UNICEF-Armenia
Chapter IoT program for 14–18-year-old teenagers
Summary
of the report
The overall project goal is to train IoT-educated groups of teenagers in 5 major
Armenia cities, Yerevan, Hrazdan, Vanadzor, Gyumri, and Goris, who will be able
to implement IoT projects in the local communities.
Experienced coaches were interviewed and chosen, helping the groups during IoT classes:
Yerevan Yervand Galoyan
Hrazdan Gayane Hakobyan
Vanadzor Ani Torosyan
Goris Martin Minasyan
Gyumri Susanna Khotsanyan
The classes were provided by Vahan Misakyan, Karen Yerznkanyan, and Yervand Galoyan, having profound knowledge in IoT. The announcement about the courses was widely advertised and groups were formed. They included teenagers with impairments.
Each group
was supplied with the following equipment:
|
# |
Name |
Quantity |
|
1 |
Arduino Uno |
4 |
|
3 |
ESP-32 Board |
4 |
|
2 |
Arduino Education Starter Kit |
5 |
|
3 |
Breadboard Jumper Wire Pack |
3 |
|
4 |
Arduino Bare Board |
8 |
|
5 |
Raspberry kit (Raspberry Pi 4B, 4GB) |
2 |
|
6 |
Sensors, Leds, Servo motors |
|
The areas of
the IoT, in which the participants were trained, are the following:
Smart home: Temperature control, Smart thermostat, Smart doorbell; Smart
lock, Smart coffee maker, Smart driver, Smart dishwasher, Smart refrigerator
Lighting control, lighting controlled by scenarios
Voice assistants: Alexa Amazon, Google Home, Alisa Yandex
Unmanned equipment, Drones
Structure of modern cars, Shuttle taxis, Unmanned economic
vehicles
Smart city: City lighting management; Management of
parking lots; Control of traffic lights; Smart stops
Agriculture: Greenhouses; Monitoring of agricultural
conditions; Prevention of fires.
Trade: Automated stores without salespeople; Amazon
Shops; Electronic labels
Cargo transportation: Monitoring of the technical
condition of the car; Optimal cargo transportation management
Power supply: Measurement and monitoring of electricity
consumption, power supply management Smart Grid; Power plant management, safety
issues
Healthcare: Telemedicine, remote medical consultation,
monitoring of patients' condition; remote operations.
During practical courses, participants worked directly on physical boards such
us Arduino Uno, ESP8266 and ESP32, sensors and actuators. In addition, online
tools Thinkercad (https://tinkercad.com) were widely used. Thinkercad is a web app for 3D design, electronics, and coding, which
is the ideal introduction to the circuit technology
that permits to emulate the circuit design. It made the study easier and
more comprehensible. Through the platform, participants were also given
individual homework, and each participant's work is further discussed in detail
in online classes. This methodology allows strengthening the participants'
knowledge.
Students’
tasks completed with the Thinkercad emulator were presented to trainers for
approval.
In parallel with classes the groups were working on the development of a voice assistant in Armenian based on Raspberry PI4 microcomputers. Commands in Armenian were developed. A solution to the problem with limited words or phrases was developed. It will help people with mobility or vision problems to control their home and office equipment (lighting, heating, doors, shutters, etc.).
The
Armenian-language voice assistant had been developed with the involvement of
teenagers included in the project. The latest technologies and solutions in
voice recognition and machine learning were used. The voice assistant was named
"Anahit" (it echoes that name). Anahit is built based on a Raspberry
4PI microcomputer, to which a microphone hub, a speaker and a sound amplifier
are attached. A 3D model was developed to give all these equipment a complete
equipment look. With a 3D printer at the disposal of
the IoT Lab laboratory, a case was made, where the mentioned equipment was
placed.
The Chapter continued to work for the House of Culture of
blinds and visually impaired people. A smart switch connected to a cloud management
system, enabling remote monitoring and control of lighting was installed. The
system allows users to check the status of lights and remotely turn them on or
off. Additionally, the installation of the Yandex Alisa voice assistant enabled
voice-controlled operation of the lighting system. Besides that, we acquired an
electronic valve, enabling remote control of the building's water supply. The video of
using Yandex Alisa voice assistant in the House of culture can be seen here. According to plans the Anahit voice assistant will
be installed in the House of culture of blinds and visually impaired people a
bit later. Anahit will be able to switch on and off electricity and water
supply.
Post-training knowledge assessment
The post-training knowledge assessment
questionnaire, that was developed to measure the level of knowledge increase
among the trainees, was converted to a survey type that was easier to use
through quizizz.com interactive online
survey. The survey questions were developed. The
overview of the survey methodology implemented for training teenagers in IoT
showed the way of improvement. The
evaluation of the knowledge gained by the participants was carried out, not
only at the end of the course, but also during it. That method had a
significant impact on the level of knowledge and skills of the participants.
The results of the final summary survey also testified to this.
And considering that surveys were
conducted online and interactively, they created a great interest and a healthy
competitive atmosphere during the courses.
Here is the list of trained
adolescents:
|
NN |
Name |
|
1 |
Edik Baghshyan |
|
2 |
Samvel Ajizyan |
|
3 |
Ruben Ghazaryan |
|
4 |
Aram Hakobyan |
|
5 |
Davit Ghaplanyan |
|
6 |
Narek Vardanyan |
|
7 |
Rudolph Kitoyan |
|
8 |
Sargis Baghramyan |
|
1 |
Mariam Ter-Petrosyan |
|
2 |
Tigran Poghosyan |
|
3 |
Milena Khachatryan |
|
4 |
Mariam Sahakyan |
|
5 |
Lili Abrahamyan |
|
6 |
Aren Halevoryan |
|
7 |
Sona Ghambaryan |
|
9 |
Alik
Sargsyan |
|
10 |
Vazgen Shekoyan |
|
11 |
Hovhannes Varderesyan |
|
12 |
Artavazd Arabachyan |
|
13 |
Gor Bayanduryan |
|
14 |
Artyom Shahnazaryan |
|
15 |
Lilit Alikhanyan |
|
16 |
Meri Qurdoghlyan |
|
17 |
Artur Aleksanyan |
|
18 |
Artur Amyan |
|
19 |
Armen Karapetyan |
|
20 |
Elen Grigoryan |
|
21 |
Elena Yeganyan |
|
22 |
Sirak Khachatryan |
|
23 |
Gagik Vardanyan |
|
24 |
May Nikoghosyan |
|
25 |
Hrach Gyurjian |
|
26 |
Aram Hovhannisyan |
|
27 |
Alain Oganov |
|
28 |
Milena Aghajanyan |
|
29 |
Lilit Martirosyan |
|
30 |
Avetis Mamikonyan |
|
31 |
Artur Abrahamyan |
|
32 |
Artur Aleksanyan |
|
33 |
Artur Amyan |
|
34 |
Armen Karapetyan |
|
35 |
Elen Grigoryan |
|
36 |
Elena Yeganyan |
|
37 |
Sirak Khachatryan |
|
38 |
Gagik Vardanyan |
|
39 |
May Nikoghosyan |
|
40 |
Hrach Gyurjian |
|
41 |
Aram Hovhannisyan |
|
42 |
Alain Oganov |
|
43 |
Milena Aghajanyan |
|
44 |
Lilit Martirosyan |
|
45 |
Avetis Mamikonyan |
|
46 |
Artur Abrahamyan |
|
47 |
Edmond Serobyan |
|
48 |
Yurik Minasyan |
|
49 |
Edgar Hovhannisyan |
|
50 |
Hripsime Hovhannisyan |
|
51 |
Davit Karapetyan |
|
52 |
Henrik Vardanyan |
|
53 |
Adelaida Baghdasaryan |
|
54 |
Luiza Paravyan |
|
55 |
Mikael Sakhbazayn |
|
56 |
Aram Alaverdyan |
|
57 |
Narek Nersisyan |
|
58 |
Nana Shakhbazyan |
|
59 |
Karine Soloyan |
|
60 |
Mariam Hovsepyan |
|
61 |
Milena Hayrapetyan |
|
62 |
Anahit Kocharyan |
|
63 |
Lily Minasyan |
|
64 |
Tirayr Harutyunyan |
|
65 |
Alexan Harutyunyan |
|
66 |
Arsen Movsisyan |
|
67 |
George Salbunts |
|
68 |
Gor Salbunts |
|
69 |
Shahen Gyurjian |
|
70 |
Eric Javahiryan |
|
71 |
Artashes Malintsyan |
|
72 |
Alen Atanesyan |
|
73 |
Nane Mashuryan |
|
74 |
Lia Hovsepyan |
|
75 |
Arame Hovsepyan |
|
76 |
Arsen Hovsepyan |
|
77 |
Tigran Apunts |
|
78 |
Gor Parsyan |
|
79 |
Suren Parsyan |
|
80 |
Davit Gasltyan |
|
81 |
Hasmik Arustamyan |
|
82 |
Tatev Aleksanyan |
Among them 12 adolescents were with impairments.