=Paper=
{{Paper
|id=Vol-2498/short54
|storemode=property
|title=LIMUS: exploration of technological prototypes for location-based services in museums
|pdfUrl=https://ceur-ws.org/Vol-2498/short54.pdf
|volume=Vol-2498
|authors=Juan Diego Gutiérrez Gallardo,Fernando Aranda-Polo,Teodoro Aguilera Benítez,Fernando Álvarez Franco
|dblpUrl=https://dblp.org/rec/conf/ipin/GallardoABF19
}}
==LIMUS: exploration of technological prototypes for location-based services in museums==
https://ceur-ws.org/Vol-2498/short54.pdf
LIMUS: Exploration of Technological Prototypes for
Location-Based Services in Museums ?
Juan D. Gutiérrez, Fernando J. Aranda, Teodoro Aguilera and
Fernando J. Álvarez
Department of Electrical Engineering, Electronics and Automation
Sensory Systems Research Group (https: // giss. unex. es/ )
University of Extremadura, Badajoz, Spain (06006)
andy@unex.es
Abstract. This paper explores three technologies: acoustic, visible light, and Bluetooth
Low Energy (BLE) to provide Location-Based Services (LBS) in museums or archaeological
sites. Acoustic and visible light beacons have been specifically designed, whereas for BLE a
commercial beacon has been chosen. Also, a mobile phone application has been developed
which implements the identification algorithms for each proposed technology. Once the
artwork has been identified, its information is displayed on the mobile phone screen.
A set of experimental tests has been carried out in order to evaluate the performance of
each technology. Results have shown a robust detection radius of 1.5 m around the acoustic
and BLE beacons, while this radius decreases to 0.5 m for the visible light beacon. Results
have also revealed the existence of some phenomena that worsen the detection quality in
certain areas. This should be addressed in an evolved version of this work.
Keywords: Location-Based Services (LBS), Cell-ID, Acoustics, Bluetooth Low Energy
(BLE), Visible Light, Museum.
1 Introduction
Location-Based Services (LBS) constitute the main reason that has fostered an intense research
activity in the field of Local Positioning Systems (LPS). They can be generally defined as
information services accessible with mobile devices through the mobile network and utilizing
the ability to make use of the mobile device location [6]. In that sense, this work presents the
development of a smartguide for archaeological sites in the Spanish region of Extremadura and
the Portuguese region of the Alentejo (The LIMUS project [4]). This project aimed to design a
common application for all visitors of a number of sites from the aforementioned regions, sites
with very distinct characteristics that may require different tag identification technologies. Three
of these technologies, namely acoustic, Bluetooth Low Energy (BLE), and visible light were finally
selected to conduct a comparative analysis of performance. The results are presented in this work.
The paper is organized as follows. Section 2 details the characteristics and components of
each prototype. Section 3 explains the transmitter and receiver architectures for each technology.
Section 4 presents the main results obtained in the experiments that have been carried out.
Finally, Section 5 highlights the most relevant conclusions drawn from this work.
?
This work was supported in part by the European Commission through the Project LIMUS under
Grant 0246-LIMUS-4-E, in part by the Spanish Government and the European Regional Development
Fund (ERDF) through the Project MICROCEBUS-UEx under Grant RTI2018-095168-B-C54, and in
part by the Regional Government of Extremadura and ERDF-ESF under Project GR18038.
2 Juan D. Gutiérrez et al.
2 Beacons Description
This section describes the beacons used, which are based on three different technologies: acoustic,
BLE, and visible light. For each beacon, its appearance, dimensions, and components are described.
For acoustic and visible light technologies, the beacons have been specifically designed to optimise
the size, price, and quality of emissions. However, for BLE technology, a commercial beacon has
been chosen, since this technology has long been used in mobile phones.
55 mm
42 mm
KC
432
2L
M3
ST 118 mm
55 mm
39 mm
r
Mou r te
n n ve
ted
Bea Audio Co
con Amplifier C
/D
(underside) AC
PC123
Sharp
Adafruit Feather
Transducer HUZZAH
(a) Acoustic beacon. (b) Estimote Proximity BLE bea- (c) Visible light beacon.
con.
Fig. 1: Beacon description for each proposed technology.
Acoustic technology offers numerous advantages when it is used to implement systems that
provide LBS. Among them, the narrow emission cone of the acoustic transducer makes it possible
to discriminate between areas very close to each other. In addition, the acoustic waves will be
confined in each museum room and detections from adjacent rooms will be avoided.
Fig. 1a shows on the right the inside of the beacon where an AC/DC converter, a NUCLEO-
L432KC board and a KSSG1708 transducer can be seen. To the left of the figure can be seen the
beacon mounted inside a plastic box of dimensions 55×55×42 mm. This box has a perforation
that allows the programming of the STM32L432KC module via its Micro-USB port. Furthermore,
the beacon can be connected directly to the mains supply network without having to replace its
batteries periodically.
Finally, this technology is suitable for the emission of robust signals against noise and the
Doppler effect. This robustness makes it possible to implement modulations in long sequences
generating 8 or even 16 bit encoding that can identify a large number of different exhibits.
The BLE beacons used for the LIMUS project are the Estimote BLE Proximity Beacons.
As shown in Fig. 1b, these beacons have a low-power 32 bit and 64 MHz Central Processing Unit
(CPU), a set of sensors (accelerometer, barometer, thermometer, magnetometer and photometer)
and a Bluetooth antenna all over a circuit board. This device is powered by a set of batteries and
wrapped in a plastic color case. Each beacon can broadcast multiple signals at the same time,
using different emission powers and advertising periods. Estimote beacon’s settings can be done
via their smartphone application or cloud service. This beacon is shown in Fig. 1b.
Visible light beacon’s final arrangement on a stand, as well as the beacon’s insides, with its
components identified, is shown in Fig. 1c. In particular, the beacon control and interruption circuit
which modulates the light signal is implemented on a Feather HUZZAH board manufactured
by Adafruit. The combination of the CMOS cameras rolling shutter effect, the high frequency
LIMUS: Exploration of Technological Prototypes for LBS in Museums 3
LED luminaries modulation, and the human eye’s inability to perceive them are the basis of this
system [2]. Thus, it is possible to emit a luminous message without annoying people close to
source.
3 Systems Operation
This section shows the beacons architecture. The transmitter operation for each technology is
presented, as well as the particularities of their own receivers.
Fig. 2 shows the operating diagrams of both the transmitter and receiver modules for the
acoustic technology. The transmitter module consists of an AC/DC converter in charge of
supplying the STM32L432KC board. This board has a microcontroller STM32F103CBT6 that
generates the digital signals. Subsequently, these signals pass through the board’s digital-to-analog
converter (DAC), to finally be sent to the amplifier in order to be synthesized using an acoustic
transducer. The receiver module is implemented in an Xiaomi Mi 8 Android terminal. The phone
acquires the acoustic signals through its embedded microphone. These signals are then processed
by the phone’s analog-to-digital converter (ADC). The resulting signal is first passed through
a matched filter with a synchronization chirp (initChirp). The compressed pulse detection of
this chirp indicates the beginning of the signal fragment where the information of the exhibit to
be decoded is located. To decode this information, this signal fragment will be sent to two new
filters. A first matched filter with the upChirp pattern determines the location of the compressed
pulses corresponding to the chirps encoding the 1s, and a second matched filter now with the
downChirp pattern determines the location of the compressed pulses identifying the 0s of the
binary code. Then, in the decision module, the signals resulting from the matched filters are
divided into sections of duration Tb (bit period). Both filtered signals are compared section
by section, assigning the value 1 or 0 to the bit depending on whether the absolute maximum
value for both filtered signals in the section in question corresponds to the pattern upChirp or
downChirp respectively. Finally, an 8 bit binary code will be obtained which identifies the artwork
in question. In addition, the use of frequencies in the audio’s upper spectrum, together with the
very low power emission that allows the chirp’s pulse compression, makes the emission of these
signals practically imperceptible to the users.
Transmitter Module
DAC
STM32F103CBT6
AC/DC Converter Microcontroler Audio Amplifier
STM32L432KC Board
downChirp
Receiver Module
Tb
Matched Filter Peak Detector
initChirp
ADC Binary
Code
Matched Filter Peak Detector Data Signal Decision
Data Beginning
upChirp
Tb
Matched Filter Peak Detector
Fig. 2: Operating diagram of the transmitter and receiver acoustic modules.
4 Juan D. Gutiérrez et al.
The parameter used for positioning with BLE is the Received Signal Strength Indicator
(RSSI). This value measures signal attenuation in a logarithmic scale and can be obtained from a
smartphone device. RSSI decreases with the square of the distance from the source, but indoors
multipath effect and emission frequency changes make measurements disperse and time variant [1].
The smartphone used as receiver performs a periodic scanning process, searching for other BLE
devices in the surroundings. In each scanning, RSSI results are sorted from highest to lowest.
The output code is the one associated with the first element of the list provided that its RSSI
is above a threshold value, U1 . This value is fixed to detect the code in the proximity of the
beacon, otherwise the system can detect the code even at large distance inside the BLE maximum
transmission range.
There could be situations when nearby beacons have high RSSI readings and all values are
above the threshold U1 . In order to avoid detections in these situations, the RSSI of the second
element of the sorted list must be smaller than a second threshold, U2 . Finally the whole process
must be repeated three times to correctly identify the code and avoid false positive identifications.
The whole process is shown in Fig. 3, where χRSSIi is the output code of the system.
BLE
Start
Scanning
j = 0 j = 0 j + +
no no no
RSSI yes yes
RSSI1 > U1 RSSI2 < U2 j≤n
Sorting
yes
χRSSIi
Fig. 3: BLE proposed code identification.
Fig. 4a shows the operating diagram of the visible light beacon transmitter module, while the
block diagram that describes the acquisition and further signal processing is shown in Fig. 4b.
The transmitter module needs two AC/DC converters, the first for the LED panel, the second
for the Feather HUZZAH development board, which is used to interrupt the power supply with
the help of an optocoupler. The board is programmed to convert the message to a Manchester
encoding via on-off keying (OOK). The LED panel turns off completely to transmit a 0 and lights
up to transmit a 1, at an oscillation frequency of 5 kHz.
The Android app visible light detection module uses the rear camera of the terminal for the
acquisition of the signal. First, the sensitivity of the camera is increased to the maximum, while
its exposure time is reduced as much as possible. As a result, the luminous parts of the captured
scene are more prominent than the rest, giving priority to luminaries. A single photograph is
enough to carry out a complete decoding process. This process is repeated as many times per
second as the capacity of the smartphone allows, twice in this work.
First, the acquired image is converted to gray scale, since only the intensity of the signal, not
its chromatic components, are of interest. Next, the signal noise is reduced using a Gaussian
smoothing function. Finally, a thresholding operation is performed, resulting in a black and white
image. Otsu’s algorithm [3] is applied to obtain the optimal threshold value. The second phase of
processing begins with a reduction operation applied to the image columns, using the average of
all the values. Otsu’s thresholding is reapplied to the value vector obtained. The result of this
LIMUS: Exploration of Technological Prototypes for LBS in Museums 5
5 4
14 12 13 15 0 16 2 SCL SDA
BAT EN USB
#0
Antenna
huzzah!
RST
CHG
NC
NC
RST 3V NC GND ADC NC NC NC SCK MO MI RX TX
CHPD
Feather Huzzah
AC/DC Converter
Switch
(a) Transmitter module.
Grayscale Blur Threshold
Sensitivity: max
Exposure time: min
Binary Code
Reduce Threshold Decision
(b) Receiver module.
Fig. 4: Visible light beacon operating diagrams.
phase is a series of zeros and ones that can be processed to decode the message. The third and
final signal processing phase looks for matches between the sequence of zeros and ones in the
received message and the patterns. If said message is received three times consecutively, it is
considered to be correct and sent as the output of the receiving module.
4 Experimental Results
In this section, a performance study of each technology will be carried out. To this end, the
efficiency of these systems will be studied, evaluating the detection success in the surroundings of
each type of beacon.
As depicted in Fig. 5a, both the beacon and the receiver (mobile phone) are mounted on a
tripod. The beacon is placed at the origin of coordinates and the receiver is moved to the positions
defined by a grid whose dimensions and spacing depends on the coverage area offered by each
technology. For each test point, the mobile phone has taken 100 consecutive acquisitions of the
beacon’s identification signal, and the percentage of successful detections has been calculated.
The acoustic beacon was studied first. The emitting beacon was placed at 1.125 m height on
a stand located at the coordinates origin of a grid with dimensions of 2.4 × 2.4 m2 and spacing of
0.4 m. On the other hand, the mobile phone was installed on an adjustable tripod, matching its
6 Juan D. Gutiérrez et al.
100
2.8 60% 15% 64% 20% 12% 22% 62%
Beacon
2.4 1% 0% 25% 1% 3% 0% 2% 80
Detection Success (%)
Tripod 2.0 24% 24% 28% 63% 76% 13% 2%
Receiver 60
y (m)
1.6 36% 13% 74% 73% 74% 48% 12%
40
(0,0)
1.2 50% 95% 95% 100% 100% 97% 65%
0.8 93% 100% 100% 100% 100% 100% 91% 20
(x,y) 0.4 97% 100% 100% 100% 100% 100% 97%
0
Grid -1.2 -0.8 -0.4 0 0.4 0.8 1.2
x (m)
(a) Experimental setup.
(b) Acoustic beacon.
100 100
2.8 0% 0% 0% 0% 0% 0% 0% 0.8 0% 0% 0% 0% 0% 0% 0%
2.4 1% 4% 6% 9% 4% 2% 0% 80 0.7 0% 0% 0% 0% 0% 0% 0% 80
Detection Success (%)
Detection Success (%)
2.0 35% 30% 42% 49% 22% 34% 28% 0.6 0% 0% 21% 62% 35% 3% 0%
60 60
y (m)
y (m)
1.6 61% 70% 82% 89% 72% 58% 73% 0.5 0% 62% 100% 100% 100% 100% 6%
40 40
1.2 93% 100% 100% 100% 99% 100% 86% 0.4 11% 100% 100% 100% 100% 100% 42%
0.8 100% 100% 100% 100% 100% 100% 100% 20 0.3 26% 100% 100% 100% 100% 100% 67% 20
0.4 100% 100% 100% 100% 100% 99% 100% 0.2 3% 100% 100% 100% 100% 100% 66%
0 0
-1.2 -0.8 -0.4 0 0.4 0.8 1.2 -0.3 -0.2 -0.1 0 0.1 0.2 0.3
x (m) x (m)
(c) BLE beacon. (d) Visible light beacon.
Fig. 5: Experimental setup (a) and results (b), (c), and (d).
microphone height with the one previously established for the acoustic emitter. In this way, both
the transmitter and receiver acoustic axes are aligned. Therefore, a grid of 7 × 7 = 49 points was
obtained with a separation of 0.4 m between each of them. The results are shown in Fig. 5b, where
a robust detection (> 90%) area of approximately 1.2 m radius semicircle around the acoustic
beacon can be observed. Beyond this area it can be noticed how the detection success decreases
due to the effect of several factors (combined or not) such as the distance signal attenuation, the
relative transmitter/receiver orientation, and the multipath effect produced by walls, furniture,
and floor. It is worth mentioning that the row at y = 2.4 m has a detection success practically
null due to the multipath produced by the floor.
For the study of the BLE technology the same experimental setup used for the acoustic
technology was employed. The beacon was placed at 1.175 m height on the same stand and
the same 7 × 7 grid was used for measurements. The mobile phone was placed in an adjustable
tripod, with no further considerations regarding its alignment since mobile and BLE beacon
antenna have uniform polarization [5]. Fig. 5c shows a detection rate higher than 90% in an area
of 1.2 m around the beacon. Beyond this, the detection rate decreases because the RSSI value
LIMUS: Exploration of Technological Prototypes for LBS in Museums 7
is below the U1 threshold. Since consecutive RSSI measurements are very sparse, the change
in the detection rate is not abrupt, with a small region featuring a detection rate around 50%.
The threshold defines an area around the beacon where code detection is expected. Threshold
increase or decrease changes the area with a high detection rate, thus it must be fixed beforehand
according to the location and the minimum separation between exhibits.
A grid of 60 × 60 cm, with cells of 10 × 10 cm, was prepared for testing the visible light beacon
performance. The light source was located 20 cm away from the middle of the grid. The center of
the transmitter was located at 1 m height, as it was the camera optical axis. Both transmitter and
receiver where parallel to each other. Given the differences in coverage between the two previous
technologies and this one, using the same grid for the three experiments would have less accurate
results for the case of visible light. There is a clear limit marked at a distance of about y = 0.5 m
where the success rate decreases rapidly, as shown in Fig. 5d. For longer distances, detection is
unfeasible due to the physical limitations imposed by the size of the emitting source, the camera
resolution, and interference from other light sources present in the environment.
5 Conclusions
This work has explored different Location Based Services (LBS) technologies for mobile phones in
museum environments. Concretely, acoustic technology, Bluetooth Low Energy (BLE), and visible
light have been evaluated. Acoustic and visible light transmitter beacons have been specifically
designed. Since BLE is a consolidated technology, an available commercial beacon has been chosen.
Besides, the design and operation principle of each beacon has been explained. Also, the design
of the mobile phone code detection algorithm for each technology has been described.
Moreover, an experimental study of detection robustness in the surroundings of each beacon
has been carried out. This study shows that both the acoustic technology and BLE beacons have
a robust detection radius of about 1.5 m around the beacon where the percentage of detections is
above 90%. However, the visible light beacon detection radius is lower, around 0.5 m. According
to the results, the three technologies have zones where the detection percentage decreases due to
different factors that mask or deteriorate the signal. These issues should be addressed in later
developments of this work.
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