Nowadays
billions of electronic brain are interconnected. Physical objects are able to
be  connected to each other and
communicate with no human intervention. The connection between the digital  devices is called Internet of Things (IOT)
and the enviroment generated is define Smart. In this paper, the focus is on
the application of IOT in the Smart Classrooms. The paper proposes a prototype
application called ‘Newton Smart Classroom’, built on a opensource software
infrastructure system composed of  multiple
interacting intelligent agents, using web service technology within a smart space. The mobile
application integrated with an IQRF chip permits to gather information of the
campuses and enhance access to data stored in the database, allows students to
have an overview of the education curriculum. The project is designed to help
educational institutions use and connect their existing technologies to provide
a tailored learning path. The digital devices associated to the system allow the
istitutions to gather data on their  user
 as a proper understanding of every
student’s strong and weak points. Outside of the classroom, the solution
Intelligent-Contextual-Proactive uses analytics, cognitive and data drive
systems to monitor and proactively interact with the students. This gives them
better dashboards that exposes future demands for jobs and career options
matched to their skills and interest.

Keywords:

·     
Mobiles

·     
Sensors

·     
Smart
Classroom

·     
Internet
of Things

·     
Learning
and teaching activities, Cloud

·     
Mobile
Computing, Cognitive systems

·     
Education
Transformation

·     
Career
opportunity

 

Problem

 

 

In the
coming years, technology will impact the learning experience in many ways. The Internet
of Things (IOT) continues to confirm its important position in the context of
Information and Communication Technologies and the development of society. The university needs
to deal with novel learn techinques in order to satisfy the learners’ needs and
to supply a new education production system, where multi-disciplinary
activities, complementary competencies and skills from humanities to
technologies are include.  It is common
in the last few years to find job searches demanding experts having that integration
of diverse skills sets.  Sadly,  today most graduates have a specific
knowledge background, rapresenting the education path they have been chosen. This
prevents young graduates from having immediate success in the global market,
which is based on services, multitasking skills, and teamwork. In this context
we need to promote collaboration among all the parts involved in education.

Students should have the opportunity of interacting with companies and
industries throughout their studies, therefore to be able to orient themselves
towards specific job application. Moreover, the collaboration between the Business
world and Education Institution can offer  multiple advantages, such as having apprenticeship programs and facilitating
the technology information transfer from university research laboratories
straight to industry.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Solution

 

 

The
paper proposes a prototype application called ‘Newton Smart Classroom’, built
on a opensource software infrastructure system composed of  multiple interacting intelligent agents, using
web service technology within a
smart space. The mobile application integrated with an IQRF chip
permits to gather information of the campuses and enhance access to database
allows students to have an overview of the education curriculum. The project is
designed to help educational institutions use and connect their existing technologies
to supply a tailored learning path. The digital devices associated to the system allow the
istitutions to gather data  as a proper
understanding of every student’s strength and weaknesses. Outside of the classroom, the solution uses
analytics, social networks, cognitive and data drive systems to observe and proactively
interact with the students. This gives them a dashboard that exposes future
demands for jobs and career options matched to their skills and interest. Interactive classroom, the smart
classroom expose the students to infinite possibible learning experiencies
based on collaboration (teamwork). Personalised
education, technology  enables the
opportunity of learning anytime, anywhere, from any device, without the need
for an instructor. This method of learning is expounded by Siemens (2005) “Learning becomes the
critical recognition of connections that change the network itself,
simultaneously adding new connections, potentially in the absence of an instructor or
authority” (Connectivism)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Produced

 

The prototype is developed in five layers
following the integration of sensors, actuators, networks, cloud computing and
technologies of the Internet of Things.

 

 

• Sensing
layer ( In This layer  several types of
devices are used. The specific data type determines the implementation and
production of the device. The main activity of the sensors are collection and
transfer information)

• Databases
layer ( Physical databases  have a  typical  set of SQL and nonSQL (object). The IoT data
can be collected and processed in real time. Virtual databases allows to keep
track of the data flows.)

 

 

• Network
layer (The IoT network layer, connects all the devices  and allows 
them to understand  its smart
space. In this layer the system can collect data from existing IT
infrastructure)

 

 

 

 • Data
response layer (In this layer, the processed data is stored. All data
received from the sensors are processed in the network node and sorted in a
logical way)

 

 

 

 • User
layer (In this layer, the API is employed  for application design. The main applications
whitin industry 4.0 project are ERP solution. The entity relathionship model
permit to control, measure, and implement the main function of the software
developed)

 

 

 

 

 

 

 

 

 

 

Background

 

 

The overall architecture used for the
Internet of Things is a three-tiered. In the initial level the various  sensors are deployed. Information  is obtained real-time from the device. The
intermediate level integrates multiple wired and wireless networks to transfer
the information of the items with exactitude. Data collected by the sensors is
transferred frequently  to the web  by the network. The highest  level of the architecture is the level of application.

It consists of three  layers (technology, middleware and application).

The application layer consists of applications that export all the
functionality of the systems to the end user and exploits the capabilities of
the network layer. The middleware is a software layer between the technology
and the application levels. This  feature
is to cover  the details of the different
technologies. This feature is crucial to exempt the programmers of the topics that
are not directly relevant to their developments, which is the development of
the specific application enabled by the infrastructure (Gubbi et  al.

2013). The middleware is gaining increasing relevance in recent years. The use
of the cloud computing, has permitted to perform all the computing in it,
without any need to own servers or mainframes. This has opened a new economic
model in computing, the companies offer hardware, platforms and software as
subscription services. The most important features of the project will be the
integration between the IoT solution and the social network, social internet of
things (SIoT). In this context, several works have been already conducted,
which could be a starting point for the definition of the project. (Semantic Annotations
for WSDL (SAWSDL), Unified Service Description Language (USDL), Web Service
Modelling Language (WSML), Web Service Modelling Ontology (WSMO), and Semantic
Annotations for Representational State Transfer SA-REST). Sub-layer includes
the tools that implement the core functionality of the SIoT system, ID management, The owner control (OC), relationship management (RM), The service discovery (SD), The service
composition (SC), trustworthiness
management (TM).

 

 

 

 

 

 

 

 

 

DATA

 

By Using the
available content, the system generates a communication network that permits  the access to the user in any place and
consultation of data at any time, due to the connection of the physical sensors
with the server online.  

Data collection: (university system- social networks) the sensors gather
data always, aware of each movement in 
the system is deployed.

Data Transfer: different sensors (actuators)  enable to transfer data into the network
composed by User (mobile device), physical device(IQRF) through Cloud Computing

 

 

 

 

 

SKILLs

 

Learning skills: In particular, the development
of autonomous learning (DevOps, programming code, integration IOT and Social
network).

 

 

 

 

 

 

 

 

METHODOLOGY

 

The metodolody of the project will be  DevOps 
deployment.  This method is
structured around the organizational variation and the collaboation within the
diffent development operations.

By using the  DevOps methododology the projet will benefit
of several adavantages, time to market, 
identification  of the priority,
low failure rate, recuded the time between the fixed operations.