This paper presents a novel approach for predicting a driver's risk of developing smart IoT based biomedical heart rate oximeter using artificial intelligence and deep learning techniques. The use of wearable medical devices has increased significantly in recent years, with a focus on monitoring vital signs such as heart rate and oxygen saturation levels. In the automotive industry, car-driving safety has become a major concern, and integrating these medical devices with the Internet of Things (IoT) technology can provide real-time monitoring of drivers' vital signs for safer driving. In this study, we present a guideline for the development of a smart IoT-based biomedical heart rate oximeter for car-driving safety. The device is designed to monitor the heart rate and oxygen saturation levels of drivers in real-time and transmit the data wirelessly to the cloud for analysis. The device is also designed to integrate with the IoT technology to provide real-time alerts to drivers, passengers, and emergency services in case of any abnormalities in vital signs. The device is developed with a focus on accuracy, reliability, durability, ease of use, and regulatory compliance. The guideline outlines the research, design, prototyping, testing, and refining process for the device, with emphasis on IoT integration for car-driving safety. The development of this device has significant implications for improving car-driving safety, reducing accidents, and improving overall health outcomes for drivers.

Chung-Hsing Chao. Development of smart IoT based biomedical heart rate oximeter for driving safety. Academic Journal of Engineering and Technology Science (2023) Vol. 6, Issue 12: 1-6. https://doi.org/10.25236/AJETS.2023.061201.

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