For my midterm I built RU Stealth—a radar system that connects an Arduino and ultrasonic sensor to a live, sweeping display on screen. The video below shows it in action: the hardware pings the room, sends distance data over serial, and Processing draws the radar in real time.

Video Walkthrough

Behind the Scenes: RU Stealth 📡

Here is a quick write-up to accompany my midterm video, RU Stealth: Real-Time Radar Visualization.

The Purpose & Audience

I made this walkthrough primarily for recruiters and other computer engineering students. The main goal is to show actual systems engineering in action—specifically the data pipeline and the "handshake" between the hardware and software—rather than just showing off a finished UI. When you are building a complex project, understanding the underlying communication protocols is just as important as the final output. This video is meant to bridge that gap by showing the raw logic behind the system.

Tools I Used

I utilized a few different tools to put this project and video together:

Finding the Video & Why It Matters

I am hosting this video on YouTube and embedding it directly on my portfolio. I expect some people to find it by clicking through my resume or by searching for Arduino-to-Processing integration tutorials. However, as Christine T. Wolf notes in her research on DIY video consumption, what users actually end up watching is heavily dependent on the platform's "recommended" or "related" video algorithms (Wolf, pp. 266, 281). Therefore, I anticipate some viewers will discover my tutorial through the related sidebar while watching other maker videos.

When it comes to why viewers will find it worth watching, it boils down to authenticity and practical proof. Wolf points out that viewers evaluate the credibility of a video using a "speaking for itself" heuristic, meaning a video gains credibility when viewers can see the finished project actually functioning at the end (Wolf, p. 241). By showing the actual radar sweep working accurately, I establish that credibility. Furthermore, viewers often harbor skepticism toward highly polished commercial tutorial videos because they use time-lapse editing to make complex projects seem unrealistically easy (Wolf, pp. 253–254). Instead of a sanitized corporate overview, my video provides an authentic look at the raw data flow, the math, and the logic. This transparency allows other students to engage in their own "risk management," helping them assess if they have the skills and confidence to attempt a similar hardware-software integration themselves (Wolf, p. 216).

References

Wolf, Christine T. “DIY Videos on YouTube: Identity and Possibility in the Age of Algorithms.” Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ACM, 2018, pp. 1–12.