Project develops an AI-driven, low-cost blood centrifuge to improve diagnostic testing in underserved areas, suggesting enhanced healthcare access.
Blood centrifugation is a crucial step in diagnostic testing; however, many rural and low-resource healthcare centers lack access to standard centrifuge machines due to high cost and maintenance requirements. This project proposes an ultra-affordable, portable smart blood centrifuge integrated with Artificial Intelligence and Internet of Things technologies. The device employs a high-speed motor to separate blood components, while an embedded camera continuously monitors the separation process. AI algorithms analyze the captured images to accurately determine the completion of plasma separation, preventing over- or under-centrifugation. An IoT module enables real-time monitoring and status notifications through a mobile application, allowing safe and remote operation. By reducing dependence on skilled manpower and conventional laboratory infrastructure, this intelligent system enhances diagnostic reliability and supports timely clinical decision-making, making it highly suitable for primary healthcare centers, mobile medical units, and underserved regions.
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Yogapriya et al. (2026) studied this question.
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