<![CDATA[This systematic review evaluates the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in infectious disease monitoring. The review analyses the recent development, implementation, and effectiveness of AI-IoT systems in surveillance, early detection, and outbreak prediction. An analysis of peer-reviewed literature from 2021 to 2024 reveals key trends, challenges, and opportunities in the application of these technologies in public health. AI plays an important role in analysing big data to detect patterns and predict the spread of diseases, while IoT provides the infrastructure for real-time data collection through interconnected devices. The results of this review show that the combination of AI and IoT can speed up diagnosis, improve public health response, and facilitate remote patient monitoring, especially in hard-to-reach areas. However, there are some key challenges that need to be addressed, such as data privacy, cybersecurity, and interoperability between systems. In addition, the successful implementation of these technologies requires multidisciplinary collaboration between the fields of technology, health, and policy. The review also highlights the potential benefits of AI and IoT integration in addressing complex public health issues, especially in the context of mitigating and controlling future outbreaks. The development of safer and more integrated technologies is necessary to maximise their positive impact. AI and IoT synergies offer great opportunities to improve global health systems, but their sustainable implementation requires more attention to relevant technical, ethical, and policy aspects]]>
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