Interim Report

So far, we have met with the PO twice, and we have a pretty clear vision on what our plan is when we really start working on the project at the start of next year. We are going to use a Raspberry Pi with some sensors and a cellular connection to display data regarding air quality using Microsoft Azure. We want to be able to monitor air quality and notify the user, if target values for different air quality metrics are exceeded. We are also interested in using a 3D-model of our school to display the data, but we are not yet sure if we are going to have access to the 3D-model.

For now, we have divided the work to three different parts of the project: The Raspberry Pi and the sensors, machine learning, and coding. Matti, Rami and Sami will work on the Pi and the sensors, Minh, Ife and Eetu on machine learning and Jan, Patrik and Pyry on the code. In addition to these tasks, Rami is our project manager, and Matti is our project contact person.

Our desired end result is to get the Pi and the sensors to work in a way, which allows us to monitor and display data on room temperature, carbon dioxide and humidity in a visually pleasing way.

Week Report - Week 48 - Preparations

Tuesday 26.11.

On Tuesday we had a lecture on prototyping. Which in our project's case is a plan on how we are going to conduct our sensing in the classrooms. We started this planning already last week so we were ahead of schedule a bit. But we did continue those plans and they will be posted on the blog as a separate post.

Friday 29.11.

Friday we didn't have a lecture, so we just had a group meeting about the state of our project. Next Tuesday we have a PO meeting where we will be introduced to the sensors that we will be using. We also made a base PowerPoint presentation for our upcoming presentations or pitches about the project.

Week Report - Week 47 - Progress!

Tuesday 19.11.

On Tuesday we got a lot of things done, and started planning how to start the project. We built a mind map and an idea tree, we also did our peer blog review. I also wrote a report on our first meeting with the project owner. Our project's lean canvas was also built.

We also started our research on air quality standards and sensing. Tasks were given out to people to find articles and research papers on air quality for Friday so we can go through them together and see how we need to do our sensing.

Friday 22.11.

Friday we had a group meeting to go through our findings as a group. We had found good research and standards on air quality that we can use as a basis for our own project. We also found information on how sensing needs to be done so the results are good and the data has good quality.

We made initial plans on how to start our testing with the sensors once we get our hands on them. I contacted our PO and asked about when we could get a sensor, to test how it behaves and how we can gather data from it. Our PO will arrange a presentation on the sensor for our next meeting.

Review of peer group's findings

This review is from our peer groups blog: https://capstone20.blogspot.com/

"WHAT IS SCADA?
SCADA stands for Supervisory Control And Data Acquisition. It is software package that is positioned on top of hardware. SCADA in general is interfaced via Programmable Logic Controllers (PLCs), or other commercial hardware modules.
SCADA systems are widely used in industry for Supervisory Control and Data Acquisition of industrial processes."
WHAT IS SCADA?

We chose their secondary research of SCADA for review since some aspects of SCADA could be implemented in our project for data acquisition. It would be possible to create automated alerts from real time monitoring of rooms using NBIoT sensors.

Mind Map

Idea Tree

Lean Canvas

Project Owner Meeting Report

The project is about creating behaviour models for classrooms and monitoring classroom air quality. The behaviour models should be built using machine learning. The room sensing will be performed with NBIoT sensors that work over mobile networks. The project owner wants the data to be visualized in a 3D-model of the building. If we can build a digital-twin model for the project that would be good. The goal for the project is a proof of concept.

The data collected should include temperature, humidity, co2 levels. Additional sensors that could be used is a motion sensor to automatically detect how many people enter a room, but that is not mandatory. Air quality should be our focus on the project. Light levels could also be measured and then we need to consider light colour as well. Correct placement of the sensors is a key thing for quality data. We also need to observe the amount of people in the room and how long they are present as they directly correlate to the air quality in the room.

The digital twin model would have real time data from a building that would automatically display the data on the virtual counterpart. Digital twins integrate IoT sensors, AI and machine learning to create the living digital simulation. This model would use the 3D-model of the building and visualize the data in it. Turku GameLab should have the 3D-model for the building that we can use. This requires large amounts of data for the machine learning, as you can not train AI without data. The visualization is also a key part of the project.

Data security is also an issue we should consider on the project. Environmental data could be interpreted as personal data in some cases, so security is required to keep data private. Some officials say that sensing in spaces is under GDPR law, motion sensors could be considered as cameras and those would require people to opt in for the data gathering. Normal air quality sensing is not directly related to persons, but it can be combined with other data that could link it to a person so it would fall under GDPR. Testing in classrooms might require permissions from Kiinteistöpalvelut, and we need to know if we need to inform teachers etc. about testing in a classroom during a lecture.
For data security we could do cybersecurity analysing and testing for IoT systems. Good security is a must for smart buildings. Security planning and risk analysing would need to be done and testing the system on how secure it is.

For the coding languages we can use what ever we want but keeping it simple is a good choice. If we use Unity for the 3D-modeling it uses C#. Data will be gathered to Azure Cloud but that does not restrict code usage, so keeping it in Python or C# is a good idea.
For data transfer the project owner wishes to use a testing network, that would require permissions from other persons not involved directly in the project. If that is not possible, we can use mobile networks for data transfer.

Research on machine learning is needed to use it effectively in the project to build the behaviour models. We also need to find research data on room air quality and use that as a base for planning our own monitoring and testing. Experimenting with the sensors on how they behave is also important to gather quality data. There are several key figures that need to be considered for the data so it can be used in the project effectively. For example, the amount of people affects the levels of CO2 directly over time.

There has been previous work done on the project, so we do not have to start from scratch. The project owner will provide us access to the work that has been done previously. Parts of the project need to be developed at the same time as they are dependant on each other, realizing roadblocks and dependencies is key for the project to move forward smoothly.

Clear planning for the project is important. If we need to order certain sensors it will take time to acquire them for the project. Regular face to face meetings with the project owner is a good idea so we can keep everyone onboard and plan the project forward accordingly.

Group Task 5: Secondary Research

Group Task 5: Secondary Research

Interesting articles:

An IoT Based Air Pollution Monitoring System for Smart Cities
https://www.researchgate.net/publication/334092485_An_IoT_Based_Air_Pollution_Monitoring_System_for_Smart_Cities

Air quality all around the world, and in cities especially, is decreasing and air pollution is cited responsible for millions of deaths per year worldwide, according to WHO. According to the article, the solution to this problem is smart cities and IoT air quality control devices that are, e.g. based on Raspberry Pi 3 Model B with sensors, a cloud data storage platform and an API/dashboard. With these sensors we can track qualities like temperature, humidity, carbon monoxide, smoke, gases and concentration of hazardous particular matter. The article is based around an Android app while the data is stored privately on ThingSpeak and is requested through the API through HTTP requests. The data stream is sensors (analog to digital converter depending on sensory output) -> Raspberry Pi -> ThingSpeak -> JSON format -> application.

Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings
https://www-sciencedirect-com.ezproxy.turkuamk.fi/science/article/pii/S0167739X17314127

In this paper the authors try to collect, transmit and analyse the enormous amounts of data produced by IoT devices, transmitted through the internet and to the cloud environment. They propose efficient smart building network architecture, and they use an operating system called Contiki and emulator Cooja to simulate their proposed network design in real time. The authors also explore other related works, such as "An indoor location-aware system for an IoT-based smart museum" -article, in which the authors designed and validated an indoor location-aware architecture which is able to enhance the user experience in a museum. The system relies on wearable device that combines image recognition and localization capabilities. This system interacts with the cloud with the aim to store multimedia contents that is produced by the user and to share environment-generated events on user’s social network.

IoT-based Occupancy Monitoring Techniques for Energy-Efficient Smart Buildings
https://www.researchgate.net/publication/280157569_IoT-based_Occupancy_Monitoring_Techniques_for_Energy-Efficient_Smart_Buildings

Development of Internet of Things (IoT) devices such as smartphones, sensors, cameras, and RFIDs, has made collection of data from these devices for tracking and localization purposes possible. Data collection is done via WiFi (WiFi-based), use of cameras (camera-based) or sensor-based. WiFi-based data collection involves installation of packet analyzers which captures incoming packets. These packets are further captured using tcpdump and forwarded to servers for MAC address and RSSI value collection. Camera-based collection makes use of cameras to detect motion. With the aid of motion, occupancy in a building can be collected. Human face, head, upper body, are for example, used by the algorithm to make counting. Sensor-based make collection of data using microcontroller with WiFi support, such as Arduino. With Arduino, different kinds of variables can be inputted for calculation / counting. Data collected from these IoT devices are from various type of occupancy sensors which are generally places within buildings. Occupancy can be further divided into detection, counting, tracking and behavior recognition. Occupancy detection gives data about the space and if empty. This is generally done in meeting places or cafeterias. Occupancy counting gives data about the number of people in a place at a given time. It can count total number of people in the whole building or sectors of the building. Occupancy tracking provides data from people by counting, locating and tracking them. Occupancy behavior analyzes people behavior in a space by using data from occupancy detection.

Interesting products/services/applications/concepts:

Envira IoT – Structural health monitoring of buildings
https://enviraiot.com/structural-health-monitoring-of-buildings/

Using sensors to monitor the structural health of buildings, technologies include REST, MQTT, 3G, LTE, LORA. Data is transferred to a platform where it can be graphically displayed and downloaded for further analysis. It allows for real time monitoring of structures and buildings, extensive logging enables studies of trends in the behaviour of fissures.

Urban.io
https://www.psitechnologies.com/product-lines/smart-buildings-iot-urban-io/

Urban.io provides a range of low cost, industrial grade IoT devices that provide real time data from building systems. For example, using IoT sensors to detect a failure in cool rooms and freezers.  Adding sensors that provide real time data of such rooms to alert if the temperature rises too high. This leads to reduced costs, since the spaces don’t have to be inspected manually multiple times a day.

FSG Smart Buildings
https://www.fsgsmartbuildings.com/services/iot

Using multiple IoT sensors to monitor and control buildings. For example, automatic temperature control etc. They work with multiple sensors like temperature, humidity, co2, activity detection and vibration to name a few. They have a platform named Chariot that is a cloud-based management plane for the IoT sensors and provides real time monitoring.

Week report - Week 46

Tuesday 12.11.

Started the week with a lecture about Lean Start-Up models. Then as a group did secondary research on IoT Monitoring of buildings. We found a couple of similar products available on the internet and found a few research articles about the subject. Reports on those are in the works right now.

Friday 15.11.

Had a meeting with the project owner about our project and what the goals are. The meeting went well and we got a lot of insight into what our next steps should be to get our project underway. Our basic points right now for the project are listed below.

• Research room air quality standards and see if research data could be used in the project
• Plan on how to collect the data that we want to gather in our project
• Research machine learning on how collected data could be used to create behavior models
• Experiment with sensors to see how they behave, so quality data can be gathered.

These are things that we should start working on as soon as possible to end up with a good outcome for the project. A more detailed report of the meeting is in the works and will be posted later.

Introduction - Ife Olaleye

Hi there everyone!  I am Ifedayo Olaleye. Everyone calls me Ife J

I am a third-year student at TUAS specializing in Data Networks and Information Security. I studied earlier at OAMK for a year before transferring studies and moving to Turku.

At the moment, I am working and also an MBA student, so it is kind of hectic sometimes. I am also involved in some small-sized companies with IT-support related activities.

Many eons ago, I worked briefly for an ISP but then went to study. After graduating from my first degree, I worked in the Tourism, Leisure and Hospitality industry.  In my spare time, if and when I get one, I enjoy the outdoors, listening to music, movies, books, tech-related stuff.

I expect that the Capstone project will help develop some of my skills and learn new skills that would be essential for my future endeavours. 

Group Rules

• Inform the group if you are late for a meeting, or if you can't attend
• Do the work that is assigned to you
• Ask if you need help
• If you feel you have too much work, talk about it and we can delegate
• Do not be afraid to voice your opinion
• Give credit where credit is due

Week report - Week 45

Tuesday - Lecture and group meeting

On Tuesday we had a lecture on agile project developement, held by Matti Kuikka.

After that we had a group meeting where we clarified our team rules and made the letter of agreement, we also have a group communication channel in Telegram. We also came up with questions for the project owner and studied the contracts that we need to sign with the project owner. We also scheduled a meeting with the project owner for Friday Nov 15th, at 12 o'clock.

Friday - No meeting

For Friday we decided to not have a meeting since we have very little information about the project at this time. Group members should use this time to study the scrum training materials found at http://scrumtrainingseries.com/ and finish other individual tasks they still might have. Members can also prepare for next week by finding out about similar products or projects, and finding academic journals similar to the project.

Introduction - Minh Le

Hi, I am Minh Le, a 20-year-old, third-year student at Turku University of Applied Science specializing in Data Networks and Cybersecurity. I am willing to learn about Networking, Cybersecurity, teamwork and IoT also.

I have some programming skills in Python and C++.
In my free time, I like to play games, listen to music and play football. I am friendly but I am too reticent.

I hope this project helps me to develop my teamwork skills further, and could be a good place to do the whole project from the beginning. Also, I am looking forward to learning more about IoT devices which has been growing significantly nowadays.

Introduction - Eetu Kaasalainen

Hi!

My name is Eetu, I am 24 year old, third year business IT student at Turku University of Applied Sciences. Currently specializing in Networks and Information security.
 
I would say I am positive and friendly person who likes to cheer people up if they have done a good job on something.

My hobbies are PC-Gaming and being a Community Moderator

I except Capstone to be challenging project that I can learn alot from and I am really looking to work with the current group.

Introduction Patrik Nordlund

I am 27-years old, third year student in Turun AMK, I am specializing in the Networks and Information Security. Before coming to Turun AMK, I studied theology for 6 years in Åbo Akademi, so I am completely bilingual in Finnish and Swedish. 

I have some programming skills in Python and Java. 

My hobbys entail fixing laptops, playing on my pc as well as  boardgames and discgolf. 

I am having high expectations for the capstone project, as a learning experience, because I am always eager to learn new things, especially when it is IT related. 

Work experience:

Paf Gaming Host (sales promoting) - SP-Works - 2016/12 - 2019/01 
Summer Theolog - Keski-Porin Kirkko - 2016
Construction Work - Nicos Stall - 2013-2015 

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Introduction - Stockfelt Jan

Hello!

My name is Jan 27-year old, third year business IT student at Turku university of applied Sciences. Currently specializing in Networks and Information security. Currently unemployed but have worked previously in IT repair and sell in Jimm's PC store. Also have some previous experiences in PC-support.

Through previous experiences and studies, i have programming skills in Java, Python and JavaScript. I have also completed several Cisco CCNA certifications and i have a keen interest towards network and web application security.

In my spare time I’m avid gamer who likes lots of different genres. I also study nearly anything IT related which just happens to pique my interest. Some of the more recent topics have been about whit hat hacking and networking in general.
Other hobbies I like to do are going outside biking, playing snooker and sometimes play different ball games with friends.


From capstone I expect it to be challenging and a interesting learning experience. I'm also looking forward for any potential new skills i might be able to learn or develop during this period.

Introduction - Pyry Lahtinen

Hi!

I’m Pyry-Petteri Lahtinen, age 24. I study information and communications technology and I am specializing in data networks and cybersecurity. I’m interested in learning more about cybersecurity, teamwork and IoT technology.

I expect the project to offer me new insights on how to improve team effectiveness. I am also looking forward to learning more about the technologies we are going to utilize, coding and also project management in general.

My strengths include the ability to quickly grasp the bigger picture, keeping things light when everything is going well and shaping up the group when all is not. Qualities I could improve on are making sure I don’t walk over anyone’s opinion, making sure I communicate my vision concisely and understandably and making sure I start tasks on time rather than leaving them last minute.

For the past few years, I have been employed by DNA Kauppa Oy as a sales negotiator. I also have earlier related work experience as an IT-assistant and Telecommunications Specialist at Suomen Tietoliikenne Oy.

In my free time I dive into NPO work as a pastime. I am also a little bit of a nerd and a featherweight lobbyist.

Contact info:

Phone no.: +358 50 409 76 79

E-mail: pyry.lahtinen@edu.turkuamk.fi

LinkedIn: https://www.linkedin.com/in/pyry-petteri-lahtinen-9a8b22156/

Twitter: @PyryLahtinen

Introduction - Sami Laine

Hi!

I’m Sami, a 22-year-old third year student at Turku University of Applied Sciences. My field of study is business IT, and I specialize in networks and information security. I also work part-time at 2M-IT as an application specialist trainee.

I have programming experience with C#, Java and Python, and I also have some experience in making websites. Most of my expertise however is focused on networks and network security. I have several CCNA certifications, and I have knowledge on fields such as penetration testing, information security risk management and data protection and privacy.

In my spare time I like to listen to a lot of different kinds of music and read about music history. I also collect music on physical media (mostly vinyl, but also CDs). As I’m an IT student, I of course also love technology and games, and spend a fair amount of my spare time reading up on the latest trends in technology and gaming with my friends.

I hope this project helps me develop my teamwork skills further, especially in an English-speaking work environment. I also hope to learn a lot about IoT devices and their possible uses, since the importance of them grows every year.

Work Experience

• 2M-IT Oy – Application Specialist Trainee – 11/2018 –
• PerkinElmer Oy – IT Support Intern – 04/2018 – 06/2018

Introduction - Rami Takala

 

Hi, my name is Rami, a 26-year-old, third-year student at Turku University of Applied Science in Information and Communication Bachelor degree program. I am specializing in Health Care. I have worked for about three years before starting studies, mainly in the electronic industrial.

I have some coding skills in c, c#, and python.

My hobbies are ice hockey, floorball and of course computer games. So I have good skills for teamwork and I like to do work in a team.

I expect the capstone project is a good place to learn about teamwork and to do the project from 0. And for me it's good place to practice my English skills because I have to practice more for that, I can understand English but my produce in English is bad.

Work Experience:

Tepcomp Oy - AOI Spectator - 5/2019-8/2019

Tepcomp Oy - AOI Spectator - 6/2018-8/2018


SCF Huolto Oy - Service Mechanic - 8/2014-7/2017

Laukamo Electromec Oy - Collector - 1/2014-07/2014

Introduction - Matti Saastamoinen

Introduction - Matti Saastamoinen

Hi! I'm Matti, a 29 year old, third year IT-engineering student at TurkuAMK and I am specializing in Networks and Information Security. I also have a vocational qualification in business IT. I've worked in different industries before starting my studies at TurkuAMK, mainly in electronics and waste management. I currently work at 2M-IT as an Application Specialist Trainee.

I have skills in programming, mainly C++ and Python. I have also completed several Cisco CCNA certifications. While I was at Edututor I built an online shop with Magento.

My hobbies are anything related to computers and IT and disc golf.

I expect the capstone project to be challenging and a great learning experience. I am also excited to learn new skills that the project might introduce. IoT devices is an ever expanding field in IT and it's uses are near limitless. They also pose a major risk in information and connection security, so that is also something I want to learn about.

Work Experience

• 2M-IT Oy – Application Specialist Trainee – 9/2019
• Edututor Oy – Finnish eCommerce Academy Trainee – 3/2017 – 5/2017
• Kaukora Oy – Assembly Line Worker – 9/2012 – 2/2016
• ME-Group – Collector – 9/2011 – 12/2011
• L&T Turku – Material Sorter – 9/2010 – 4/2011
• L&T Tammisaari – Truck Driver – 6/2010 – 8/2010 and 8/2009 – 10/2009
• Finnish Net Solutions Oy – Trainee – 4/2009 – 5/2009
• Datatek Ny – Marketing Manager – 8/2008 – 4/2009
• Purkat Oy – Cleaner – 5/2008 – 7/2009

Links

My LinkedIn profile can be found here: https://www.linkedin.com/in/matti-saastamoinen

My GitHub profile can be found here: https://github.com/aldzor/