IoT Embedded System Communications for Wireless Underwater Depth and Temperature Monitoring

Abstract

This paper presents an embedded wireless Internet of Things architecture, integrating real time embedded systems that communicate underwater through acoustic signals. The proposed architecture is based on an ultra-low-power Flash Micro-controller that manages communications with sensors, and synchronization between the whole system through wireless radio link. The developed system was tested with water depth and temperature sensors monitoring. Sensed data is gathered to the main station by means of wireless acoustic pulses, sent by transmitters through water. The transmitter and the receiver acoustic chains are based on a Digital Signal Processor. The receiver acoustic board is connected to a local server implemented on a RaspberryPI unit.

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www.ijaceeonline.com ISSN: 2456 - 3935
International Journal of Advances in Computer and Electronics Engineering
Volume: 2, Issue: 7, July 2017, pp. 21–28
International Journal of Advances in Computer and Electronics Engineering, vol. 2, no. 7, pp. 22-28, July 2017
IoT Embedded System Communications for
Wireless Underwater Depth and Temperature
Monitoring
Redouane Es-sadaoui
Research Scholar, Embedded System Design Laboratory, National Institute of Posts and
Telecommunications, Rabat, Morocco
Emails: red.essadaoui@gmail.com
Lahoucine Azergui, Mohammed Guermoud
Embedded system Engineers, Cadi Ayyad University, Marrakech, Morocco
Emails: lahoucine.azergui@uca.edu.ma, mohammed.guermoud@uca.edu.ma
Dr. Jamal Khallaayoune, Samir Bouaazzaoui
Associate Professor, National Institute of Posts and Telecommunications, Rabat, Morocco
Software Engineer, National Institute of Posts and Telecommunications, Rabat, Morocco
Emails: laayoune@inpt.ac.ma, bouazzaouisamir1@gmail.com
Tamara Brizard
Managing Director, Arkeocean S.A.R.L, Aspremont, France
Email: tamara.brizard@arkeocean.com
Abstract: This paper presents an embedded wireless Internet of Things architecture, integrating real time
embedded systems that communicate underwater through acoustic signals. The proposed architecture is based
on an ultra-low-power Flash Micro-controller that manages communications with sensors, and synchronization
between the whole system through wireless radio link. The developed system was tested with water depth and
temperature sensors monitoring. Sensed data is gathered to the main station by means of wireless acoustic
pulses, sent by transmitters through water. The transmitter and the receiver acoustic chains are based on a
Digital Signal Processor. The receiver acoustic board is connected to a local server implemented on a
RaspberryPI unit.
Keyword: IoT; wireless acoustic communication; underwater sensors; embedded systems.
1. INTRODUCTION
Internet of Things (IoT) represents the interconnec-
tion, through the Internet, of a large number of things,
uniquely identifiable physical objects with sensing,
communication and actuation capabilities. The term
has been introduced by Kevin Ashton in 1999 in the
context of chain supply management [1]. In others
words, IoT is considered as a network of devices that
integrates a large number of physical objects that are
connected to internet which enable these objects to
collect and exchange data, in the aim to transform any
object in the real-world into a computing device that
has sensing, communication and control capabilities
[2].
The majority of the earth’s surface is covered by
sea. The emergence of wireless underwater acoustic
sensors provides new opportunities for the exploration
of natural undersea resources and gathering of scien-
tific data in collaborative monitoring missions. Vari-
ous systems have been studied in terrestrial IoT sen-
sors, however, they cannot be applied directly to un-
derwater sensor because of attenuation of Global Po-
sitioning System (GPS) and Radio Frequency (RF)
signals underwater, which makes the IoT underwater
particularly challenging.
This paper presents the design and experimenta-
tions of an IoT platform that integrates depth and wa-
ter sensors, Digital signal processors, Flash micro-
controllers, wireless radio link, RaspberryPI and
acoustic transmitters and receiver chains. The rest of
paper is organized as follows. Section 2 gives a re-
view of literature on IoT, underwater sensor synchro-
nization and water depth measurement. In Section 3,
Cite this paper:
R. Es-sadaoui, L. Azergui, M. Guermoud, J. Khallaayoune, S.
Bouaazzaoui, T. Brizard, “IoT Embedded System Communications
for Wireless Underwater Depth and Temperature Monitoring”,
International Journal of Advances in Computer and Electronics
Engineering, Vol. 2, No. 7, pp. 21-28, July 2017.

ISSN: 2456 - 3935
International Journal of Advances in Computer and Electronics Engineering
Volume: 2, Issue: 7, July 2017, pp. 21–28
www.ijaceeonline.com 22
the proposed architecture is described. In Section 4,
we present the result of experiments. Finally, in Sec-
tion 5, a conclusion is given.
2. LITERATURE REVIEW
2.1 IoT sensors
The number of IoT applications is growing in many
areas including smart home, healthcare monitoring,
smart city, utilities, smart agriculture, security, smart
water, industrial control, environment monitoring, and
more. The integration of things in the internet is chal-
lenging because they may have characteristics such as
limited memory, processing capacity and energy re-
sources [3] [4] [5].
In the paper [6], authors discussed architectures and
technical aspect related to IoT. They gave a survey of
IoT technologies, protocols and applications. a
framework integrating different protocols was also
given.
Paper [7] proposed a wireless temperature moni-
toring system based on ZigBee module. authors
showed the capability of the system to solve wiring
issues, limited adaptability, and others issues related
to distributed wireless temperature monitoring system.
Vu Chien Thang proposed in [8] a solution for wa-
ter factories in Vietnam using automatic meter read-
ing technology. Author realized a prototype of water
meters and water quality meters for water factories in
Vietnam.
According to [9], [10], there are number of hard-
ware IoT platforms. Table I lists the most popular
brands of IoT boards and their characteristics.
2.2 Radio Synchronization
Paper [11] presented an acoustic based time syn-
chronization method for underwater sensor networks
to resolve problems related to messaging time stamp-
ing, node mobility and Doppler scale effect, where
they compare many message time stamping algo-
rithms in addition to different Doppler scale estima-
tors. In time based systems, synchronization depends
on message exchange between nodes to be synchro-
nized.
In [12], authors took into account node’s move-
ment, basing on the DA-sync like protocol, by using
first order kinematic equations, which tune Doppler
scale factor estimation accuracy, and give a good syn-
chronization performance. In this article, the authors
propose to modify both time-stamping and Doppler
scale estimation procedures. Many simulations and
real tests are performed in a water test tank and a
shallow-water test in the Mediterranean Sea.
Paper [13], by Z. Guo et al., proposed a new frame
synchronization approach based on Linear Frequency
Modulation signal parameters estimation, considering
the problem of false frame synchronization for un-
derwater acoustic communication. The author’s me-
thod showed its capability to locate the frames of the
received signal efficiently, with no reduction of data
rate, and it is low-computational cost because of algo-
rithm simplicity. This paper addressed many simula-
tion and experimental results to show the performance
of the proposed method.
S. Kim and Y. Yoo suggested in [14] new time
synchronization protocol called “SMP-sync” based on
sea environment characteristics. To show the weak-
ness of traditional time synchronization, authors de-
fined error factors over linear regression and proposed
a method to correct those errors. The effectiveness of
this method is the exploitation of seawater features
such the water movement, and node deployment.
Also, this protocol removes channel access delay from
the timestamp to add more time accuracy. The SMP-
Sync is battery friendly; because it conducts time syn-
chronization with smaller transmission and reception
times compared with previous works.
F. Hong et al. described in the paper [15], a scala-
ble synchronization protocol for multi-hop USWNs
called MulSync, taking in consideration the acoustic
communication limitations and restricted mobility of
sensor nodes, and resolving many problems in exist-
ing time synchronization protocols. MulSync includes
the synchronization communication scheme to exploit
acoustic communication nature of broadcast. Simula-
tion results demonstrated its high accuracy at low
message overhead and time cost.
2.3 Water depth sensors
There are a wide variety of ways to produce a sig-
nal that tracks the depth of water in a specific part of
the sea. Ultrasonic detectors find the distance between
seabed to the surface of the water. To measure level,
depth, with an ultrasonic range detector, the module is
mounted at the bottom of the sea, seabed, looking up
the surface. We must measure the time between the
transmitted pulse and the echo received pulses. Since
the ultrasonic signal is traveling at the speed of sound,
the time between transmission and echo received is a
measure of the distance to the surface, water depth.
Paper [16] presented an architecture of depth mea-
surement based on the ultrasonic waves and a micro-
controller. The micro-controller sends a pulse to the
ultrasonic module then the modules start sending a
wave for a short time and wait for the echo. The depth
is estimated by using the difference between the time
of sending pulse and that of receiving the echoes.
Paper titled "Real-Time Monitoring Method of
Water Depth Using Oblique Incidence Sonar in Har-
bour Channel" [15] proposed a novel real-time moni-
toring method using the oblique incidence sonar to
realize an in-situ measurement of water depth in har-
bour channel. By making the use of the multipath
propagation structure of underwater acoustic channel,
the method obtains the depth values by calculating the
relative time delay of acoustic signals between the

ISSN: 2456 - 3935
International Journal of Advances in Computer and Electronics Engineering
Volume: 2, Issue: 7, July 2017, pp. 21–28
www.ijaceeonline.com 23
direct and the shortest bottom reflected paths.
3. PROPOSED ARCHITECTURE
3.1 Combined sensor architecture
The combined sensor architecture, presented in
Figure 1, is based on an ultra-low-power consumption
flash microcontroller (Flash MCU) that features a
powerful 16-bit Reduced Instruction Set Computing
"RISC" architecture, 16-bit registers, and constant
generators that contribute to maximum code effi-
ciency. The temperature sensor is immersed under-
water to measure the temperature of the environment.
The depth sensor measures the water depth based on
the echoes received from the seafloor. The radio tran-
sceiver is used to communicate between systems on
the surface. The sensed temperature and depth is
transmitted through water to a distant receiver by
means of an acoustic transmitter that incorporates a
piezo-ceramic sensor (Acoustic transceiver antenna)
to transform electrical signals to mechanical vibra-
tions transmitting through water.
The Flash MCU manages the communication with
the depth sensor, the temperature sensor, the radio
transceiver and the acoustic transmitter.
TABLE I. IOT PLATFORMS SURVEY
Features
Raspberry Pi 3
BeagleBone
Black
Arduino Yun
UDOO
SoC/ CPU
roadcom BCM2837
and
ARM Cortex-A53
64-b Quad Core
AM335x ARM
Cortex-A8
ATmega32U4+Atheros
AR9331
ARM Cortex-A9 and
Atmel SAM3X8E
ARM Cortex-M3
Clock speed
1.2 GHz
1 GHz
16 MHz and 400 MHz
1 GHz
GPU
BCM VideoCore IV
400 Mhz
BCM Video-
Core IV 400
Mhz
no
Vivante GC 2000 for
3-D + GC 355 for 2-D
(vector graphics)
+ GC 320 for 2-D
RAM
1 GB LPDDR2
512 MB DDR3
64 MB DDR2
1 GB DDR3
Storage
Micro SD
4 GB 8-b
eMMC, micro-
SD
32 KB and 16 MB + micro-
SD
Micro SD
USB Ports
4
1
1
2
Ethernet
IEEE 802.3 10/100
Mb/s
IEEE 802.3
10/100 Mb/s
IEEE 802.3 10/100 Mb/s
IEEE 802.3 10/100
Mb/s
WiFi
IEEE 802.11 b/g/n
no
IEEE 802.11 b/g/n
IEEE 802.11 b/g/n
Bluetooth
Bluetooth 4.1 LE
no
no
no
HDMI
yes
yes
no
yes
OS Supported
Raspbian, Windows
10 IoT Core, Ope-
nELEC, OSMC,
Pidora, Arch Linux,
RISC OS, Ubuntu
Debian, An-
droid, Ubuntu
OpenWrt-Yun (based on
GNU/Linux)
UDOObuntu, An-
droid, XMBC,
Yocto, Arch Linux,
OMV
communication
4xUART, 2x SPI,2x
I2C, 2x CAN BUS
1x SPI, 2x I2C,
PCM/I2S,
1xUART
I2C, UART
SPI, I2C, UART,
CAN BUS
Price
$35
$49
$58
$135
Figure 1 Diagram block showing the combined sensor components

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Figure 2 Diagram block showing the host component
3.2 Host Architecture
The host architecture, presented in Figure 2, incor-
porates a fixed-point digital signal processor (DSP)
based on an advanced modified Harvard architecture
which provides an arithmetic logic unit (ALU) with a
high degree of parallelism, application-specific hard-
ware logic, on-chip memory, and additional on-chip
peripherals.
The radio transceiver is installed to communicate
with combined sensors on the surface. Once im-
mersed, the acoustic pulses coming from the com-
bined sensors are received through the acoustic re-
ceiver chain. When a pulse is detected, the DSP com-
putes the Time of Arrival (ToA) of received pulses
and interprets the values of temperature and depth
sent by each combined sensor. computed data is
communicated via Ethernet port to the RaspberryPI
local server.
4. SYSTEM DEVELOPPEMENT AND
EXPERIMENTS
3.1 Temperature monitoring
Figure 3 illustrates a block diagram of the temper-
ature monitoring module. The Flash MCU collects the
surrounding environment sensed data from the tem-
perature sensor, then sends measurements to Raspber-
ryPI server through Wi-Fi. Figure 4 shows the plot of
some real measurements stored by the server.
Figure 3 Performance value against input parameter
Figure 4 Performance value against input parameter
3.2 Water depth measurement
Figure 5 shows a simplified block diagram of the
water depth sensor chain. In order to perform water
depth measurement, the Flash MCU triggers the
transmission of an ultrasonic wave by setting a control
command to the echo sounder electronic board. When
the echo pulse is received, the Flash MCU processes
the time difference between the transmitted pulse and
the echo pulse and computes the distance to the
seabed.
The depth measurement is repeated many times in
order to get an accurate depth values. In the first
stage, the obtained measurements are buffered into
Flash MCU memory.
4.2 Radio Communications
The RF hardware structure is typically based on
Flash MCU and a RF module as shown in Figure 6.
Our design is mainly composed of two parts: The
Flash MCU and the radio transceiver. The Flash MCU
manages the interface to the radio transceiver. The
wireless link is ensured by a low-cost RF module with
built in stack management and full support for low
power mode, it can communicate with the Flash MCU
through Serial Protocol Interface (SPI). During our
tests, we used batteries to provide a stable power

ISSN: 2456 - 3935
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supply to the RF module. Figure 7 describes the dif-
ferent level of the software developed on the Flash
MCU for radio communication. Many considerations
have been taken into consideration in order to build
our module, such as:
 How many connected objects will participate
the wireless network?
 What is the maximum range between con-
nected objects?
 Is the RF module has any low power features?
Figure 5 Waster depth measurement setup
Figure 6 Radio Interface to MCU
Figure 7 Radio Development levels
4.3 Power management
It is essential to have an IoT low power application,
in order to maximize the power supply autonomy of
the actual system. This section discusses the result of
the study and experiments realized on the improve-
ment of the system power consumption by integrating

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a sleep mode in order to save energy. Table II depicts
the estimated current consumption of the MCU run-
ning a firmware to read data sensed by the tempera-
ture sensor and to transmit the measurement to the
Raspberry Pi server.
TABLE II. CURRENT CONSUMPTION MODES SUPPORTED
INTO FLASH MCU
MCU mode
Current consumption
Busy mode
100 mA
Sleep mode
0.001 mA
Duty mode
20 mA
Experiments have been performed in order to eva-
luate the performance of the system in terms of power
consumption: The first experiment consists of a busy
mode configuration that set the Flash MCU running
continuously in active state. In the second experiment,
the duty mode is enabled by using a duty cycle be-
tween the busy and the sleep states. Figure 8 give a
comparison between the busy and the sleep mode.
The duty mode is then selected for the actual system.
Figure 9 shows a real measurement obtained a
4.5Volts Alkaline battery. The batteries autonomy is
estimated depending the transmission cycle that cor-
responds to the frequency of reading data from sensor
and transmit it to the server through wifi. refer to Fig-
ure 10.
Figure 8 Estimation of Battery discharge rate depending the
two MCU mode: Busy mode and Sleep mode 1.
4.4 Power management
The developed system was tested during sea trials,
performed in BOUREGREG MARINA, located at the
mouth of the Bouregreg River, on the shore of SALE,
Morocco. This location provides an easy-to-access
environment for experimental tests (Figure 11). The
combined sensor and the host receiver were spaced
with a maximum range of 500 meters. The sea expe-
riments have been conducted successfully and showed
the ability of the combined sensor to transmit the
sensed data to the acoustic receiver.
Figure 9 Real measurements of battery discharge rate
Figure 10 Real Estimated battery autonomy
Figure 11 Marina bouregrag map showing the location of
the experimental setup
5. CONCLUSION
In this paper, we addressed some of the most im-
portant points of IoT platforms and sensor networks

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applied in underwater environment: Water depth and
temperature sensing, synchronization between sen-
sors, power management and acoustic communica-
tion. The developed system integrates an ultrasonic
ranging module for water depth measurement and a
temperature sensor.
A novel method was proposed to synchronize sen-
sors through radio link. The Laboratory and sea water
tests results illustrated the ability of the system to
gather the sensed depth and temperature measure-
ments to a local host server, installed on Raspberry PI
unit.
In order to reduce the power consumption of the
actual system, a duty mode that alternates between
active and sleep mode was tested and qualified de-
pending the frequency of transmission. The presented
platform will be improved in the future by including
algorithms to localize sensors underwater in reference
to GPS coordinates and add more sensors to the actual
system.
6. ACKNOWLEDGEMENTS
We would like to thank the Bouregrag Marina staff,
for giving us permission and support to perform sea
trials.
REFERENCES
[1] Ankush B. Pawar and Shashikant Ghumbre (2016), "A
survey on IoT applications, security challenges and counter
measures," 2016 International Conference on Computing,
Analytics and Security Trends (CAST), pp. 294-299.
[2] Dan Dragomir and Laura Gheorghe, "A Survey on Secure
Communication Protocols for IoT Systems," 2016
International Workshop on Secure Internet of Things (SIoT),
Heraklion, Greece, 2016, pp. 47-62. doi:
10.1109/SIoT.2016.012
[3] Machina Research, IoT Global Forecast & Analysis 2015-
2025. Retrieved date [ August, 2016] online available at:
https://machinaresearch.com/news/press-release-global-
internet-of-things-market-to-grow-to-27-billion-devices-
generating-usd3-trillion-revenue-in-2025.
[4] Karimunnisa Begum and Sunanda Dixit, "Industrial WSN
using IoT: A survey," 2016 International Conference on
Electrical, Electronics, and Optimization Techniques
(ICEEOT), Chennai, 2016, pp. 499-504.
[5] McKinsey, “Unlocking the potential of the Internet of
Things”, Retrieved date [ 2015] online available at
http://www.mckinsey.com/insights/business_technology/the_
internet_of_things_the_value_of_digitizing_the_physical_wo
rld.
[6] [ Sajjad Hussain Shah and Ilyas Yaqoob, "A survey: Internet of
Things (IOT) technologies, applications and challenges,"
2016 IEEE Smart Energy Grid Engineering (SEGE),
Oshawa, ON, 2016, pp. 381-385. doi:
10.1109/SEGE.2016.7589556
[7] Andrii Polianytsia and Olena Starkova, "Survey of hardware
IoT platforms," 2016 Third International Scientific-Practical
Conference Problems of Infocommunications Science and
Technology (PIC S&T), Kharkiv, Ukraine, 2016, pp. 152-
153. doi: 10.1109/INFOCOMMST.2016.7905364
[8] Vu Chien Thang, “A Solution for Water Factories in Vietnam
Using Automatic Meter Reading Technology”, International
Journal of Advances in Computer and Electronics
Engineering, Vol. 2, No. 6, pp. 15-20, June 2017
[9] Lai Wei and Shuqin Zhang, "Wireless temperature monitoring
system based on FBG and Zigbee," 2016 15th International
Conference on Optical Communications and Networks
(ICOCN), Hangzhou, 2016, pp. 1-3. doi:
10.1109/ICOCN.2016.7875806
[10] Kiran Jot Singh and Divneet Singh Kapoor, "Create Your
Own Internet of Things: A survey of IoT platforms.," in IEEE
Consumer Electronics Magazine, vol. 6, no. 2, pp. 57-68,
April 2017. doi: 10.1109/MCE.2016.2640718
[11] Oriol Pallares and Pierre-Jean Bouvet, "TS-MUWSN: Time
Synchronization for Mobile Underwater Sensor Networks,"
in IEEE Journal of Oceanic Engineering, vol. 41, no. 4, pp.
763-775, Oct. 2016.doi: 10.1109/JOE.2016.2581658
[12] Jun Liu and Zhaohui Wang "DA-Sync: A Doppler-assisted
time-synchronization scheme for mobile underwater sensor
networks" IEEE Trans. Mobile Comput. vol. 13 no. 3 pp.
582-595 2014.
[13] Sungryul Kim and Younghwan Yoo, "SMP-Sync: Time
synchronization using seawater movement pattern for
underwater wireless networks," 2014 International
Conference on Computing, Networking and Communications
(ICNC), Honolulu, HI, 2014, pp. 842-846.doi:
10.1109/ICCNC.2014.6785447
[14] Feng Hong and Bozhen Yang, "Time synchronization for
underwater sensor networks based on multi-source beacon
fusion," 2014 20th IEEE International Conference on Parallel
and Distributed Systems (ICPADS), Hsinchu, 2014, pp. 218-
224. doi: 10.1109/PADSW.2014.7097811
[15] Peng Hou and Wenhai Xu, "Real-time monitoring method of
water depth using oblique incidence sonar in harbour
channel," 2009 9th International Conference on Electronic
Measurement & Instruments, Beijing, 2009, pp. 2-761-2-765.
doi: 10.1109/ICEMI.2009.5274462
[16] Shahram Etemadi Borujeni, "Ultrasonic underwater depth
measurement," Proceedings of the 2002 Interntional
Symposium on Underwater Technology (Cat. No.02EX556),
2002, pp. 33-36. doi: 10.1109/UT.2002.1002376
Authors Biography
Reoduane Es-sadaoui, is a
Ph.D candidate at The National
Institute of Posts and Tele-
communications, Rabat, Mo-
rocco. He completed his Engi-
neer degree in department of
Electrical Engineering, Cadi
Ayad University, Marrakech,
Morocco. He worked for four
years as a Research and Devel-
opment engineer in the domain of underwater embedded
system and real-time software engineering. His research
interests are underwater embedded systems, Wireless
Acoustic communications and signal Processing.
Lahoucine Azergui, is an
Embedded System Engineer.
He completed his BE in Em-
bedded systems department at
the Cadi Ayyad University of
Marrakesh. His research inter-
ests are Internet of Things,
electronic devices, communi-
cation systems.

ISSN: 2456 - 3935
International Journal of Advances in Computer and Electronics Engineering
Volume: 2, Issue: 7, July 2017, pp. 21–28
www.ijaceeonline.com 28
Mohammed Guermoud, is an
Embedded System Engineer.
He completed his BE in Em-
bedded systems department at
Cadi Ayyad University of Mar-
rakesh. His research interests
are signal processing and Radio
communication.
Samir Bouazzaoui, is a soft-
ware developer in Telecommu-
nication and networks Engi-
neer. He completed his BE in
Telecommunication Depart-
ment of at the National Institute
of Posts and Telecommunica-
tions, Rabat, Morocco. His
research interests are Wireless
communications and networks.
Dr. Jamal Khallaayoune, is an
associate Professor of embed-
ded systems at Department of
Electronics, micro-waves and
optics, at the National Institute
of Posts and Telecommunica-
tions, Rabat, Morocco. He
completed Ph.D in microelec-
tronics, in 1988, from the Gre-
noble Alpes University, Gre-
noble, France. He completed a
second Ph.D in underwater communication and acoustic
guidance, in 2001, from the University Mohammed V,
Rabat, Morocco. His research works are related to
microelectronics, real time embedded systems, signal
processing and underwater acoustic guidance.
Tamara Brizard, is a manag-
ing director, specializes in re-
search and development of
underwater acoustic positioning
and communication systems.
She completed a Bachelor of
Science (B.S.) in electrical and
computer engineering and a
B.S. in Evolutionary Anthro-
pology from Rutgers Univer-
sity, New Jersey, United States.
Cite this paper:
R. Es-sadaoui, L. Azergui, M. Guermoud, J. Khallaayoune, S.
Bouaazzaoui, T. Brizard, “IoT Embedded System
Communications for Wireless Underwater Depth and
Temperature Monitoring”, International Journal of Advances
in Computer and Electronics Engineering, Vol. 2, No. 7, pp.
21-28, July 2017.
.