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http://www.iaeme.com/IJCET/index.asp 23 [email protected]
International Journal of Computer Engineering & Technology (IJCET) Volume 8, Issue 6, Nov-Dec 2017, pp. 23–35, Article ID: IJCET_08_06_003
Available online at
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ISSN Print: 0976-6367 and ISSN Online: 0976–6375
© IAEME Publication
SURVEY ON INDOOR LOCALIZATION:
EVALUATION PERFORMANCE OF
BLUETOOTH LOW ENERGY AND
FINGERPRINTING BASED INDOOR
LOCALIZATION SYSTEM
Gemechu Wako Samu
Department of Computer science and Engineering,
Symbiosis International University, Institute of Technology, Pune, Maharashtra, India
Prachi Kadam
Ass. Prof., Department of Computer science and Engineering,
Symbiosis International University, Institute of Technology, Pune, Maharashtra, India
ABSTRACT
Location-based systems are significantly trending issue in IoT fields, as it comes
up with services such as navigation and direction to use it for guiding those in need of
assistance. While GPS provides reliable outdoor localization, indoor localization
system is still challenging and many technologies have been proposed. Indoor
localization systems are being developed since last two decades, by making use of
radio frequency, ultrasound or infrared based signal and other technical
advancements in IoT, to provide location and navigation service to the users.
However, most of them rely on customized hardware or presume some dedicated
infrastructure. The main objective of this survey paper is to provide the reader with a
review of the main technologies explored in the literature to solve any indoor
localization issues. Moreover, some of the common used indoor localization
algorithms along with their measurement methods for position estimation in indoor
environments are presented and discussed. Finally, one of the localization algorithms,
fingerprinting algorithm based BLE indoor localization scenario will be discussed.
Key words: Indoor Localization, Internet of Things, BLE, Ibeacon, Fingerprinting
Algorithm.
Cite this Article: Gemechu Wako Samu and Prachi Kadam, Survey on Indoor
Localization: Evaluation Performance of Bluetooth Low Energy and Fingerprinting
Based Indoor Localization System. International Journal of Computer Engineering &
Technology, 8(6), 2017, pp. 23–35.
http://www.iaeme.com/ijcet/issues.asp?JType=IJCET&VType=8&IType=6
Gemechu Wako Samu and Prachi Kadam
http://www.iaeme.com/IJCET/index.asp 24 [email protected]
1. INTRODUCTION
Internet of things is a very highly contributing and an important part of the new era of
technology, have come up rapidly with both theory and practice ever since it has been
proposed. This on a regular basis has resulted in many applications such as Smart city,
Industrial Internet, Smart home, Smart Retail, intelligent environmental monitoring, IOT in
Healthcare and of course, location-based services. For location-based service, outdoor and
indoor localization are two common ways of the service. GPS works very well in the outdoor
environment, but in case of indoor localization, the signal from the GPS satellites is weak to
enter into buildings, which makes it hard for GPS to function in indoor localization
environment. Moreover, locating position information in indoor situations is most challenging
because of quite a few reasons like; errors by multipath and Non-Line-of-Sight conditions,
the presence of moving people that modify the indoor propagation channel, greater density of
obstacles that cause a high attenuation and signal scattering, demand of a higher precision and
accuracy. Fortunately, over last two decades, important research is being done in the area of
indoor localization. This has led to the development of several indoor positioning systems
using different signal technologies for both research and commercial purposes. These
solutions are built with different measurement methods e.g. fingerprinting, literation,
angulation, and Received Signal Strength. Therefore, when developing an indoor positioning
system choice has to be made with respect to signal technologies available and measurement
methods that can be used with these technologies. The following figure shows some of the
common signal technology that is used in making indoor positioning systems.
Figure 1 Common signal technologies used in Indoor Localization
To develop an indoor localization system and choose from which signal technology to
use, a lot of factors such as; cost, accuracy, robustness, scalability, resilience, and coverage
should be considered. It’s obvious that a solitary solution that works without limitation for
any scenario does not exist. Then, it is significant to consider the enactment factors of all
technologies and contest them with the user requirements, which have to be examined and
defined precisely for each application. Additionally, the standards of performance factors are
not unambiguously determined since they, in turn, depend on numerous factors and
conditions. Therefore, it is necessary to find the right method to be used taking in to account
performance parameters, user requirements, and environmental conditions in order to come
up with a good solution.
Indoor
Localization
system
Optical
system
Ultrasound
Based
System
Radio
frequency
based
Infrared
Based
System
Other
System
Survey On Indoor Localization: Evaluation Performance of Bluetooth Low Energy and Fingerprinting
Based Indoor Localization System
http://www.iaeme.com/IJCET/index.asp 25 [email protected]
In indoor localization works done, there are several approaches in which some of them
focus their attention on one technology. In [1], the deliberated indoor localization approach is
based on the Radio Frequency Identification (RFID) technology, in [2] the Sample Size
Determination Algorithm for fingerprinting based indoor localization systems is explored. In
[3], fingerprinting indoor localization technique is explored where deep learning model,
called de-noising auto-encoder is used, to extract robust fingerprint patterns from noisy RSSI
measurements and make a BLE based indoor localization environment.
In [4] the authors present an Indoor Multi-Tag Cooperative Localization Algorithm Based
on NMDS (nonmetric multi-dimensional scaling) for RFID. They even used received signal
strength Euclidean distance based on finger printing method to get the rank order of the
distance between all pairs of tags, whereas in [5], the implementation of indoor localization
based on an experimental study of RSSI using a wireless sensor network is analyzed and
discussed. Finally, [6] provides an implementation of a mobile-based indoor positioning
system using mobile applications with the iBeacon solution based on the Bluetooth Low
Energy (BLE) technology.
This survey paper aims to give an updated overview of the most popular enabling
technologies and provide a review of the main technologies explored in the literature to solve
the indoor localization system issues. Moreover, some of the common used indoor
localization algorithms along with their measurement methods for position estimation in
indoor environments are presented and discussed.
2. INDOOR LOCALIZATION METHODS AND TECHNOLOGY.
Indoor localization systems enable users to find the location of assets, people and places in
specified environments like a shopping mall, Hospitals, Train Stations and Airway stations.
Meanwhile, GPS is imperfect inside buildings for the reason that visual contact with GPS
satellites is poor and the signals can’t penetrate through walls, an Indoor Localization
Systems need to use other positioning means. In most cases, this includes RFID, WLAN/Wi-
Fi, ZigBee or Bluetooth Low Energy Beacons in combination with the internal sensors of a
smartphone. The first and most important step in the implementation of indoor positioning
systems is the selection of the indoor positioning signal technology.
As mentioned earlier, indoor localization systems can be developed using different signal
technologies. Following are the most commonly used signal technologies.
1. Infrared (IR) based Localization Systems
2. Ultrasonic (US) based Localization Systems
3. Radio Frequency (RF) based Localization Systems
4. Optical-based Localization Systems
5. Other Localization Systems
2.1. Infrared (IR) Localization Systems
Infrared-based indoor localization technology is among the most commonly used systems that
work with the help of wireless technology and can be used in applications for detecting or
tracking objects or assets. They are readily available for various devices like mobile phones,
PDAs, and TV (both wired and wireless). The mechanism for IR-based systems is based on
using LOS communication between the two nodes, i.e. transmitter and receiver, provided
there is no interference from light/optical sources in the environment. They are advantageous
due to their small size, being lightweight and thus easily moveable. But also have issues like
security and privacy and require expensive hardware and maintenance cost. An example of a
localization system based on Infrared technology is Active Badge System [13]
Gemechu Wako Samu and Prachi Kadam
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IR based indoor location systems use Infrared light pulses (like a TV remote) to locate
signals inside of a building. IR readers are installed in every room, and when the IR tag
pulses, it is read by the IR reader device. It is a near-foolproof way of guaranteeing room
level accuracy. The drawback is that every room needs a wired IR reader to be installed in the
ceiling. It is commonly used in new hospital construction.
2.3. Ultrasonic Localization Systems
Ultrasonic based localization systems use ultrasonic waves to measure the distance between
the sound source and the mobile system (whose localization is required). Generally, such
systems have multiple ultrasonic receivers and synchronization between them is required
which is usually done with IR or RF waves. The systems use ToA (Time of Arrival)
information of the sound signal from the source to the receiver to estimate receivers’ distance
from the source. The systems based on ultrasonic technology enjoy very good accuracy. Also,
low cost, ease of implementation and high accuracy make such systems a good option for
indoor localization. The disadvantage is they are also affected by a multipath reception and
can have large-scale implementation complexity.
2.3. Radio Frequency Based (RF) Localization Systems
Localization systems based on radio frequency (RF) technologies are most commonly used
nowadays due to the property of radio waves to penetrate through obstacles like walls, human
bodies etc. These systems thus provide better coverage and can be deployed with less
hardware. Another useful aspect of RF-based localization systems is the further division of
RF into narrowband based technologies (RFID, Bluetooth, WLAN/WiFi, and FM) and
wideband based technologies (UWB). RF-based localization systems have attracted
researchers interests over the last ten years and a significant amount of work is done in this
regard. The technique used in RF-based localization is given below and will be subsequently
explained.
1. RFID
2. Bluetooth Low Energy
3. WLAN/WiFi
4. ZigBee
5. UWB and
6. Hybrid
RFID
RFID (radio-frequency identification), practices the use of radio waves to wirelessly
communicate the identity and other characteristics of an object, to an evolving positioning
technology and allows flexible tracking of objects or people. RFID is not suitable for area-
wide positioning as it offers a limited range of less than a meter, but rather for a selected
object identification. It’s cost-effective, easy for maintenance and provides both identification
and location. This makes localization via RFID mostly appropriate for tracking results in
manufacturing environments (e.g. asset management).
The categories of this expertise brands it the perfect contender for the tracking of
numerous products, like food or drugs [14], [15], [16] along the stock series, but it is also
used for several further purposes, comprising indoor localization. RFID technology based
localization systems are used in many applications such as locating people, in automobile
assembly industry, in warehouse management, in supply chain network etc. since the system
works without line of sight requirement.
Survey On Indoor Localization: Evaluation Performance of Bluetooth Low Energy and Fingerprinting
Based Indoor Localization System
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A basic system would consist of a reader (also known as RFID scanner) with an antenna
which constantly scans for active transceivers or passive tags in its environment. Using radio
signals as one way wireless communication of data is done from RFID tags to the reader.
Following fig shows basic procedures of how RFID based localization works.
Figure 2 Representation of RFID technology working
Bluetooth (BLE beacons)
Bluetooth is a wireless standard for WPANs (Wireless Personal Area Networks) just like
ZigBee. It is a patented format handled by Bluetooth SIG (Special Interest Group). Bluetooth
operates in the 2.4 GHz ISM band. Compared to WLAN, the range is shorter (typically 10–15
m). With Bluetooth standard also used for information exchange, there is also another benefit
of this technology in form of provision of high security, low cost, low power and small size.
Bluetooth technology can be used in position detection and authorizing to reuse the devices
previously well-appointed with Bluetooth technology, so the addition of a fresh consumer to
such a system does not involve any extra hardware. Meanwhile, Bluetooth is a less in cost
and has low power consumption technology, it is effectual in order to project indoor
localization systems. Moreover, Bluetooth tags have small size transceivers. As any other
Bluetooth device, respective tags have an exclusive ID, which can be used to locate the
Bluetooth tags. On the other hand, Bluetooth is a “lighter” and pervasive typically because it
is implanted in most devices such as mobile phones, personal digital assistants (PDAs),
laptop, desktop, etc.
There has been researching done in exploring the best possible positioning principle for
Bluetooth based localization systems. In [6], a mobile-based indoor positioning system using
mobile applications with iBeacon solution based on the Bluetooth Low Energy (BLE)
technology are implemented. Whereas in [9] the technology is used for finding an accurate
and precise location of a tracked asset or place by using smartphone built-in inertial
measurement unit (IMU) sensors, WiFi received signal strength measurements and
opportunistic iBeacon corrections based on particle filter. BLE-based indoor positioning
systems usually use Proximity and fingerprinting localization approach. The following fig
shows how a common BLE based indoor positioning system would work by fingerprinting
approach.
Gemechu Wako Samu and Prachi Kadam
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Figure 3 Representation of BLE technology working
WLAN/WiFi
Using a WiFi-based indoor positioning system is common practice because of low
infrastructure cost and no need for line-of-sight (LOS). Any device with WiFi compatibility
can be easily localized without any additional hardware or software manipulation. They are
commercially available and are mostly based on received signal strength measurement
principle.
There are several advantages for designing a localization system using WLAN (WiFi)
technology. Some of them include the ready availability of access points in indoor
environments, no special hardware requirements, a 50-100 meters range making it more
attractive in comparison to Bluetooth or RFID.
ZigBee
ZigBee is wireless technology standard popular for short and medium range communication
applications. It can be regarded as a low rate Wireless Personal Area Network (WPAN). The
standard is designed for applications requiring low power consumption in mind and not
requiring large data throughput. For indoor environments, ZigBee signal range is typically
20-30m. RSSI is the usual principle used for distance estimation between two ZigBee nodes.
One drawback is that since ZigBee operates in the unlicensed ISM band, the designed
localization system would be vulnerable to interference from other signal types consequently
harming the radio communication. In [8] ZigBee communication technology is used to design
an energy efficient indoor localization system and to improve the localization accuracy.
Whereas [7] used ZigBee to perform an indoor localization application and locate a person in
a building with a reasonable position accuracy
UWB
Ultra-wide-band is a radio technology for short range, high bandwidth communication
holding the properties of strong multipath resistance. For localization systems with high
accuracy demands (20-30 cm), UWB is widely used as other conventional wireless
technologies such as RFID and WLAN/WiFi do not provide such high level of accuracy. A
basic UWB based localization setup would include stimulus radio wave generators and
receivers which can capture the propagated and scattered waves. UWB signals have property
to penetrate through walls, glass and other obstacles making it extremely good for indoor
localization because ranging is then free of LoS constraint and also inter-room ranging is
Survey On Indoor Localization: Evaluation Performance of Bluetooth Low Energy and Fingerprinting
Based Indoor Localization System
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possible. The problem with UWB is that hardware is expensive thus making it unsuitable for
large-scale implementation.
Hybrid
Hybrid localization systems use multiple different localization technologies for locating a
mobile client. Localizing a mobile client is one of the most important services of a
localization system and since some location technologies are primarily designed for indoor
and GPS based positioning system is unsuitable for indoor, thus a hybrid system which works
both indoors and outdoors would be highly desirable. This is how the concept of hybrid
localization system came into being. Hybrid localization systems have been worked upon and
[12] implemented a prototype of the hybrid indoor positioning system to obtain better results
jointly using both iBeacon BLE and WiFi.
2.4. Optical Positioning Systems
Optical indoor positioning systems use the camera as the main sensor. There are also optical
positioning systems in combination with a distance or mechanical sensors. Optical indoor
localization systems using camera-based system architectures are exclusively built on the
Angle of Arrival (AoA) method. The advancement in CCD technologies, processing speed,
and image understanding have helped in developing camera-based indoor localization
systems.
2.5. Other Systems
There are other ways to do indoor localization as well. Some of the systems developed in this
regard are discussed now. They can be a specifically designed system with a certain
application in mind and would make use of different available options including external
(multiple sensors), different RF technologies etc. They are as:
• Inertial Navigation Systems (INS)
• Magnetic Localization
• Infrastructure-Based Localization Systems
3. INDOOR LOCALIZATION ALGORITHMS
The over-all algorithms which are commonly used for indoor localization are listed below:
• Trilateration Algorithm
• Triangulation Algorithm
• Fingerprinting Algorithm
• Proximity Algorithm
• Dead Reckoning Algorithm
These algorithms make use of different measurement methods for position estimation for
indoor positioning. A graph showcasing the above-mentioned algorithms with their
corresponding measurement methods is given below. Each algorithm is briefly explained
afterward.
Gemechu Wako Samu and Prachi Kadam
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Figure 4 Common Indoor Localization algorithms
Triangulation and Trilateration
The working principle of triangulation practices geometric assets of triangles to define the
target’s position, whereas travel time of the signal from the source to destination is used in
trilateration. They are of two derivations (basic measurement principles):
• Lateration and
• Angulation
Lateration (Trilateration)
In lateration, the position of an object is estimated by measuring its distance from multiple
reference points. In this approach time of arrival (ToA) or time difference of arrival (TDoA)
measurement method is used and distance is derived by computing attenuation of signal
strength or by simply using the relationship that signal velocity multiplied with time traveled
gives distance. The common lateration measurement techniques are:
• Time of Arrival (ToA) Method
• Time Difference of Arrival (TDoA) Method
• RSS (Received Signal Strength or Signal Attenuation) based Method
• RToF (Roundtrip Time of Flight) Method
• Received Signal Phase Method
Angulation (Triangulation)
In angulation measurement method, the position of an object is computed with help of
measured positions comparative to several location points. This method is typically
implemented with Angle of Arrival method.
Fingerprinting
Fingerprinting or Scene analysis is a type of algorithm used for indoor localization in which
the first step is to gather features of a scene and then assess the position of an entity by
corresponding current location’s dimensions with the neighboring apriori location
fingerprints. Position fingerprinting involves, matching of the fingerprint of a signal’s feature
which is location dependent. This technique comprises of two stages:
Indoor localization
Trilateration
ToA
TDoA
Triangulation AoA
Fingerprining RSSI
Proximity RSSI
Dead Reckoning
Survey On Indoor Localization: Evaluation Performance of Bluetooth Low Energy and Fingerprinting
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• Offline &
• Online stage.
The offline stage is about doing a site survey of the environment. This involves taking
signal strengths of various location points from the close-by base stations (reference units)
and noting them down. The online stage would then be using a positioning algorithm to
estimate the current location, based on the observed current signal strength and previously
collected information. The key challenge for the positioning algorithms based on location
fingerprinting is a general problem with signal strength i.e. it being affected by diffraction,
reflection, and scattering in its propagation in an indoor environment. There are multiple
fingerprinting-based localization algorithms using pattern recognition method, e.g. Euclidean
distance, Probabilistic methods, K-Nearest neighbors (kNN), Neural networks etc.
The standard signal technology used is RF (Received Signal Strength Indication, RSSI)
for fingerprinting but there are also fingerprinting localization systems with audio signals or
visual images.
Proximity
The proximity method for localization finds the position of a mobile device just by its
presence in a special area. Hence, proximity-based algorithms provide symbolic relative
location information. This method works by simply forwarding the location of an anchor
(base or reference) point from where the strongest signal is received. Proximity measurement
method has a simple implementation, but the accuracy of this method depends on how much
anchor points are deployed and signal range. Proximity-based localization systems are usually
based on signal technologies like Infrared Radiation (IR) and Radio Frequency Identification
(RFID). General examples of proximity-based localization systems are in sensing physical
interaction, automatic ID systems, and mobile wireless locating systems.
Dead Reckoning
In dead reckoning, the position is estimated by using knowledge of previously defined points
and recognized or assessed speeds over the intervened period. Usually, the main sensor type
used is an inertial navigation system. The one problem with this system’s usage is inaccuracy
is cumulative; hence, abnormality in the location fix raises with time. In the domain of indoor
applications, a term called Pedestrian Dead Reckoning (PDR) is used in literature to indicate
that external sensors like accelerometer are being attached to the user’s body.
Table ahead summarizes different algorithms and measurement methods used for indoor
localization with respect to some key performance parameters.
Table 1 Summary of different methods used in indoor localization systems.
Method Measurement
Type Accuracy Coverage
LoS/NLo
S Multipath affect Cost
Proximity RSS Low-high Good Both No Low
Direction AoA Medium Good LOS Yes High
Time ToA,TDoA High Good LOS Yes High
Fingerprinting RSS High Good Both No Medium
Dead
reckoning
Acceleration,
Velocity Low-medium Good NLOS Yes Low
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4. MAKING OF BLE FINGERPRINTING ALGORITHM BASED
INDOOR LOCALIZATION
In making indoor localization system, fingerprinting is commonly used localization approach.
This is because this method requires no additional cost on infrastructure along with no prior
knowledge of the environment is required. This algorithm starts with a comprehensive survey
of the site (i.e. the indoor space which is to be localized) with respect to RSS readings that
can be recorded over multiple points (distance distribution) in the coverage area. This results
in a database of recorded signal strengths over numerous points (i.e. fingerprints of each
point). The localization (of a mobile device) problem is then reduced to co-relating
(matching) the currently measured RSS reading with those in the database to estimate
position. The system works on the assumption that each position in localization space can be
associated with a unique signal strength feature and by virtue of this current location can be
obtained relying on the difference of signal strength at different positions.
4.1. How it works
The implementation of fingerprinting involves conducting an offline & online phase. These
two phases are explained in detail ahead to develop a better understanding so that a BLE-
based indoor localization system can be developed using fingerprinting localization approach,
and its performance with respect to accuracy will be evaluated.
4.2. Offline phase
The offline phase starts with the division of the indoor environment area (where localization
of a mobile device is to be done) into a grid of cells. The Figure (3.7) helps explain this first
step of offline phase. Consider a generic indoor environment, presented as a blank square box
on left side in Figure (3.7). This indoor space is divided into small cells. Each cell enjoys a
unique identification within the localization space. In the second step of offline phase, signal
strength characteristic for each cell is recorded (usually at the center of each cell) and
associated with it. This way a database (or radio-map) is built where each cell will have its
own unique RSS characteristic from each reference node and hence the word fingerprint. The
radio-map (or database) can be created in two ways: mean value type radio-map and
probability density function type radio-map. Commonly mean value type radio-map
(database) is created in offline case. In mean value type radio map, mean RSSI values from
each reference node are gathered for each cell
Figure 5 The division of (desired) localization area into small cells acts as the first step of offline
phase. For each cell mean RSS value from each reference node is measured and uniquely associated
with that cell’s identity.
The pseudocode for offline phase (also called calibration phase) is provided here for
fingerprinting approach. The quality of radio-map would determine the precision and
accuracy of position estimation of a mobile device. Therefore more the number of points
where signal features are collected i.e. the richer the database, better would be the outcome of
Survey On Indoor Localization: Evaluation Performance of Bluetooth Low Energy and Fingerprinting
Based Indoor Localization System
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localization results. Hence for good localization performance, an extensive site survey
(offline phase) should be conducted. This requires that fingerprints of numerous points (with
high resolution) in the localization space should be gathered.
4.3. Online Phase
In the online phase measurements taken at the current location (in the localization space) are
matched with the already-established database (or radio-map) from the offline phase. The
position estimation of a mobile device is done by matching the current position’s signal
feature with the fingerprint (signal features) of each cell in the database. The cell whose
signal feature is closest to mobile device’s current location’s signal feature is obtained and the
coordinates of the midpoint of that cell are estimated as the 2D position of the mobile device.
One problem with fingerprinting-based localization approach is that indoor environments
are dynamic and collection of signal features in offline phase may not account for the change
of indoor environment via indoor decoration, furniture, or walking of people which might
have happened at the time of online phase measurements. This can severely affect
localization performance.
The following figure of an architecture taking the BLE based indoor localization of
fingerprinting approach is assumed.
Figure 3 An architecture showcasing how fingerprinting based indoor localization would work
5. CONCLUSION
The attention in the direction of the indoor localization is quite large in the literature and
more and more efforts are made to explore further operative explanations which are able to
overcome the limitations of the technologies which could be applied. Selection of the
appropriate technology, or a combination of them, varies in circumstance and depends on
both the explicit application framework and user necessities in relation to precision, coverage
area, price, obligatory set-up, robustness, scalability, and so on. Actually, a solution that is
appropriate for a specific state, can indicate to failure for another. This paper is envisioned to
deliver an outline on latest technologies for tracking and positioning in an indoor
environment. Particular attention has been turned to systems for indoor positioning based on
fingerprinting approach of iBeacon technology and how they operate.
Gemechu Wako Samu and Prachi Kadam
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