Resistor Sorter System; Artificial Intelligence: An Analysis of Scientific and Societal Perception

The Technical Capstone Project specifically focuses on the electrical component, the resistor. Often utilized by electrical engineering projects, the resistor (measured in “ohms”) restricts and resists the flow of electrons through it, allowing for more control over the designed circuit. Every resistor contains colored bands on the outside casing representing the value of its resistance. Normally, resistors of all measurements can get mixed up with one another and it is up to the person working with them to manually go through each one and sort them if they wish to keep them organized by value. In this project, the colored bands are analyzed using a camera and computer vision to electronically determine the resistance value. Once the value is determined, it is sent via a Bluetooth signal to a microcontroller that interfaces with a small stepper motor. This motor will spin an angular distance that corresponds with the value of the resistor that was obtained earlier in the process. A “slide” connected to the motor will then guide each resistor down into different sorting bowls that will contain each of the resistors of common values after all of the sorting has completed. Ultimately, the goal of this project is the assistance of facilitating organization of key parts for a project. With that said, any group of objects that could be sorted can utilize this system.
The subject of the STS research paper revolves around AI and its integration into society, particularly developed countries. Since the technology is in its infancy, scientists and the general public alike are both excited and anxious regarding the future of AI. The STS paper specifically focuses on answering the question: how does the varying level of perception in the current state of artificial intelligence shape societal and technological interactions? To answer this question, documentary research and an interview with a university professor will be used as methods. Furthermore, the STS framework of co-production will be used to scope the question and ultimately provide more insight into how AI and the users of AI interact as the technology is still developing. Ultimately, the goal of this research is to provide more insight on the topic of AI and how society as a whole can better prepare for a future with AI implemented in it. The outcomes of this project will have significance in the field of engineering and STS in that engineers developing AI will have to remain thoughtful of not only the users of their products, but the potential societal implications of how even small AI advancements in the present can affect the future in drastic ways.

School of Engineering and Applied Science
Bachelor of Science in Computer Engineering
Technical Advisor: Harry Powell
STS Advisor: Bryn Seabrook
Technical Team Members: Robyn Guarriello, Joseph Laux, Kiri Nicholson