The fast rise of artificial intelligence, along with computer vision tools, is changing how we monitor exams in places like schools. Old-school ways of watching students during tests usually come with mistakes, personal bias, or gaps in attention - especially when hundreds take the test at once. To fix this, our idea is a smart exam watcher using AI that spots odd actions, keeps tabs on what students do, flags forbidden items, while making sure rules are followed as things happen. It uses advanced neural networks to recognize faces, follow where someone’s eyes move, detect objects, check body positions - all helping make oversight more solid and quicker. This setup combines a smooth front-end made with up-to-date design tools plus a back-end running ML workflows and protected data storage. Live camera feeds get analyzed instantly to catch warning signs: sudden head turns, constant glancing off-screen, phone use, or multiple people showing up unexpectedly. Notifications pop up on their own for supervisors, so they spend less time checking things by hand while tests stay fairer. This smart exam helper works without help from people, runs smooth whether it’s used online or offline, scales easily when needed, keeps data safe, shows what's happening clearly, avoids favoritism, spots odd behavior fast, cuts down errors, saves effort across schools and boards alike.
N et al. (2026) studied this question.
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