Keyword: Smart surveillance

ABSTRACT: Hospital-acquired infections (HAIs) continue to be one of the biggest problems for modern healthcare systems, and the problem is getting worse because antimicrobial resistance (AMR) is on the rise. Antibiotics that used to work are quickly losing their effectiveness, which is giving rise to highly adaptable bacteria in clinical settings and turning routine procedures into high-risk situations. This publication examines the intersection of healthcare-associated infections (HAIs) and antimicrobial resistance (AMR) within the framework of smart surveillance—digital, data-driven systems engineered to identify, predict, and disrupt the spread of infections in real time. We examine the historical development of infection surveillance, analyze the epidemiological burden and resistance mechanisms contributing to a covert pandemic, and assess emerging technologies such as electronic health record integration, machine-learning analytics, genomic sequencing, and Internet of Things (IoT) sensor networks. These new ideas give us new ways to prevent infections before they happen, but they also bring up difficult moral, legal, and social problems about privacy, fairness, and governance. We contend that intelligent surveillance should be integrated into comprehensive infection prevention frameworks and antimicrobial stewardship initiatives to establish resilient hospitals. By combining predictive analytics with basic IPC procedures, ethical monitoring, and giving workers more autonomy, healthcare organizations may turn passive surveillance into active defense. In the end, winning the war against HAIs will depend not just on cutting-edge technology, but also on how it is used with care, honesty, and openness.