Determine optimized methods for user interaction to capture failure incidents - ON-209
Preferred Disciplines: Computer Science focus on UI and mobile apps, post-Masters preferred
Company: Anonymous
Project Length: 1 year (2 units)
Desired start date: As soon as possible
Location: Kitchener ON, may be a split team with some in Toronto
No. of Positions: 1
Preferences: Colleges and Universities in Kitchener/Waterloo area. Strong preference for institutions without onerous IP requirements.
About the Company:
Organization is an AI startup focused on harvesting and enriching data related to product defects for sale to corporations.
Project Description:
The aim of this assignment is investigation of methods to minimize user interaction with a mobile app while capturing as much information as possible (context is user’s situation requires they can be only minimally distracted). Proof of success is a prototype app that can capture incident information and transmit it to a data lake for downstream inspection and processing.
Research Objectives:
- Investigation and documentation of scenarios for minimal interaction.
- Investigation and discovery of techniques to interact with users in these scenarios.
- Creation of an app that allows the techniques to be tested for user interaction and robustness of data captured.
Methodology:
The overall (multi-position) objective is to create a data lake with a visualization dashboard that can support analysis:
- Find unique sources of data that relate to reviews of consumer products
- Analyze these sources of data for added value and clean
- Set up an online repository to collect these raw sources of data
- Implement ability to tap into external APIs (e.g. weather, traffic) for additional raw data
- Load raw sources of data into distributed database
- Attach a visualization tool that can support dashboard analysis
- Investigate any correlations using AI or statistical data science, e.g between location and weather at time of incident
- Implement an emulation of a mobile app that can inject glitch data into the data lake with automatic ability to lookup external data
Challenges:
- Data might be biased for example not updating amazon reviews during a product life cycle
- Need to investigate novel sources of data that can supplement primary sources - data may not be readily available
- Sheer quantity of data available (that can be scraped) is enormous
Expertise and Skills Needed:
- An understanding of how HTTP works specifically REST architectures for API development
- Proficient in the Python programming language for API development
- Knowledge and/or experience with the micro web framework Flask a plus
- Knowledge and/or experience with React a plux
- UX expertise, particularly in unusual user contexts
For more info or to apply to this applied research position, please
- Check your eligibility and find more information about open projects
- Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform.