Detection Techniques Development

Closed
Grass Oceans Ammolite
Lethbridge, Alberta, Canada
Caitlin Furby
CEO
(13)
4
Preferred learners
  • Anywhere
  • Academic experience
Categories
Software development Machine learning Artificial intelligence Databases Hardware
Skills
analytical techniques data collection algorithms machine learning chemical composition data analysis spectroscopy
Project scope
What is the main goal for this project?

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.

What tasks will learners need to complete to achieve the project goal?

Project Description:

In this project, students will work together to design and implement detection techniques for material identification. The project consists of the following key tasks:


Detection Technique Selection:

  • Students will study the characteristics and properties of the materials of interest (resin, dyed materials, natural minerals, and rocks).
  • Based on the materials' properties, they will select appropriate detection techniques. For example, spectroscopy for chemical composition analysis and X-ray diffraction for mineral identification.

Experimental Setup:

  • Set up the necessary equipment and instruments for the chosen detection techniques.
  • Ensure that the equipment is calibrated and ready for data collection.

Data Collection and Analysis:

  • Students will collect data from samples representing different materials.
  • Analyze the collected data to identify unique signatures or patterns that distinguish between materials.

Algorithm Development:

  • Develop algorithms or methods for automated material classification based on the analysis of the data.
  • Explore machine learning techniques if applicable to improve classification accuracy.


Project Deliverables:

Upon completion of the project, students will deliver the following:

  1. Detection Technique Implementation: The implementation of selected detection techniques, including the experimental setup and data collection process.
  2. Data Analysis Results: An analysis of the data collected, highlighting the unique signatures or patterns used for material identification.
  3. Algorithm Prototypes: Prototypes of algorithms or methods for material classification based on the data analysis.


About the company

Grass Oceans Ammolite is a harmonious blend of a geological museum, a gemstone emporium, and a restoration workshop all rolled into one, making it the ultimate haven for fossil enthusiasts, collectors, and anyone with a curious spirit.