System for Supporting Implementation and Monitoring of Smart

Campus Applications based on IoT Protocols

Franklin A. M. Venceslau

1 a

, Ruan D. Gomes

2 b

and Iguatemi E. Fonseca

1 c

Federal University of Para

ıba, Jo

ao Pessoa, 58055-000, Brazil

Federal Institute of Para

ıba, Campina Grande, 58432-300, Brazil

Keywords:

Smart Campus, IoT, MQTT, WSNs.

Abstract:

This paper descbribes a system for monitoring Smart Campus applications based on IoT protocols. The system

have as main goals to support the deployment of new sensors, actuators, and gateways in the campus, based

on a pre-deployed network infrasctructure, and to monitor the performance of applications along the time.

The network architecture considered in this paper provides reliability through the use of diversity techniques

at physical and data link layers, based on the IEEE 802.15.4g SUN standard, and it performs the persistence

of information based on time series database. In order to support the network infrastructure evolution and the

incorporation of new devices and applications, information about the currently running applications and about

the quality of the data links and the wireless network’s overload level can be collected by the proposed system.

In this position paper, the architecture of the system is described in details, and initial results are discussed.

1 INTRODUCTION

Currently, several applications for smart cities and

smart campuses have been proposed, for example: in-

telligent transport and lighting and environmental and

energy resource monitoring (Ejaz et al., 2017). Most

of these applications require the use of wireless trans-

mission for communication between the sensing sys-

tems distributed across the city/campus to a central-

ized server. Given this perspective, some solutions

for data transmission that already exist, such as Wi-

Fi, Bluetooth and ZigBee, are often not adequate due

to spatial range limitations.

An alternative may be the use of long-range and

low-power networks, such as LoRa or SigFox (Ve-

jlgaard et al., 2017). Both standards operate in the

Sub-GHz spectrum, acting with efﬁcient modulation

techniques that allow the creation of sparse networks

or networks with star topology, which are easier to

deploy and maintain. However, these solutions have

some disadvantages, since they are proprietary tech-

nologies, and have limited ﬂexibility with regard to

critical communication requirements on different de-

vices. Among these limitations we can mention: in

the case of SigFox, the dependence on an external

https://orcid.org/0000-0003-2203-1708

https://orcid.org/0000-0003-4700-7843

https://orcid.org/0000-0002-5457-7601

service provider in addition to its low transmission

rate, about 600 bps under ideal conditions (Vejlgaard

et al., 2017). In turn, LoRa, is a parameterizable op-

tion according to the spreading factor, however the

maximum bit rate is 21.9 kbps, in the frequency range

licensed in Brazil (Vejlgaard et al., 2017).

Another alternative to implement LPWAN net-

works is the IEEE 802.15.4-2015 standard, which

deﬁnes three different modulation schemes aimed

for applications of smart utility networks (SUN):

SUN-FSK (Frequency-Shift Keying), SUN-OQPSK

(Offset Quadrature Phase-Shift Keying), and SUN-

OFDM (Orthogonal Frequency-Division Multiplex-

ing) (Tuset-Peir

o et al., 2020). Different from LoRa,

this standard is open and offers a greater level of ﬂexi-

bility, since 31 different physical layer conﬁgurations

are supported with bit rates ranging from 6.25 kbps to

800 kbps (Mu

noz et al., 2018). In addition, it consid-

ers both the Sub-GHz and the 2.4 GHz band.

In order to build a scenario for the deployment of

several smart campus applications, a network archi-

tecture was designed with the focus on providing re-

liable communication through the possibility of ap-

plying diversity techniques at the level of modula-

tion and receiver, which is possible by using the IEEE

802.15.4-2015 standard, due to the possibility of us-

ing different modulation schemes and conﬁgurations

in a single transceiver. At the same time, it is ex-

Venceslau, F., Gomes, R. and Fonseca, I.

System for Supporting Implementation and Monitoring of Smart Campus Applications based on IoT Protocols.

DOI: 10.5220/0010346201130119

In Proceedings of the 10th International Conference on Sensor Networks (SENSORNETS 2021), pages 113-119

ISBN: 978-989-758-489-3

113

tremely important to have a way of managing the de-

ployment and evolution of this network infrastructure,

as well as providing the means to monitor the appli-

cations that are running at a given time, to provide

information about reliability, and to verify the feasi-

bility of inserting new devices on the network. In this

context, this work proposes a management system,

which connects to Gateways to conﬁgure and monitor

the network, as well as to offer important information

to support the implementation of new applications for

network evolution.

2 RELATED WORK

Based on a previous bibliographic survey and on the

studies listed as follow, it is observed that there is a

relatively large number of studies that focus, in gen-

eral, on describing monitoring applications (e.g. for

smart energy) using sensor networks. Each study

proposes its own analysis focusing on the techniques

used, carrying out experiments with different IoT pro-

tocols and evaluating the efﬁciency in the data com-

munication.

Based on this perspective, this work gives a new

contribution and aims at the implementation of the

concept of “reuse” of the monitoring infrastructure.

The proposed infrastructure is seen in a more generic

concept, aimed at adding additional layers to provide

a better reliability and availability, through data diver-

sity and persistence techniques.

(Marﬁevici et al., 2017) proposes the implementa-

tion of a WSN (Wireless Sensor Network) to monitor

an internal environment, composed of a small data-

center room taking into account the existence of dif-

ﬁcult factors for an accurate monitoring, for exam-

ple account of the location within an industrial envi-

ronment such as: temperature, ﬂuctuations, noise and

large amount of metallic surfaces that cause a high

level of electromagnetic interference. A report based

on 17 months of observations from 30 wireless sen-

sor nodes was assembled. In this system, tempera-

ture, humidity, air ﬂow level, among other aspects,

were measured. After an initial period, a connectiv-

ity assessment carried out on the network revealed

a high level of noise in some of the nodes, caused

by the presence of different sources of interference.

By increasing the CCA conﬁguration and reallocating

the positioning of some sink nodes, the network was

able to achieve 99.2% reliability in the last 8 months

of monitoring. In this way, it was possible to high-

light the need for the adequate use of reliable tools

and protocols, in addition to the deﬁnition of project

methodologies for managing and deploying WSN in

real-world environments.

(Munoz et al., 2018) makes a very comprehensive

analysis about the IEEE 802.15.4g standard, demon-

strating through experiments some applications and

simulations in indoor and outdoor environments. Sev-

eral tests were carried out in order to obtain range

measurements using the entire scope of the stan-

dard, carrying out experiments with different modu-

lation schemes and covering all parameterization in

the range comprising the range: 863-870 MHz, in

four scenarios many different. The results obtained

with the experiments demonstrated that communica-

tions with a high level of conﬁdence and that use data

rates of up to 800 kbps can be fully achieved in urban

environments at 540 m between nodes, regardless of

the minor interferences.

(Tuset-Peir

o et al., 2020) presents a set of data

obtained from the deployment of a single-hop IEEE

802.15.4g SUN (Smart Utility Network) network (11

nodes) in a large industrial environment (110,044

m2) for a long period of time ( 99 days). The data

set contains 11 M entries with RSSI (Received Sig-

nal Strength Indicator), CCA (Clear Channel Assess-

ment) and PDR (Packet Delivery Ratio) values. The

analyzed results showed a high variability in the mean

values of RSSI (that is, between -82.1 dBm and -

101.7 dbm and CCA (that is between -111.2 dBm and

-119.9 dBm, wich is caused by the effects of multi-

path propagation and external interference. Accord-

ing to observations made and being above the sensi-

tivity limit for each modulation, these values resulted

in poor average PDR values (ie, from 65.9 % to 87.4

%), indicating that additional schemes are of great im-

portance for meet link reliability requirements for in-

dustrial applications. In this way, the set of data pre-

sented enables students, researchers and professionals

to propose new mechanisms and evaluate their perfor-

mance using realistic conditions, enabling the view of

reliability of the RAW (Reliable and Available Wire-

less) WG (Working Group) at the IETF (Internet En-

gineering Task Force) (P. Thubert et al., 2020).

(Hossain et al., 2019) This article proposes an

intelligent campus model using IoT technology to

achieve intelligent management and service on cam-

pus. After reviewing several research studies, the au-

thors suggest an intelligent IoT-based campus model

that incorporates campus-oriented application ser-

vices. The designed smart campus model was mod-

eled based on the idea of the hierarchy of three net-

works as the perception layer, network layer and ap-

plication layer. Services are provided to end users

through mobile applications and screen monitoring

infrastructure according to the proposed model. Be-

fore implementing this architecture, the challenges

SENSORNETS 2021 - 10th International Conference on Sensor Networks

114

of the intelligent campus design model were deﬁned.

The authors implemented some of the application ser-

vices using a hardware and software platform. In the

end, several experiments tested the feasibility of the

proposed model of smart campus validated in the ex-

periment. In this scenario, it was revealed that appli-

cation services based on smart campus models based

on IoT proved to be efﬁcient for students, teachers and

campus communities.

(Berouine et al., 2017) analyzes the implementa-

tion of a platform for monitoring and processing data

in real time. In addition to these aspects, the authors

also propose a model for real-time detection, mod-

eling and visualization. A prototype was developed,

based on the creation of a cluster composed of ﬁve de-

vices, one main conﬁgured as a master and the other

four as slaves. With a focus on testing the interfac-

ing between different buildings, the assembled archi-

tecture for monitoring the quantities is detailed, from

sensor nodes, Wi-Fi modules, microcontroller boards

and cluster to measure data. The study proposes an

architecture for monitoring based on a physical LAN

topology. Several graphs were presented, showing the

real power consumed as a function of the time varia-

tion for each application. As photovoltaic panels were

used to supply part of the system, the graphics also il-

lustrate the low energy consumption provided by the

energy utilization in the supply of sensor nodes. In

the experiment, data were collected in real time over

a 24-hour period, with an interval of ﬁve seconds

for each measurement cycle. Four evaluation metrics

were generated: i) The instantaneous daily consump-

tion of electricity for each monitored device, ii) The

aggregate daily consumption of electricity used by all

devices present in a security guardhouse, iii) The total

energy consumption disaggregated from each device,

iv) The total consumption of energy aggregated by the

entire safety barrier. In the end, the system proved to

be efﬁcient when reaching the listed challenges and

with satisfactory results in the implemented cluster,

showing a report of the control applications with a

high degree of energy autonomy.

(Ahmed et al., 2019) aims to design an Internet

of Things (IoT) system architecture to manage the

charging of electric vehicles on a university campus.

The proposed electric vehicle management system

consists of electric vehicles, charging stations, local

parking controllers and a central university controller.

The proposed architecture was designed in three lay-

ers: i) a power system layer, ii) a communication net-

work layer and iii) an application layer. The compo-

nents of the electric vehicle system, data trafﬁc and

communication requirements that must be taken into

account are deﬁned to implement campus smart park-

ing. The performance analysis and practical feasibil-

ity of implementing the IoT-based architecture were

investigated for smart parking on the National Chon-

buk University Campus in South Korea. The results

showed a satisfactory result within the smart campus

environment, with great possibility of expansion to

other university environments in South Korea.

3 PROPOSED ARCHITECTURE

3.1 System Overview

This work proposes the development of a system for

managing Smart Campus applications, aiming to pro-

vide support for the deployment and evolution of the

wireless networks that offers connectivity to these

applications, as well as monitoring the performance

of applications and evaluate the feasibility of insert-

ing new devices in the network, based on data col-

lected from the current functioning of the network. In

this context, a network architecture that uses different

redundancy strategies, based on the IEEE 802.15.4-

2015 Standard, is considered, to provide high relia-

bility and availability.

The system proposed in this work is called RAW-

Manager (Reliable and Available Wireless, inspired

by the RAW Techs Internet Draft (P. Thubert et al.,

2020)). In this network architecture the end nodes

communicate with the applications that run in the

cloud through Gateways and they can transmit the

packets using different modulation schemes, using a

single transceiver. Gateways are conﬁgured with mul-

tiple transceivers and are capable of receiving sev-

eral packets simultaneously, using different modula-

tion conﬁgurations. This architecture was initially

proposed in (Tuset-Peir

o et al., 2020), but in this

work, only three physical layer conﬁgurations were

considered and a single Gateway was used. The

system proposed in this work will consider a more

generic scenario, in which other physical layer conﬁg-

urations may be used, as well as multiple Gateways.

The idea behind this perspective would be to use the

best possible conﬁguration obtained by each physi-

cal layer modulation variant. For example: in a data

transmission using a type of modulation most suit-

able for when spatial reach is a critical factor. At the

same time, we would have the possibility of using re-

dundancy through another modulation conﬁguration

more conducive to situations in which the data rate is,

in turn, the critical factor. In addition to these aspects,

techniques for handling packet duplication and data

persistence are considered.

In order to provide communication from the end

System for Supporting Implementation and Monitoring of Smart Campus Applications based on IoT Protocols

115

nodes to the IoT applications that will consume from

the data obtained from the sensors, the CoAP and

MQTT protocols will be explored. Each one is re-

sponsible for a part of the communication architec-

ture. The ﬁrst is used for the communication segment

that does not have a direct Internet connection. In this

section, wireless communication is provided using the

IEEE 802.15.4-2015 standard. The second section,

from the Gateway to the ﬁnal IoT applications, is pro-

vided through the publisher / subscriber model of the

MQTT protocol.

3.2 Architecture Description

One of the speciﬁc objectives of this study is to pro-

vide the ability to use transmission diversity mecha-

nisms, through the simultaneous use of different mod-

ulation schemes, aiming to achieve a high level of

availability and reliability. A centralized system is

needed to conﬁgure the network devices and man-

age the information collected by different Gateways,

which in turn can receive packets through different

communication modules.

Fig. 1 illustrates the representation of the com-

munication between the end nodes and the Gateways

using the IEEE 802.15.4-2015 standard with different

modulation conﬁgurations. This architecture was ini-

tially proposed in (Tuset-Peir

o et al., 2020), in which

an WSN with 11 end nodes and a Gateway was im-

plemented, using three different modulation conﬁgu-

rations (SUN-FSK, SUN-OQPSK and SUN OFDM),

all at 50 kbps. The management system proposed in

this paper will consider a more general scenario, with

the possibility of having several Gateways and con-

sidering the combination of the use of modulation and

receiver diversity.

With regard to application layer protocols, it is

proposed to segment the network into two distinct

groups. One group aims at a lower level approach,

which deals with the transmission of data that are not

directly visible to the ﬁnal users. The other group ad-

dresses the application layer from the point of view of

applications that run in the cloud and offer services to

end users, their processes and agents involved.

As a communication protocol between the end

nodes and the Gateway (the lowest level part), this

proposal takes into account the use of CoAP (Naik,

2017). The focus at this segment is to provide a reli-

able communication channel between the end nodes,

equipped with sensors or actuators, and the central-

izing intermediate agent (Gateway). It is intended

to implement CoAP within the Gateway, so that the

packets would be received from the sensor nodes

by the network. (Naik, 2017) At the Gateway, the

packets received from the sensor nodes must be con-

verted to generate new packets in MQTT format,

which is the protocol considered for communication

between applications that run in the cloud with the

sensor/actuator network.

It is worth mentioning that a factor that prevents

the use of a single IoT protocol to provide the com-

munication channel in this proposed infrastructure,

is due to the fact that the MQTT requires an Inter-

net connection to exchange data. However, the mi-

crocontrollers coupled to the sensor nodes considered

in the proposed network do not have a network card

for direct connection to the Internet. For this reason,

the radio modules will communicate through a low-

power wireless network and, only from the Gateway

onwards, the data will be transmitted through the In-

ternet.

At the end node, the information to be transmit-

ted is organized in the payload of the packet. When

the packet is received, in addition to the sensor data,

other information must also be collected by the Gate-

way. It is intended to create a customizable data pack-

ate from the information collected. This payload will

consist of an Array containing several ﬁelds of rele-

vant information, such as: RSSI, package identiﬁer

and other metrics related to the quality of transmis-

sion in the communication links. Regarding the value

generated from RSSI, it is intended to use the ra-

dio module’s own integrated converter, which already

makes an automatic conversion transforming an in-

teger value, normally between 0 to 255, to a value

in dBm. Once this information reaches the Gate-

way, such data would be encapsulated in a format un-

derstood by the applications, in this scenario, using

MQTT.

Fig. 2 illustrates the details of the communication

methods used between the end node and the Gateway.

Two main CoAP methods are used to exchange infor-

mation between the sensing network composed of the

end nodes and the Gateways.

At a higher level, the applications will commu-

nicate with the Gateway through the MQTT proto-

col, based on the Publisher-Subscriber model. In this

communication model, there is a Broker, which once

allocated in the cloud allows the creation of entities

called “Topics”, which allow a particular application

interested in that group of data related to a given topic

to subscribe to receive any information that is regis-

tered in the topic.

3.3 RAW-Manager

Fig. 3 shows the details of the RAW Manager and the

communication between the Gateways until the ﬁnal

SENSORNETS 2021 - 10th International Conference on Sensor Networks

116

Figure 1: Communication Between End Nodes and Gateway.

Figure 2: Details of Communication methods between end

node and Gateway.

IoT applications. We can describe RAW Manager as a

control application that will run inside an application

server in the cloud, communicating with Gateways to

collect information and also send conﬁguration com-

mands. Still in Figure 3 it is possible to see the repre-

sentation of the details of functions involved and as-

sociated with the RAW Manager. FN1 represents the

handling of duplicate packets within the control appli-

cation, which manages the received packet. FN2 de-

scribes the communication between the database and

the control application, through the exchange of mes-

sages through a structured query language (SQL). In

turn, FN3 describes the ability of the ﬁnal IoT appli-

cations to also send control commands or request data

through their actuators. FN4 is the representation of

the communication channel responsible for accessing

the information of the packets that arrive through the

network.

Still at the application level, it is intended to im-

plement a functionality responsible for data persis-

tence. Such a tool would read the data via MQTT

and store the information obtained in a Time Series

Database (InﬂuxDB), a tool widely indicated for sce-

narios in which data storage is required that undergo

constant variations as a function of time. It is also

worth noting that the same packet can be received by

more than one Gateway, if they have compatible mod-

ulations and are within reach of a given end node.

Thus, before registering a package with the Broker,

the RAW Manager is also responsible for handling

these duplications. In what concerns the MQTT Bro-

ker, three topics are deﬁned in this example: voltage,

current and temperature.

Based on the network architecture proposed

in (Tuset-Peir

o et al., 2020), the Gateways repre-

sented in Fig. 4 will consist of a Single Board Com-

puter (SBC) connected to multiple IEEE 802.15.4-

2015 radio modules (three in the example), to receive

the packets sent using different modulation schemes.

Inside the Gatewa a Python Script is responsible for

the individual reading of each packet received by the

radio module and converting it from the raw packet to

a MQTT message.

Once the RAW Manager infrastructure is properly

functional, several information obtained will be use-

ful to evaluate the performance of the proposed net-

work architecture. Metrics such as: i) packet deliv-

ery ratio, may determine the degree of reliability in

transmission between different points inherent to the

network, ii) the level of signal attenuation may reveal

which phenomena or agents will be responsible for

the degradation of the signal quality between sources

and destination, iii) RSSI, it is possible to quantify the

capacity of agents to hear, detect and receive signals

between any devices on the network. In addition to

System for Supporting Implementation and Monitoring of Smart Campus Applications based on IoT Protocols

117

Figure 3: Detailing of RAW Manager with message exchange via MQTT.

Figure 4: Detail of the Internal Architecture of the Gate-

ways. Based on (Tuset-Peir

o et al., 2020).

these listed aspects, the RAW Manager will support

the deployment of new devices or the evolution of the

network infrastructure, with the possibility of reusing

the infrastructure for different applications.

The validation of this architecture will be done

through the deployment of a network, aiming at the

application of energy consumption monitoring. As

the support system is at the heart of this study’s pro-

posal, the sensor network’s validation strategy con-

sists of a case study, aimed at measuring and monitor-

ing electrical quantities, which aims to mitigate the

waste of electrical energy, through sectorial monitor-

ing . Through the implementation of an architecture

based on hardware and software.

After measuring the values, the system also pro-

poses the collection of data from the monitored en-

vironment, registration in a database system based

on time series and the possibility of remote man-

agement on a web platform. In the end, it is ex-

pected that the system will allow the monitored en-

vironment to identify the points of greatest consump-

tion in the network, enabling the identiﬁcation of the

main points of energy waste, in addition to the con-

struction of a wireless sensor network capable of re-

ceiving other sensor devices that can monitor differ-

ent phenomena relevant to an Intelligent Campus en-

vironment. Until then, several communication and re-

mote management experiments have been carried out.

To date, the tests have proved to be efﬁcient, exchang-

ing data between devices of totally different computa-

tional capacity and between different communication

platforms, both in real and simulated environments.

It is worth mentioning that the entire system is being

programmed locally aiming at the minimum depen-

dence on services provided by others, enabling the

system to operate with the maximum autonomy and

freedom possible.

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118

4 CONCLUSIONS AND FUTURE

WORKS

This paper describes a system for monitoring

smart campus applications based on IoT protocols.

Throughout this article, the details of the proposed ar-

chitecture were made, the main objective of which is

to support the deployment of new sensors, enabling

remote management of control applications by net-

work administrators, in addition to allowing the mon-

itoring of the analyzed applications as a function of

time, providing reliability through the use of diversity

techniques in the physical and data link layers, based

on the IEEE 802.15.4g SUN standard. Communica-

tion tests were performed with different protocols us-

ing websockets, public test instances of the MQTT

protocol and local implementations in order to verify

the degree of reliability in communication with differ-

ent levels of QoS (Quality of Service). Where, so far,

the results have been promising.

The next steps to consolidate this work will fo-

cus on providing a reliable exchange of messages be-

tween devices that operate in different modulation

schemes, respecting the predeﬁned critical levels of

QoS. As future work it is expected that the proposed

architecture can be reused for use with the most di-

verse types of sensors in order to monitor other areas

of interest on the smart campus, such as: vehicle traf-

ﬁc control, parking, intelligent lighting and security.

ACKNOWLEDGEMENTS

The authors would like to thank the partnership be-

tween the Federal University of Para

ıba and the Fed-

eral Institute of Para

ıba, the Coordination for the Im-

provement of Higher Education Personnel (CAPES),

and the Brazilian National Council for Scientiﬁc and

Technological Development (CNPq 421461/2018-7).

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