AimSense: AI-Powered Real-Time FPS Gaming Assistant Using Computer Vision

Muhammad Affan I. Mastan, Farhan T. Moula and Gousiya A. Khanche

International Journal of Scientific Research in Science and Technology, 2026, vol. 13, issue 3, 940-945

Abstract: First person shooter games need players to make decisions and react quickly to what is happening. Players also need to keep their aim accurate the time they are playing. There are some tools that can help players practice their aim. These tools are usually separate from the actual game. This means they cannot give players feedback while they are playing. We made a system called AimSense to fix this problem. AimSense uses computer vision to look at what's happening in the game in real time. It then gives players information about how they're doing. The system uses a tool called YOLOv5 that was trained on a lot of pictures from first person shooter games. The system looks at the game frames all the time to find where the enemies are and to see how well the player is doing. It checks things like how the players crosshair is aligned and how quickly they can react. AimSense does not need to access the games memory or use sensors. Instead it just looks at the screen, which makes it less annoying and more compatible with systems that prevent cheating. When we tested AimSense it was very accurate. The system can find enemies even when the game is changing a lot. This means it can give players feedback about their performance. AimSense shows how computer vision can help players practice their aim and get better at the game. It does this without hurting the players privacy or making the game unfair. AimSense is a system that helps players with first person shooter games. First person shooter games are games that require players to make decisions and react quickly to what is happening. AimSense is a tool that helps players, with these games.

Keywords: Artificial Intelligence; Computer Vision; YOLOv5; Esports Analytics; First-Person Shooter Games; Real-Time Object Detection (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v13:y2026:i3:id:1685

DOI: 10.32628/IJSRST26133218

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