the mobile robots in the indoor
environment. In addition, we provide a comparison between some of our collected
measurements with their corresponding location estimation and the actual robot
location. The comparison shows an accuracy between 0.65 and 5 meters.Comment: (c) 2016 IEEE. Personal use of this material is permitted. Permission
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this work in other work
RFID Localisation For Internet Of Things Smart Homes: A Survey
The Internet of Things (IoT) enables numerous business opportunities in
fields as diverse as e-health, smart cities, smart homes, among many others.
The IoT incorporates multiple long-range, short-range, and personal area
wireless networks and technologies into the designs of IoT applications.
Localisation in indoor positioning systems plays an important role in the IoT.
Location Based IoT applications range from tracking objects and people in
real-time, assets management, agriculture, assisted monitoring technologies for
healthcare, and smart homes, to name a few. Radio Frequency based systems for
indoor positioning such as Radio Frequency Identification (RFID) is a key
enabler technology for the IoT due to its costeffective, high readability
rates, automatic identification and, importantly, its energy efficiency
characteristic. This paper reviews the state-of-the-art RFID technologies in
IoT Smart Homes applications. It presents several comparable studies of RFID
based projects in smart homes and discusses the applications, techniques,
algorithms, and challenges of adopting RFID technologies in IoT smart home
systems.Comment: 18 pages, 2 figures, 3 table
Efficient AoA-based wireless indoor localization for hospital outpatients using mobile devices
The motivation of this work is to help outpatients find their corresponding departments or clinics, thus, it needs to provide indoor positioning services with a room-level accuracy. Unlike wireless outdoor localization that is dominated by the global positioning system (GPS), wireless indoor localization is still an open issue. Many different schemes are being developed to meet the increasing demand for indoor localization services. In this paper, we investigated the AoA-based wireless indoor localization for outpatients’ wayfinding in a hospital, where Wi-Fi access points (APs) are deployed, in line, on the ceiling. The target position can be determined by a mobile device, like a smartphone, through an efficient geometric calculation with two known APs coordinates and the angles of the incident radios. All possible positions in which the target may appear have been comprehensively investigated, and the corresponding solutions were proven to be the same. Experimental results show that localization error was less than 2.5 m, about 80% of the time, which can satisfy the outpatients’ requirements for wayfinding
Machine Learning for Indoor Localization Using Mobile Phone-Based Sensors
In this paper we investigate the problem of localizing a mobile device based
on readings from its embedded sensors utilizing machine learning methodologies.
We consider a real-world environment, collect a large dataset of 3110
datapoints, and examine the performance of a substantial number of machine
learning algorithms in localizing a mobile device. We have found algorithms
that give a mean error as accurate as 0.76 meters, outperforming other indoor
localization systems reported in the literature. We also propose a hybrid
instance-based approach that results in a speed increase by a factor of ten
with no loss of accuracy in a live deployment over standard instance-based
methods, allowing for fast and accurate localization. Further, we determine how
smaller datasets collected with less density affect accuracy of localization,
important for use in real-world environments. Finally, we demonstrate that
these approaches are appropriate for real-world deployment by evaluating their
performance in an online, in-motion experiment.Comment: 6 pages, 4 figure
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Indoor And Outdoor Real Time Information Collection in Disaster Scenario
A disaster usually severely harms human health and property. After a disaster, great amount of information of a disaster area is needed urgently. The information not only indicates the severity of the disaster, but also is crucial for an efficient search and rescue process. In order to quickly and accurately collect real time information in a disaster scenario, a mobile platform is developed for an outdoor scenario and a localization and navigation system for responders is introduced for an indoor scenario.
The mobile platform has been integrated to the DIORAMA system. It is built with a 6-wheel robot chassis along with an Arduino microcontroller. Controlled by a mounted Android smartphone, the mobile platform can receive commands from incident commanders and quickly respond to the commands. While patrolling in a disaster area, a constant RFID signal is collected to improve the localization accuracy of victims. Pictures and videos are also captured in order to enhance the situational awareness of rescuers.
The design of the indoor information collection is focused on the responder side. During a disaster scenario, it is hard to track responders’ locations in an indoor environment. In this thesis, an indoor localization and navigation system based on Bluetooth low energy and Android is developed for helping responders report current location and quickly find the right path in the environment. Different localization algorithms are investigated and implemented. A navigation system based on AÂ* is also proposed
An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System
Optical camera communication (OCC) exhibits considerable importance nowadays
in various indoor camera based services such as smart home and robot-based
automation. An android smart phone camera that is mounted on a mobile robot
(MR) offers a uniform communication distance when the camera remains at the
same level that can reduce the communication error rate. Indoor mobile robot
navigation (MRN) is considered to be a promising OCC application in which the
white light emitting diodes (LEDs) and an MR camera are used as transmitters
and receiver respectively. Positioning is a key issue in MRN systems in terms
of accuracy, data rate, and distance. We propose an indoor navigation and
positioning combined algorithm and further evaluate its performance. An android
application is developed to support data acquisition from multiple simultaneous
transmitter links. Experimentally, we received data from four links which are
required to ensure a higher positioning accuracy
MScMS-II: an innovative IR-based indoor coordinate measuring system for large-scale metrology applications
According to the current great interest concerning large-scale metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance are assuming a more and more important role among system requirements. This paper describes the architecture and the working principles of a novel infrared (IR) optical-based system, designed to perform low-cost and easy indoor coordinate measurements of large-size objects. The system consists of a distributed network-based layout, whose modularity allows fitting differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load. The overall system functionalities, including distributed layout configuration, network self-calibration, 3D point localization, and measurement data elaboration, are discussed. A preliminary metrological characterization of system performance, based on experimental testing, is also presente
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