The document discusses the development of an augmented reality (AR) prototype aimed at enhancing IoT-based educational activities related to energy efficiency in school buildings. The GAIA project utilizes AR and real-time data to engage students in understanding energy consumption and promote sustainability awareness. Future work includes evaluating the system's effectiveness in classroom settings and continuing development to further improve student engagement.

1. AN AUGMENTED REALITY PROTOTYPE FOR
SUPPORTING IOT-BASED EDUCATIONALACTIVITIES
FOR ENERGY-EFFICIENT SCHOOL BUILDINGS
GEORGIOSMYLONAS, CTI DIOPHANTUS,NOVEMBER 12, 2018

2. Introduction
• Augmented reality (AR) has been around since the 1990s,
but only recently has become more mainstream.
• AR is maturing and becoming affordable to use.
• Apart from dedicated hardware, smartphones and tablets
are the main enablers of AR technologies.
• Proliferation of AR-enabled devices and technologies has
led to numerous prototype applications, in order to test in
practice what we can do with these technologies.
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3. AR in Education
• The educational sector is one of the domains where AR is
expected to make an impact in the coming years.
• AR is often used as a means to complement an existing
educational activity, providing additional information in an
interactive manner.
• Recent studies suggest that use of AR during class has a
positive effect in students’ learning performance and
overall engagement.
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4. What we are looking into…
• Raising awareness among young people and changing
their habits concerning energy usage.
• EU considers environmental education one of the
prominent instruments to influence human behavior
towards sustainability.
• The educational community has a sizeable impact.
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5. Green Awareness In Action - GAIA
• H2020 project, developing an IoT platform that combines
sensing, web-based tools and gamification elements,
addressing the educational community.
• Increase awareness about energy consumption and
sustainability, based on real-world sensor data produced
by school buildings.
• Use real-world data generated inside schools to:
• Enable more interesting lectures
• Let students discover things on their own
• Learn while doing cool stuff!
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6. GAIA in numbers
03/04/2019
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7. What we propose…
• Use augmented reality to complement an in-class lab
activity for the GAIA project.
• Utilize IoT and real-time data to help students gain a
deeper understanding of concepts related to energy
consumption and efficiency inside their own building.
• The augmented reality part provides an additional visual
companion to these activities.
• Used to directly inspect sensor data inside classrooms at
any point in time, simplifying access to such data.
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8. GAIA IoT devices
03/04/2019
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9. • Temperature
• Relative humidity
• Illuminance
• Motion detection
• Noise levels
• CO2 concentration
• Electrical power consumption
What is monitored inside
the school buildings

10. Educational lab kit
• “Hands-on” approach, using IoT components and electronics.
• Simple IoT sensors and components allowing students to
complete activities regarding energy within 1-2 hours.
• Use already assembled components, no extensive wiring
between components, or complicated interconnections.
• A series of lab activities:
• “Energy consumption in our school”.
• “Lighting inside our school”.
• “Heating inside our school”.
• “Temperature, Humidity and Thermal Comfort”.
• “Appliances and Energy efficiency”.
• “Energy Inspectors - The energy footprint of our building”.
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12. Design approach
• Previous results suggest that AR can produce a positive
effect in students’ learning performance and engagement.
• The integration of AR capabilities to the workflow of the
lab activities enhances the lab kit aspects.
• Act as a companion to lab kit activities, and simplify
monitoring and maintenance of IoT devices.
• Not overshadow the hands-on parts of the activities but,
instead, support them by adding AR visual elements.
• Guarantee that certain parts of information related to
energy are available to the students regardless of failures.
• We showcase a prototype version of the system.
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13. Technologies used
• ZXing for QR codes - open-source image processing
library.
• Unity3D for the AR functionality.
• Used an iPad Pro 10.5 and iPhone X running iOS 11, for
development and testing.
• Use main camera to get a view of the real-world.
• QR tags are placed on GAIA devices and the lab kit parts,
to provide context.
• The scanner recognizes the IoT device we are pointing to
with our phone, or the classroom in which the user is at.
• Use MQTT to communicate with GAIA’s cloud services to
get info about devices and sensors.
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14. Architecture
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15. • As soon as the app knows where to subscribe to and has
the credentials, it starts getting updates in real-time.
• The application can overlay in AR any kind of information
available on top of the lab kit surface or an IoT device.
• Implementation is available through our GitHub repository.
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16. Companion to the lab kit activities
• Use QR tags to determine placement for data
visualization.
• Utilize “empty” spaces in physical space as extra
“displays” for activity-specific information.
• E.g., if there is a white rectangle (A4 sheet), we can use
this space to display measurements in 2D form.
• Simplify completion of the activities: aimed at students of
various ages and educational background.
• Make the activities easier to complete independently.
• AR can provide visual guides, e.g., highlighting the
important parts of the circuit.
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18. Data viewer and maintenance tool
• The IoT devices installed inside classrooms do not have
any kind of visual feedback besides a couple of LEDs.
• Users are otherwise required to enter a web portal.
• Insert AR to the overall workflow and simplify it!
• Use QR tags to enable the integration of AR visualization.
• By simply pointing to devices with a phone, the app
recognizes them and displays relevant data in AR.
• Acts as a “manual” overlaying info about a specific device.
• An AR legend shows the components on each device.
• Devices don’t have identical sets of sensors!
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21. Evaluation
• Time it takes for the app to recognize correctly QR tags:
• with an iPad Pro, on average, it takes 900 ms.
• Contact a cloud service and subscribe to an MQTT broker
to receive information regarding an IoT device/sensor.
• On average, 740 ms for receiving an update containing
the latest sensor values by this device.
• Recognizing an IoT device, contacting the service and
then produce a result, overall requires 1.5 to 2 seconds.
• QR scanning performs well 0.5 - 1 meter away from tags.
• Approx. 80% success rate in recognizing the device.
• Good lighting is required for AR to function properly.
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22. Future work
• Continue to develop the system, and evaluate its use
inside the classroom during actual educational activities.
• Introducing end-user interfaces like the ones described
here is a way to engage students to educational activities:
• don’t underestimate the power of the “wow factor“!
• Visit http://www.gaia-project.eu!
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