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 speci cally designed, whereas for BLE a commercial beacon has been chosen. Also, a mobile phone application has been developed which implements the identi cation algorithms for each proposed technology. Once the artwork has been identi ed, 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.
This section describes the beacons used, which are based on three di erent 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 speci cally 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. 118 mm 39 mm arp 123 Sh PC
Adafruit Feather HUZZAH (c) Visible light beacon.
42 mm
STM32L432KC
Acoustic technology o ers 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 con ned 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 NUCLEOL432KC board and a KSSG1708 transducer can be seen. To the left of the gure 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 e ect. 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 di erent 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 di erent 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 nal arrangement on a stand, as well as the beacon's insides, with its
components identi ed, 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 e ect, the high frequency
LED luminaries modulation, and the human eye's inability to perceive them are the basis of this
system [
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 nally be sent to the ampli er 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 rst passed through a matched lter 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 lters. A rst matched lter with the upChirp pattern determines the location of the compressed pulses corresponding to the chirps encoding the 1s, and a second matched lter 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 lters are divided into sections of duration Tb (bit period). Both ltered signals are compared section by section, assigning the value 1 or 0 to the bit depending on whether the absolute maximum value for both ltered signals in the section in question corresponds to the pattern upChirp or downChirp respectively. Finally, an 8 bit binary code will be obtained which identi es 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.
DAC STM32F103CBT6 Microcontroler
STM32L432KC Board AC/DC Converter AudioAmplifier ADC initChirp
Matched Filter
Peak Detector
Data Signal Data Beginning downChirp
upChirp Matched Filter
Peak Detector Matched Filter
Peak Detector
Tb Tb
Decision
Binary Code
Fig. 2: Operating diagram of the transmitter and receiver acoustic modules.
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 e ect and emission frequency changes make measurements disperse and time variant [
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 identi cations. The whole process is shown in Fig. 3, where RSSIi is the output code of the system.
Start
BLE Scanning RSSI Sorting j = 0
no RSSI1 > U1 yes j = 0
no RSSI2 < U2 yes j + +
no j n
yes RSSIi
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 rst 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-o keying (OOK). The LED panel turns o 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 [
(a) Transmitter module.
CRH0#SGT!zahuh3RVSTNCGNDBAADTCENNCUSNCBNC1N4C1N2C13 S1C5K M0O1M6I 2RXST5CXLS4DAPDCHtennaA Feather Huzzah
Sensitivity: max Exposure time: min
Grayscale
Blur
Threshold Reduce
Threshold
Decision
Binary Code (b) Receiver module. phase is a series of zeros and ones that can be processed to decode the message. The third and nal 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
In this section, a performance study of each technology will be carried out. To this end, the e ciency 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 de ned by a grid whose dimensions and spacing depends on the coverage area o ered by each technology. For each test point, the mobile phone has taken 100 consecutive acquisitions of the beacon's identi cation signal, and the percentage of successful detections has been calculated.
The acoustic beacon was studied rst. 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
Beacon (0,0) Grid
Tripod
Receiver (a) Experimental setup. 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 e ect of several factors (combined or not) such as the distance signal attenuation, the relative transmitter/receiver orientation, and the multipath e ect produced by walls, furniture, and oor. 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 oor.
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 [
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 di erences 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
This work has explored di erent 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 speci cally 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 di erent factors that mask or deteriorate the signal. These issues should be addressed in later developments of this work.