Math proofs to implement algorithms to detect and predict most likely clickable elements in web pages.
A more in-depth understanding on front-end languages like HTML/CSS.Learning how to make a Chrome extension.Integration with servers like Firebase proved difficult owing to security constraints.Difficult to communicate as we were doing the hackathon virtually.Not all pages built the same, so HTML/CSS part did not work perfectly on all components of all pages.Some Chrome extension API was deprecated.If the user likes the prediction, they can simply click at their current cursor position, taking them to the next page and expediting the browsing process! Challenges we ran into Using information from the direction, the algorithm finds the most relevant clickable object within a fixed field of view from the cursor and animates that object. The script goes through the website identifying all possible clickable objects such as buttons, images or links. Using this, over a small window, a vector is created for the direction of the cursor movement. Once activated, the extension takes snapshots of the user's cursor at fixed intervals. The object will be highlighted for the user and they may click wherever they are to simulate a click on that object. What it doesīased on the user's mouse movements, Cruiser Cursor will try to find the most relevant clickable object in that direction. So, we decided to ideate on a tool that would allow users to browse the web on cruise control. When surfing the web for an extended period of time, all the wrist movement could add up, resulting in muscle strain. Web surfing is mouse intensive, especially for pages with an abundance of links. We were inspired by hotkeys and aimbots for games and wondered how other actions like mouse movements could be made more efficient.
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