A Smart Monitoring System For Improved Efficiency And Hospital Safety
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Abstract
A hospital is an environment where people receive medical treatment. Overcrowding in the hospital environment may cause the spread of infectious diseases. In order to address this issue, crowd management is necessary in a hospital. Conventional crowd management has completely relied on manual methods, such as paper-based approaches and visual estimations of crowd density. These traditional methods lack real-time insights and are prone to human errors. In response, this paper introduces an innovative solution by integrating sensor fusion techniques and artificial intelligence-driven algorithms for precise crowd estimation and staff attendance verification in real-time in a hospital environment. This transition from traditional to our advanced solution ensures scalability, adaptability, improved data privacy, and cost efficiency. Our system promises dynamic decision-making based on the estimation of people in a specific region. The purpose of this project is to provide a cost-efficient solution that enhances hospital management practices by optimizing resource allocation and security measures to improve patient care and safety.
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