A Wireless Sensor Network as a Living Lab for the Development of

Solutions for IoT and Smart Cities

Jorge Arturo Pardiñas-Mir, Luis Rizo-Dominguez and Luis Eduardo Pérez-Bernal

Department of Electronics, Systems and Informatics, ITESO University, Periférico Sur 8585, 45604, Tlaquepaque, Mexico

Keywords: Wireless Sensor Networks, Internet of Things, Living Lab.

Abstract: As internet connectivity and digital solutions spread all over, it has become necessary to have the possibility

of experimenting and developing solutions for the Internet of Things (IoT) into a laboratory with similar

conditions as those of the big scale application. Living Labs are a solution for such a need and in this paper

we present the implementation of a living lab based on a wireless sensor network (WSN) aimed to help the

learning of this technology by giving the opportunity of experimenting and developing solutions. The WSN

works primarily on the ZigBee protocol but, being an educational and developing tool, it also permits to add

devices working in other protocols like WiFi, 3G and Sigfox, that we have already experienced. The system

includes the possibility that the collected data be kept into an internet server and be able to be displayed to

users through a mobile application.

1 INTRODUCTION

As internet connectivity and digital solutions spread

all over, it has become necessary to have the

possibility of teaching, research, and develop

solutions for the Internet of Things (IoT) into a

laboratory with similar conditions as those of the real

big scale application. This need has been identified in

the scientific community, so several efforts have been

invested in that direction. We think that despites the

many meanings given to the term “Living Lab”, for

example in (Del Vecchio et al., 2014), (Vicini et al.,

2013), and (Tang and Hämäläinen, 2012) among

others, it is adequate to describe such a kind of

facility, as defined by (Eriksson et al., 2006): “a user-

centric research methodology for sensing,

prototyping, validating and refining complex

solutions, in multiple and evolving rea life contexts”.

In (Chin and Callaghan, 2013) it is argued that

Internet-of-Things is a perfect platform for teaching

computer science and it proposes a Living Lab

approach based on combining concepts taken from

iCampus, Smart Box ad Pervasive-interactive-

Programming (PIP). They show that their methods

have a good potential for introducing students to

programming in a way that is simple and motivating.

An experiential learning program, Living Lab,

which provides real world experience in all aspects of

information technology to students, is presented in

(Justice and Do, 2012). It helps students to develop

modern technological skills, effective oral and written

communications skills, and the ability to perform well

in teams. The development of a wireless sensors and

controllers network for training students in

Automation is described in (Katsaounis et al., 2014).

This is a chance for students to keep in touch with a

small-scale implementation of a hybrid network. An

educational platform for promoting awareness of lake

environmental protection is presented in (Wang et al.,

2016). It is based on Internet of Things and wireless

sensor network technologies, monitoring water

quality of lakes and providing data analysis of lake

pollution.

In this paper, we describe our approach to the

implementation and launching of a Wireless Sensor

Network (WSN) as a support for teaching and

research on issues related to the Internet of Things. It

has the aim of also being a “Living Lab” allowing the

development and testing of solutions under real

conditions that facilitate its implementation in a larger

scale. This project is not focused on a particular

course, but it allows experiencing many topics related

to the internet of things. Students can use the system,

for example, to develop the final project of a sensor

course, or to demonstrate the operation of a

microcontroller that performs some function within

the network. There are students involved in

Pardiñas-Mir, J., Rizo-Dominguez, L. and Pérez-Bernal, L.

A Wireless Sensor Network as a Living Lab for the Development of Solutions for IoT and Smart Cities.

DOI: 10.5220/0006915103030308

In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications (ICETE 2018) - Volume 1: DCNET, ICE-B, OPTICS, SIGMAP and WINSYS, pages 303-308

ISBN: 978-989-758-319-3

303

application projects related to sensor networks and

mobile applications. Some of the topics that this

framework allows to study are the four core

technologies normally embodied in currently IoT

systems: embedded computing, sensors, networking,

and cloud computing (Dickerson, 2017). The

teaching of these technologies are mainly aimed to

students of the following bachelor programs:

Electronic Engineering, Computer Systems

Engineering, Information Security and Network

Engineering, and Engineering in Service Companies.

Our system was developed based on the

monitoring of environmental conditions of the

university campus, taking into account the main

technical subjects required in learning and working

with Internet of Things projects. On the one hand, a

wireless network has been developed that monitors

the temperature and humidity of the soil in different

points of the campus gardens. This goal took into

account the university needs related to maintaining in

good health the gardens and trees of the campus. The

collected information is placed in the hands of the

university authorities for analysis and undertake of

appropriate action. On the other hand, independent

wireless nodes have been added that communicate

directly with the system, bypassing the wireless

network, to provide information on specific aspects

or to allow the use of a different technology.

The architecture of the implemented system and the

description of the elements related to the management

of collected data, its storage and availability on the

Internet was presented in (Perez et al., 2015). This

paper focuses on the development and

experimentation of the wireless sensor network and

its communication with the system.

Section 2 describes the architecture of the system

as a whole. Section 3 presents the network

development and section 4 describes some tests and

results. Finally, the conclusions include some ideas

about future work.

2 SYSTEM’S ARCHITECTURE

The Living Lab System for the Development of

Solutions for IoT and Smart Cities is a system

operating in a university campus, aimed to measure

mainly environmental variables of the campus. The

system is composed of 3 main elements, Figure 1: the

wireless sensor network, the acquisition and storage

internet service and the information retrieval service.

 The wireless sensor network is in charge of

collecting the data through several sensor

nodes around the campus. The first series of

installed nodes has the capability of

measuring soil’s temperature and moisture.

This information is sent from each node to the

network coordinator who, acting as a

gateway, send the data to the system server in

internet.

 The acquisition and storage of data on the

web, is an internet service being in charge of

the system server. It keeps track of each node,

stores the collected information in a database,

and it also manages everything related to the

network, like adding and deleting nodes,

sensor variables to be measured, and

assigning a location to each node.

 The retrieval of information is the server’s

section providing real time data collected by

the nodes. It also allows generating data

reports. The data can be consulted and

displayed through a web page or through a

mobile application via internet.

Figure 1: Elements of the system.

The information system design also allows having

independent nodes sending its data directly to the

server, without belonging to the wireless network,

allowing testing special sensor nodes configurations

or new sensor technologies.

The university campus, where the system is

installed, has a surface of over 41 hectares of which

22 are green areas: gardens and trees. It is a polygon

with approximately 530 meters wide and 715 meters

long. It exists at the campus over 3,000 trees of about

280 species. In the first stage of development of our

system, the wireless network was installed in a

delimited area, allowing easily ensuring and

monitoring its operation. The system is then a

laboratory the size of the campus, with a network of

sensors and an information system in operation. The

system allows to easily experiencing topics related to

the internet of things in an integrated manner:

embedded systems, sensors, powering and energy

consumption in sensors, use of communication

systems for sensors, web services, front-end, back-

end, and cloud computing. The services related to the

information systems have already been described in

(Perez et al., 2015), while in this paper we will focus

in describing the wireless sensor network, its

operation, experiments and results.

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3 WIRELESS SENSOR

NETWORK DEVELOPMENT

The wireless network was developed with an initial

application target: measuring humidity and

temperature of soil, under the requirements of the

university office in charge of campus facilities. In this

way, we would achieve first the objective of working

with a real application. At the same time, its

development took into account the possibility of

having an easily growing network and of being

compatible with different technologies. Taking this as

a starting point, it was determined to divide the

development of the network into 3 parts: the choose

of the technology, the architecture of the network and

the sensors to be used.

3.1 Base Technology

It was decided to use a well-known technology as the

basis of the network, which would make it possible to

operate a network of sensors easily and reliably. This

would allow to add new elements little by little and to

try new technologies later. The chosen technology

was the XBee sensor modules from Digi

International, which communicate via the ZigBee

protocol working at the ISM 2.4 GHz band, Fig 2.

Among the features of these modules are being

specifically configurable for activities related to

sensing, like defining the inputs and outputs and the

sampling time. There is available a Pro version with

high transmission power (50mW -17dBm-) and high

receiver sensitivity (-102 dBm) focused on network’s

coordinators and routers and a low power version

with less transmission power (2 mW -3 dBm-) and a

smaller receiver sensitivity (-96 dBm) focused on end

devices. These modules have the possibility of

defining 4 analog inputs and 4 digital input/outputs.

The communication with the module is made through

a serial UART.

Figure 2: XBee ZigBee module physical aspect and block

diagram.

3.2 The Sensor Network

As it is known, a ZigBee network is formed with a

single network coordinator (CN) that controls the

network, routers nodes (RN) that create the links

between all elements in the network and end or

sensor nodes (SN), which are tasked with taking

samples periodically and transmit them to the

network. The implemented WSN uses the two

different ZigBee modules in the network according

to the functions of the nodes. In the case of sensor

nodes, the low power module version is used while

for the routers and coordinator nodes the high power

version is installed instead. The network is

organized in 3 zones, each one with a router in

charge of many sensor nodes. Each router in turn

communicates directly to the network coordinator or

to another router if it is within its range. Fig. 3 shows

the block diagram of such an architecture, where

HS, ST, and TT are the end devices measuring

humidity of the soil, soil temperature and tree

temperature respectively. The latter is a sensor not

yet implemented. The ZigBee protocol allows the

nodes to create automatically the needed links to

form the network.

Figure 3: Topology of the implemented WSN.

3.3 The Sensor Nodes

Each sensor node comprises an XBee low power

version module, working as an end device, a soil

temperature sensor and a humidity soil sensor. We

choose sensors aimed to be applied in real

environments in order to obtain a reliable and useful

behaviour. We selected the Vegetronix THERM 200

and VH400 respectively, shown in Fig. 4. They

output an analog voltage proportional to the

temperature and moisture. Each node is powered by a

3.7 volt battery, which is recharged through a solar

cell. A 3.7V-5V converter powers the sensors. Some

nodes are additionally powered by night. The node is

μC

Tx/Rx

A/D ins

D outs

XBee

serial

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configured to take samples around each 30 minutes,

send it to the router and return to a low activity state

(sleep) until next sampling. The data is transmitted to

the sensor network into a ZigBee frame, which in the

XBee implementation is a 0x92 API frame. One

version of the implemented sensor node is shown in

Fig. 5.

Figure 4: Soil’s moisture and temperature sensors.

Figure 5: The Sensor Node.

3.4 The Gateway

The gateway is composed of a microcontroller and a

Zig-Bee coordinator. The data arriving from the end

devices to the routers is transferred to the network

coordinator. The microcontroller analyses the

received frame and extracts the voltage values

corresponding to the temperature and moisture’s

sensors. These values are converted to the

corresponding temperature and moisture units and

they are placed in the format of a new frame,

recognizable by the system server. A first version of

the Gateway was developed with an Arduino

microcontroller board, using a WiFi shield, Fig. 6. It

was preferred to use WiFi technology to have greater

versatility in the position of the gateway, and increase

the possibilities of experimentation.

Figure 6: The Gateway architecture.

4 RESULTS

4.1 Installation Tests

The installation and operation of the Wireless Sensor

Network was carried out experimenting with different

positions of nodes and distances between them. The

sensor nodes were installed at ground, between the

trees. It was found that a good distance to avoid losing

any frame was in general a maximum of 30 meters. It

is good to remember that the sensor nodes transmit

with a maximum power of 2 mW (3 dBm) and have a

Figure 7: Received power vs distance between the network

coordinator and one router.

Figure 8: The Wireless Sensor Network Architecture.

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receiver sensitivity of -96 dBm. On the other hand,

range tests were made between routers and the

coordinator, both of them transmitting with a

maximum power of 50mW (17dBm) and with a

receiver sensitivity of -102 dBm. Here the distance to

locate routers apart from the coordinator was found to

be around 150 meters. Fig. 7 shows the results of one

of the tests. The final location of nodes into the

network at the test stage is shown in Fig. 8.

4.2 Monitoring of Environmental

Variables

As said before, being the first job of our system to

behave as a Living Lab, the network was designed to

serve the campus authorities to collect environmental

data concerning the health state of gardens and trees

of the campus. With this information, the office in

charge of the campus facilities will have the

possibility of taking actions to improve, for example,

the irrigation system. Additionally to the temperature

and moisture of soil, we have added to the system, as

required by the same office, two different kind of

sensors. One device, a Waspmote Libelium Plug &

Play!, measuring some air pollution gases and

connecting to the ZigBee network. The second device

measures some variables related to the water quality

of the campus water treatment plant. It connects

independently to the internet server through WiFi.

Figure 9 illustrates, as an example, the web

information page showing the graphic of the

Oxydation Reduction Potential values of water,

collected during September 2017.

4.3 Learning Laboratory

As a Learning Laboratory, our system has helped in

the development of training experiences for students

in their last year of engineering, in different technical

areas. This work has been done under real application

conditions. Some of the tasks carried out by the

students have been:

 Design and implementation of a voltage

converter card for analog sensors.

 Programming a ZigBee-WiFi Gateway

using the Waspmote device from Libelium.

 Programming a SigFox enabled sensor node

based on the Freescale (NXP) KL43Z.

 Addition of functions to the server’s data

reception service, such as the automatic time

stamping of the received frames and

improvement of graphics display.

 Improvement of network management tools.

Some of these activities allowed some students to

participate in a project to install a wireless sensor

network in a forest. The objective is to monitor,

within a limited area, the variables that can show the

improvement of soil characteristics. In this project,

we have collaborated with professors from other

areas, such as chemical engineering and

environmental engineering.

Figure 9: Example of webpage showing Oxydation

Reduction Potential values of water.

5 CONCLUSIONS

This paper presents a wireless sensor network that is

part of a system acting as a Living Lab. It helps at the

same time the development and learning of

technology solutions for IoT and Smart Cities under

an easy manageable scale but with similar conditions

as the application implemented at full scale. The

WSN platform was implemented successfully,

allowing the collection of useful data for the care of

the campus gardens. It is ready for experimenting new

technologic approaches or new products. It has

helped students to experience and learn about these

technologies. The system makes it easy to add a new

technology sensor, or to test a new topology, for

example. In the short term, the next steps in the

development of the system are to increase the number

of sensor nodes, to expand the network coverage, and

to give the Gateway more intelligence for doing more

local processing.

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