Key result
Proposed smart device system uses machine learning and IoT to automate cardiovascular emergency notifications.
Why the study?
Cardiovascular diseases cause over 18 million deaths globally, and there is a need for a mechanism providing immediate emergency notifications to hospital management to enable timely medical assistance.
Proposes an automated IoT and ML-based system to monitor resting heart rate and notify hospital management during emergencies to prevent cardiovascular deaths.
Over 18 million people die due to Cardio-Vascular Diseases (CVDs), making it the disease that causes more deaths in a human being than other conditions, as stated by a report given by the World Health Organization. However, it is also observed that immediate assistance from a doctor can prevent a curious portion of these deaths by reacting quickly and taking immediate help from a doctor. So, there is a need for a proper mechanism to provide immediate emergency notifications to the hospital management. A new phase of technology has been significantly increasing in recent years, known as Smart Technology, comprising various hardware equipment like sensors, cameras, and modern technologies like AI, ML, IoT, etc. This paper provides an automated, effective solution to notify the hospital management in case of an untimely emergency caused by rapid changes in the individual’s resting heart rate using a smart device that works on IoT, ML, and heartbeat sensors.
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Rao et al. (2021) studied Cardio-Vascular Diseases (CVDs). Smart HeartRate Analysis and Notification System for Emergencies (SHANE) was evaluated. An automated smart device system utilizing IoT, machine learning, and heartbeat sensors was proposed to provide immediate emergency notifications to hospital management for cardiovascular emergencies.
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