Tricorder-Like Device Design Project

The main goal for the project is to create three 3D renderings of tricorder-like devices, modernized for contemporary use in the rock, gem, and fossil industry. The prototypes will be designed in three versions: an industrial model, a phone attachment model, and a handheld model. The primary function of these devices will be to analyze and identify the composition of rocks, gems, and fossils, and present the results in a user-friendly manner to democratize access to scientific information.

Detection Techniques Development

In this project, students will collaborate to develop and implement detection techniques for material identification. They will explore various analytical methods such as spectroscopy and X-ray diffraction to analyze and classify different materials, including resin, dyed materials, natural minerals, and rocks. The goal is to lay the foundation for accurate material identification in subsequent phases of the project.

Machine Learning Model Development for Material Identification

In this project, students will collaborate to develop machine learning models capable of accurately identifying different materials, including resin, dyed materials, natural minerals, and rocks. They will explore various machine learning algorithms and techniques to build robust models for material classification, contributing to the development of a reliable material identification system.

Machine Learning Model Development for Material Identification

In this master's level project, students will collaborate to lay the essential groundwork for the development of a tricorder-inspired material identification device. The focus of this phase is to design, train, and evaluate machine learning models that will form the intelligence behind the tricorder. The project comprises key tasks aimed at preparing the necessary data and selecting models for effective material identification.