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Thesis - Machine learning to improve the User Experience i Lund

Axis enables a smarter and safer world by creating network solutions that provide insights for improving security and new ways of doing business. As the industry leader in network video, Axis offers products and services for video surveillance and analytics, access control, and audio systems. Axis has more than 3,000 dedicated employees in over 50 countries and collaborates with partners worldwide to deliver customer solutions.

Om tjänsten

Category: Machine learning, web development, UX

Scope: 2 students completing 30 credits (20 weeks) each.

Webpages get more advanced graphically and performance wise over the years. For example, webpages load faster today than they did 15 years ago. As the technology becomes better our standards as users gets higher as well. Examples of today standards is if a webpage takes longer than 3 seconds to load, 50% of the people will leave the webpage. If a page is not easy to navigate and the user do not find what he/she is looking for, they leave as well. Therefore, it is important to have a high standard website with a good UX (User Experience) design so users want to stay and do not use competitor's sites. Another way to improve the UX is by implementing AI (Artificial Intelligence). AI gets better and more implemented at websites more and more. There for it is important to apply AI to our products as well, to keep a competitor's edge.

How can AI improve the User Experience? One good example where AI improve the UX are a commuting app. A regular commuter mostly takes the same bus and train in the morning from their home to work, and the same buss & train back home after work in the afternoon. Thanks to a subfield in AI called machine learning which gather a lot of different data/variables tied to a specific event, it can predict outcomes and find patterns by analyzing the sampled data.

In this example the machine learning can predict which station the user is at and where she/he is going by just knowing the time. This is done by collecting the data the user puts in when he/she searches for a station, such as (fromstation, to-station, time, day of week). So when the user wants to go home from work at afternoon he/she just opens the commuter application and don't need to enter any stations. The application fills in the two search fields (from, to) for you, which saves you time instead of typing. Things like these can improve the UX.

We want to research where machine learning in the UX could be implemented in our products web interfaces to improve them, examples

• When a customer sets up a camera system and navigate through the menus would it help by navigation his/she mostly clicked menus to the top, instead of a static menu? Would that be helpful or annoying?

• In a test would a user like a more personalized machine learnt interface, or would a user like a generalized interface generated by studying thousands of users?

• By comparing thousands of user behaviors navigating a menu, machine learning could come up with a better static menu than a default one designed by a human?

 • When a user choosing default settings for options on a product could machine learning find and suggest what settings would suit this user with his/her circumstances. Example: “These Audio settings are commonly used for customers with stores, schools, large rooms ....”

Which students are we looking for?
Two students studying a software university degree, or one studying UX designer. The important is to have a student who is interesting in predicting behavior/patterns, analyzing data to find behavior patterns, have an interest in how design can improve a user's experience scientifically. You will work with web applications programmed in HTML, CSS, JS and React.

OK, I am interested! What do I do now?
You are valuable to us – how nice that you are interested in one of our proposals! There are a few things for you to keep in mind when applying.

  • Applications are accepted in both Swedish and English, and you apply via the proposal advert.
  • The announced theses are open only to students affiliated with a Swedish university/college either directly or via an exchange program.
  • When the thesis proposal states that it includes two students working together, we would like you to apply in pairs. In these cases, send one application each but make sure to clearly state in your application who your co-applicant is. If you have any questions regarding this, please do not hesitate to contact us.
  • Please attach your CV and University/college grade summary. 

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