MotionLab.Berlin – Hardware Innovation Hub & Makerspace

How #keeptheboxgreen increases your productivity

#keeptheboxgreen

A lot has happened in the last few years. Progress is happening and many areas are rapidly driving innovation. But despite this, there are still many things in which too little has changed – especially when it comes to social responsibility, climate justice and environmental protection.

 

And that is precisely where we see our responsibility. We make things right and wake up industries. We are shaking up those who have been asleep for so long. And we do it, with the most talented students and the strongest partners we could find. We make up for what didn’t happen. We MakeUp Internet of Things!

 

Together with CODE University for Applied Sciences, the German Federal Ministry for Economic Affairs and Energy (BMWi) and the IoT+ Network, we developed the MakeUp Internet of Things incubation program. Over a period of two years, more than 130 students will complete the program and be trained as experts in the field of Internet of Things (IoT). The goal is to educate within IoT and promote the realization of IoT projects by combining technical knowledge with software programming and the construction of physical products.

Today we find out in the report from Irina Baeva, Soyoon Choi and Jongwoo Park how productivity means to #keeptheboxgreen.

#keeptheboxgreen

Project description

The project idea came from personal experience and needs. Since we are working as software developers, we spend most of the day next to laptops. Sometimes we forget that it is time to have a break or watch out for posture. So we thought it would be helpful to collect the data during the workday, remind users about their working conditions, and give some tips like “have a break” and so on.

 

Why is it important? We checked studies and found that temperature is one of the measurements on which our productivity depends. “The temperature of the working environment affects the performance of the workers in physical and psychological ways (1)”. Also, “The indoor temperature affects several human responses, including thermal comfort, perceived air quality, sick building syndrome symptoms and performance at work. (2) ” The similar findings are for humidity, dust level and importance of taking a break. Our team decided to work on a lightbox that reacts to different measures with the light and tips on the display. We had a goal to have at least an MVP device by the end of the semester: a lightbox, which has sensors such as temperature, humidity, dust level and logic to change color of light and messages. For measuring desk time, we consider that the user changes the distance between themselves and the lightbox for not more than 50 centimeters for some time to trigger the desk time measure. Besides building the device, it was essential to figure out the flow of sensor data from the device to a simple web app.

 

Based on the above description and considering that it was our first experience with IoT, we set the following goals for the semester time:

 

  1. Build MVP lightbox based on different sensors with breadboard
  2. Learn basics of electronics and soldering and move from breadboard to more
    stable implementation
  3. Collect sensors data in the cloud database
  4. Build a small api to serve the data for web app
  5. Build a small web app to display data.

Project implementation

We started the project from complete scratch. During the brainstorming period, we used visual brainstorming with Mood Boards.

#keeptheboxgreen - moodboard
Figure 1. Visual brainstorming: mood board for an idea.
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Figure 2. Visual brainstorming: mood board for device shape.
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Figure 3. Visual brainstorming: mood board for LCD.

We did a very basic sketch of our idea during the MotionLab.Berlin workshop.

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Figure 4. MotionLab prototyping.

Before starting the implementation process, we researched optimal values.

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Figure 5. Optimal constants

Also, we created a fritzing schema of the MVP.

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Figure 6. Using fritzing software for the circuit

The first step was to find the board. We were considering Arduino MKR WIFI 1010 and esp32. Even though esp32 seemed faster and more professional, we decided on Arduino. One of the reasons to go with MKR WIFI 1010 was the WiFI connection which we need for time-series data. So we configured the board to connect to WIFI securely with self-issued certificates stored in the board. Before starting with sensors, we attended the MotionLab.Berlin workshop to understand electronics and be more confident with reading schemas. During the workshop, we built a Tesla coil. It was exciting and fun. In addition, we learnt how to solder, which helped us to build a more user-friendly board.

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Figure 7. Electronics workshop

The workshop gave us the confidence to start building the project.

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Figure 8. Building process

All the time, we were missing some design knowledge in order to figure out the case of the device. For the middle term presentation, we came up with the idea to use an Ikea lamp.

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Figure 9. Building process

During the second part of the semester, we decided against starting to work on posture
detection but worked mostly on improving the UX of the device.

Figure 10. Improving UX
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Figure 11a. Working on soldering
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Figure 11b. Working on soldering
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Figure 11c. Working on soldering

We had an idea to implement some more logic with the humidifier, but it did not work out, because it would be dangerous to use next to a laptop or electronics and this consideration needed extra design decisions.

#keeptheboxgreen
Figure 12. Atomisation module connection

Hardware

Hardware used during the first stage implementation:

  1. Arduino MKR 1010 Board
  2. DHT22 Sensor
  3. HC-SR0 4Ultrasonic Sensor
  4. LED Strip
  5. 1.8″ TFT Display
  6. Nova PM SDS011 PM 2.5 sensor
  7. Protoboard

For posture detection, we ordered raspberry pi and a camera, since Arduino does not have enough processing memory.

Source code and project documentation

Arduino: [link]
Device documentation: [link]
API docs (serving data from database): [link]
Production API showing all data: [link
Mid-term video gif – [link]

Status of the project and next steps

Currently, we have finished all implementation of the main logic of the device. But we are still missing the casing.

 

Next steps:

 

  1. Implement a very simple box using the laser cutter so we can finalize the main
    part of the project.
  2. To learn how to implement posture detection with raspberry pi, but this step we
    are going to do at our own pace.

(1) A study on the effects of weather conditions on the worker health and performance in a construction site. Sadık Alper Yıldıze [link]

(2) Effects of thermal discomfort in an office on perceived air quality, SBS symptoms, physiological
responses, and human performance. Li Lan [link]

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