Group task 21 – Scrum planning

On last Friday we had a Scrum meeting where we selected a Scrum master for this sprint and discussed future tasks and everyone’s parts in doing these tasks. We’ve also updated these tasks to Trello, which we use to keep track of our project.

In short, the tasks are as follows:

Sami, Matti and Rami – Raspberry Pi, sensors and NB-IoT connection

Patrik, Jan, Pyry and Anastasiia - Programming

Ife, Minh and Eetu – Machine Learning and Azure

Jan will also be our scrum master for this sprint.

The main outcomes of the week were already covered in the week report, where you can find more about how our week went.

Week Report - Week 4 - Progress!

On Tuesday we finally made some progress with the Raspberry Pi and the sensors, as we got some readings from the sensors! Next, we need to decide how to store the data, and more importantly how to get it transferred over the internet. We still have some problems with the cellular connection, as we can’t get the connection working. We think there might be a problem with the data subscription, but we need to investigate that further.

Thursday we had a PO meeting, which was also attended by some representatives from the city of Turku. We will have another blog post going slightly more in depth on the details of the meeting, but in short, the city of Turku has a similar project to that of ours, and we will be comparing results and other differences between our sensors and theirs.

On Friday’s meeting we discussed the PO meeting, and how we should move on from here. Unfortunately, Matti was sick and since he had the Pi and the sensors, we couldn’t do much practical work. We did review some of the code we used to get the sensors working and created a GitHub repository for working on the code.

This week we also got a brand-new team member, Anastasiia! It’s hard to bring in new people when the project has already been going on for a while, but we did our best to get her up to date with all the stuff we’ve been doing and added her to all of our workspaces.

Week report - Week 3 - Pitch review

First blog post of the decade!

This week was the pitching week and our pitch was held by Matti. The pitching went alright despite Matti losing his train of thought towards the end of the pitch. Luckily the slideshow was easy to follow. Sadly, we didn’t make the pitching finals but overall the group was content with the results.

Now that pitching is over and done with, we can start focusing on our project full force. We set a PO-meeting with us and representatives from the City of Turku for Thursday next week. We also have been working on reviewing code made by past groups and have been hard at work with getting our NBIOT device to work and the connection running.

Our peer review groups for the pitching were Jameshaft and Jobitti. Here is our comments on the groups:

Jameshaft

The slides maybe had a bit too much text, but otherwise the presentation was good. Speech was well delivered and captivating. Ending the presentation with a slogan was a nice touch.

Jobitti

A well-rehearsed and captivating presentation. Speech was clear and understandable and delivered well. The start of the presentation immediately caught your interest and had you listening through the whole presentation. Could have more slides to have a visual representation of the project as well.

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.