College of Computing and Software Engineering 2020-2021 Projects

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  • 2020-2021 First-Year Scholar: Taylor Blade, computer science

    • VMControl: A Mobile Application to Control Robotics via Voice and Motion

      This project is a sub-project under the big future learning environment project, which is to create a smart and student-centered learning environment through integrating the Internet-of-Things (IoT) technologies. The ultimate goal of this sub-project is control the instructor system (such as PowerPoint slide control) by audio or motion commands recognized by the implement mobile app. In this project, the student will do the Proof-of-Concept implementation on homemade robotics.

      To be more specific, for this project, the student will design and implement a mobile app to recognize the pre-set audio commands (such as move forward, move backward, spin, etc.) through integrating Amazon Alexa API, and the pre-set motion commands through building a machine-learning model, which analyzes the accelerometer and gyroscope data collected by the mobile device. The recognized commands will be saved in Google Firebase (cloud database), which can be fetched and executed by the homemade robotics. The homemade robot car consists of a Raspberry Pi as the brain, a motor controller, and a 4-wheel chassis. The Raspberry Pi can fetch the command from Firebase and then translate the command into the corresponding Python scripts, which can fully control the motors on the robot car.

    • The learning objectives include being able to:

      • know how to get the real requirements of a practical project
      • investigate how to use React Native to build cross-platform mobile application
      • complete the mobile application Graphic User Interface (GUI) design
      • investigate how to integrate Amazon Alexa API into the mobile application development
      • become familiar with how to save, pre-process, and analyze the sensing data collected by mobile device
      • investigate the best suitable machine-learning model to detect the pre-set motions based on the collected accelerometer and gyroscope data
      • learn and practice the latest IoT technologies
      • conduct the system performance evaluate to help how to revise the app and help users
      • work collaboratively as a team with other undergraduate and graduate students in our College of Computing and Software Engineering (CCSE) IoT Lab.
      • present and demonstrate the application results
      • write technical implementation reports
      • Weekly meeeting and reports
      • Front end GUI design and implementation
      • Back end design and implementation
      • Machine learning algorithm design and implementation
      • Sensing data collection, pre-processing, and analyzing
      • Application performance evaluation
      • Present and demonstrate the mobile application
      • Final implementation report
  • 2020-2021 First-Year Scholar: Tyler Holmes, computer science

    • Building Modern Services with Security Assurance in the Edge Infrastructure

      This project aims to address these critical security issues by using adaptively data-driven execution model in the cloud-edge systems, including various IoT devices, and revisiting how they affect resource management and energy consumption. It also helps in learning and usage of resource control as the IoT devices should be capable of running two or different applications on the same time. The goal of this project is to explore the possible solutions to improve the security of the modern edge services and propose solutions to advance the reliability of the edge infrastructures.

      Specifically, this project will help you achieve the following outcomes: 1) Understanding the techniques and concepts of using these IoT devices for better implementation; 2) Analyzing the semantic gaps in the cloud and the edge, and design augmented abstractions to bridge the gaps; 3) Using the data-driven execution model to provide effective, efficient, and secure components; 4) Increasing the fundamental understanding of cloud-edge systems in resource management and energy control.

      1. Attain an ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs
      2. Gain system research skills through weekly meeting
      3. Gain knowledge in using IoT devices to run different applications with much efficiency and better performance
      4. Work collaboratively with other undergraduate and graduate students
      5. Improve the ability to solving real-world problem by self
      1. Weekly group meeting and report the progress
      2. Share the results on Microsoft Teams with advisor in discussion
      3. Design and implement a computer-based system
      4. Evaluate the system performance using microbenchmarks or applications
      5. Present work at C-day
      6. Participate in advisor NSF grant proposal preparation
      7. Accomplish a final report and complete a research paper