Computer Science and Engineering Projects

Key Objectives:
1. Add inventory management features to pre-existing data organizing web app.
2. Implements several new views to the program to enable the user to find and manipulate data in new ways.
Expected Deliverables:
1. Rapidly enter information for cataloging items in the order she specifies in the template.
2. Photograph the item and have that be entered as one of the templated fields.
3. Query for items that match arbitrary criteria and display them as specified by the template.
4. Switch between the spreadsheet for viewing all items and the view that displays a single item.

Key Objectives:
1. To have a software platform to support the demonstration and execution of KSL based simulation applications
2. To make it easy to develop and deploy KSL based web-applications
Expected Deliverables:
• KSL users will be able to log into a secure, web-portal that enables them to meet and interact with other KSL users, learn about and run shared KSL models, and deploy and share their own KSL models with clients and other KSL users via web-applications.

Key Objectives:
• To make it easy to develop and deploy animations of KSL simulation models
Expected Deliverables:
• At the end of this project, KSL users will have the ability to develop and deploy 2-dimensional animations of their KSL models. The animations will be able to be viewed on Windows, Mac, and Linux based operating systems.  KSL users will be able to record and share the simulation animation files.

Key Objectives:
• Aims to investigate the impact of weather conditions and large events (concerts, pandemics, hurricanes) on supply chain performance, particularly focusing on the timeliness of shipments from warehouses to distribution centers for retailers such as Walmart, Amazon, Target.
Expected Deliverables:
1. This is a greenfield project with a goal to build a web service that provides features that:
a) Explains past supply chain delays using weather and significant events
b) Predicts future supply chain delays
c) Cost analysis of past supply chain disruptions

Key Objectives:
• Environmental monitoring is key to running a healthy datacenter. Brand new equipment such as HVAC systems and Electrical systems often have new monitoring systems integrated but older equipment lack methods to actively monitor and notify datacenter staff if issues occur and track environmental health.

Expected Deliverables:
1. Development will be within an AWS subscription which is provided to the team.
2. Sensor hardware will be provided. A discussion of the best hardware to use will kick off the project.
3. The CGI team will be responsible for setup and configuration of the Asset Hive application within AWS.
4. Sensors should be programmed using Micropython
5. A server infrastructure for data collection and storage should be developed to securely ingest and store data into the database within AWS.
6. A front end will need to be developed within the Asset Hive application to view real time and historical data and create thresholds for notifications.
7. CGI team will work with the UofA team continuously to assure success. 

Key Objectives:
1. This project’s objective is to reduce the cost of constructing complex multi-scale biological models. Our solution focuses on allowing users to utilize pre-existing models when constructing their own biological model.
2. The goal is to have the solution be user-friendly and performant: users should be able to get results quickly.
Expected Deliverables:
1. Researchers will be able to plug-and-play multiple biological models instead of developing their own platform to simulate the models.
2. Running the model simulations will allow researchers to test hypotheses by saving the results of the model variables, which the researchers can use to compare with expected results.
3. Platform will run simulations in a time and resource efficient manner and make predictions that researchers can use to diagnose diseases and develop treatments.
4. Multiple computational biological models can be run such that outputs, or variables, of some models will be inputs, or parameters, of other models.

Key Objectives:
1. To create an app that manages all aspects of data associated with running an ice cream business.
Expected Deliverables:
1. An app that:
a) Tracks and stores basic info about the employee.
b) Uses data from employee’s work availability to build a schedule for scheduling manager.
c) Keeps track of inventory and basic info about the item. Keeps track of expenses.

Key Objectives:
• To create a web portal that automates processes to reimburse families for medical travel.
Expected Deliverables:
• The reimbursement process will be automated by web portal, requiring very little manual effort from applying families.

Key Objectives:
• The team will design and build a vehicle to navigate an obstacle course.
– A successful run is one where the vehicle navigates around 4 waypoints and crosses the finish line in under 5 minutes.
Expected Deliverables:
CSCE team will:
1. Help design the communication protocol for communication with hardware
2. Design software to interpret video and other input to determine where to navigate
3. Design software to drive the car to follow the computed navigation

Key Objectives:
• Students will design and build a device that will monitor, record, and analyze data that leads up to a transistor latch-up.
Expected Deliverables:
1. A physical set-up must be designed to allow devices to be electrically exercised to the point where the device will latch-up occur.
2. Enough data must be recorded to allow the user to determine the conditions of the latch-up.
3. This data must be transferred to a PC for graphical display and analysis and to record the results of the experiment in real-time.
4. There will also need to be some embedded system programming to interface with the PC. The interface on the current board is USB 2.0. This is based on a TMS32G0 processor.

Key Objectives:
• Characterize the costs of various types of high-performance computing tasks
– When supporting them on-site
– When having them hosted in the cloud

Expected Deliverables:
1. Perform background research to determine widely used categories of high-performance computing (e.g. molecular dynamics simulations, machine learning model training, big data analytics, etc.).
2. Acquire and/or build an example software package and dataset for each category.
3. Develop a framework that can be used to run each and collect data about its resource usage.
4. Collect data about various cloud computing services and their pricing.
5. Collect data about the costs of purchasing and maintaining hardware necessary for each type of computing task.
6. Chart the estimated cost of each type of computing task when performed locally versus using various cloud computing providers.

Key Objectives:
• We are interested in exploring the challenges related to applying machine learning algorithms to produce real-time analysis and feedback to a musician’s practice
Expected Deliverables:
A software tool that:
• Displays a musical excerpt for a performer
• Measures particular elements of the performance, like pitch, rhythm, and dynamics
• Compares these performance metrics to the desired metrics indicated by the musical score
• Provides feedback and performance tips based on the performance
• Applies machine learning algorithms for real-time analysis, improving accuracy and adapting to the musician’s changing performance quality

Key Objectives:
1. Develop a comprehensive penetration testing environment where students can simulate and perform ethical hacking techniques.
2. Provide a hands-on experience for students to understand vulnerabilities, exploit development, and security best practices.

Expected Deliverables:
1. Virtual Lab Environment
2. Attack Scenarios and Exploits
3. Defense Mechanisms and Documentation
4. Penetration Testing Report Generator? (Maybe just the report)

Key Objectives:
• To develop a tissue processing unit that can be built in under-developed countries.
Expected Deliverables:
• The hardware components of the Tissue Processing Unit will require software to control them.
•The software will have two main functions:
1. Device setup:
a. Which stations need to be used during the process, the duration of each stage, etc.
b. This will require a communication protocol set up with the embedded system
2. Alert system:
a. If the worker is not present, when the system is on the final stages there needs to be an alert so they will know they need to get back to get the sample
b. This will require a cell modem in the embedded system or communication over WiFi
c. Research and discussion will be required

Key Objectives:
• Develop a “lab ecosystem” composed of a set of software tools that are well-integrated and allow for the full spectrum of communication and data persistence needed for research lab projects, while also making searching for information quick and easy.
Expected Deliverables:
1. Will provide the following features for projects:
a)Taggable components
b)Fully searchable by name, date, project, and tags.
c)Versioning for software, etc.
d)Safe storage for large files, and large sets of files.
e)Easy remote, simultaneous collaboration.

Key Objectives:
1. Web app that gives the farmer remote control over their rice fields.
2. Can raise the gates both automatically and manually by input from the farmer.
3. Sends alerts to the farmer:
a) Incoming severe weather
b) Detection of drastic changes in water level
Expected Deliverables:
1. GateMates interface will be intuitive and easy to navigate.
2. The application will be customizable to each farmer’s needs: different crops, locations, multiple fields, and more.
3. The application should be able to integrate and communicate with physical GateMates, weather APIs, and sensors reliably.
4. GateMates design should allow for easy scalability. Many farmers should be able to access the GateMate application with no performance issues.
5. Implement robust error handling mechanisms, allowing GateMate to handle errors and problems gracefully, ensuring uninterrupted functionality.

Key Objectives:
• Provide a real-time, user-friendly navigation assistance to mitigate confusion and inefficiencies associated with navigating the ENRC building.
Expected Deliverables:
1. Conduct a thorough analysis of the ENRC layout, identifying key navigation pain points.
2. Develop a mobile application (Android and/or iOS) that users can download and use to navigate the ENRC.
3. Developers can implement one or more navigation modes, including 2D floor plan navigation, 3D navigation, and/or augmented reality (AR) navigation.
4. Ensure the navigation system integrates seamlessly with the building’s existing Wi-Fi network.
5. Develop an administrative interface for building management to update room information and manage beacons or other hardware.
6. Conduct extensive testing within the ENRC to ensure accuracy and reliability.
7. Deploy the system and provide user training and support as needed.

Key Objectives:
• To streamline the collection, storage, and analysis of seat belt use data, significantly enhancing efficiency and accuracy.
Expected Deliverables:
1. The mobile app will include:
a) User-Friendly Interface: Designed for ease of use by field observers.
b) Real-Time Data Entry: Observers input data directly into the app, eliminating the need for paper forms.
c) GPS Integration: Automatic recording of observation site locations ensures data integrity.
d) Photo and Video Capture: Optional features for documenting observations visually.
e) Data Validation: Built-in checks to minimize data entry errors.
f) Synchronization: Real-time data synchronization with a central database.
g) Offline Functionality: Ability to collect and store data offline, with automatic syncing when an internet connection is available.

Key Objectives:
• A software/hardware system that can be used as a research tool to explore the effectiveness of different machine learning classifiers on data collected while a rotary machine is in operation.
Expected Deliverables:
1. A software tool that utilizes libraries of existing ML classifiers and existing training data.
2. Imports accelerometer data from the data acquisition hardware
3. Outputs the results of classification from multiple ML classifiers while the fault simulator is running.
4. Software classifier tool operates on a deployable device to simulate a maintenance tool.
5. Has some user interactions such as changing a method of feature extraction or using the tool to collect and record more training data.