Track Your Commute - Junke Zhao

Background

We commuted to campus by bus this semester, mainly on the 61A / B / C / D routes, and it was common to see them come and go all together. As the photo shows, it looks almost like a train coming through when four of them arrive at the same time. A visualization created by CMU alumnus Mark Egge is a striking illustration of how often the 61 routes bunch in the areas around campus.

Now imagine the weather turning bad just as you miss a couple of buses that arrived together — not a pleasant experience. We wanted a device that could show us the weather and bus status at a glance.

Concepts

The project would consist of a bus info display kit and a weather display kit.

The bus tracker would be a box with an embedded acrylic panel, lit from the inside by a NeoPixel strip or a few LEDs so it can display different colors. The interaction is designed to cue users through three moments: get ready to leave, head downstairs to the bus stop, and finally, be aware that they may need to catch a later bus. As a bus approaches, the light subtly shifts toward a blue or green hue; when it is nearly time to leave for the stop, the transition speeds up; and fading to yellow means the bus is either arriving now or already gone.

Precedent Study

Weather Systems by Studio PSK, Paper Signals by Isaac Blankensmith, and Tempescope by Ken Kawamoto are fascinating cases that signal and subtly display the weather through sound, visualization, and motion. Our key takeaway is that translating status into signals through different types of actuators opens up a wide range of possibilities.

Case Studies

Design Process

Our project is divided into two main parts: real-time retrieval of bus schedules and alerts, and a weather indicator. We worked on these two directions in parallel and kept them in sync. The first step was to pull the APIs for bus schedules and real-time snowfall and send the data to the Particle microcontroller. The second was to design how that information is visualized and interacted with — that is, how to represent the retrieved bus times and snowfall data on the IoT devices.

Process of Bus Tracker

For the bus information, we obtained an API key from Pittsburgh Regional Transit (PRT) and started from the data it provided. Among the available feeds, we found route data and vehicle locations most promising. We also tested PRT's webhook to see how the API behaves.

When we started testing with data from several routes at once, we could not visualize it legibly — the indicators simply became too complicated. So we went back to a single-route solution. We chose to feed our Argon with the predicted arrival times for the inbound 61D at Forbes & Morewood, the route that takes all of our team members from campus back to where they live in Oakland.

The photo below shows us testing the bus tracker on the serial monitor. We started by mapping the predicted arrival time to the LEDs' maximum brightness across a range of 255–100, so that a bus about to arrive would glow fully red and a distant one would show a dim blue. In practice, though, the dim ends of the yellow and blue ranges were hard to see. We therefore mapped each LED's brightness within its own time range instead, which made the changes far more legible at every stage.

Process of Snow Ball

Using the Open-Meteo weather API, we tested data requests for temperature, rainfall, snowfall, and weather codes. Rain and snow were reported as depth measurements, but we were not entirely certain how to interpret the exact values, so we used approximate ranges in our conditional statements.

We quickly realized that the solenoids couldn't produce enough force to move the beads through the air as intended.

Moving forward, we tested a 5-volt mini DC fan (photo below) and got promising initial results. Prof. Daragh suggested a more powerful 12-volt DC fan, which finally felt adequate for the project. To test the effect, we built a basic model from a plastic cup and an aluminum mesh screen. To keep the beads contained, Prof. Daragh recommended adding a rubber band, which proved very helpful. Of all the materials we tested, the foam beads were the most visually interesting, so we decided to focus on those.

The DC motor's back-and-forth motion during testing added a nice effect, smoothly oscillating on the granite countertop (see the YouTube video below). Additionally, we noticed that pointing the fan upward allowed the fan structure to block airflow to the center of the container. By reversing the fan direction, we created an airflow that effectively moved the beads across the container.

DC Fan Test

Final Outcomes

Bus Time Tracker

Snowball Indicator

Prototype Video