• Nitesh S
• Anudeep Gowda K M
• Devaraj V
• Srujan K
• Padmavati S

The health industry is redefining the healthcare sector with the intersection of cloud-based security and artificial intelligence (AI).This integration is driving patient care towards a responsive. This system proposed towards a proactive, everobserved paradigm. This pol provides a methodical examination of the technologies and techniques behind smart healthcare systems that utilize the temporal aberration identification towards improved safety and foresight active performance. We schematize the research terrain, pointing out the dominant technological innovations and the dominant application challenges and research opportunities. Our synthesis shows that the temporal anomaly detectors which is (AI-based ones, especially LSTM) effectively solves the problem. Autoencoders have an impressive level of accuracy of as high as 98 percent on benchmarks of abnormalities in ECG detection under controlled conditions. However, the transfer of those gains to the real-life is not so smooth for deployment process, in which the latest methods are used, like federated learning remain partially adopted. By means of arranging existing work into a logical taxonomy, determining the level of technology preparedness and describing the roadmap to the development process, this survey highlights the need to make the transition between high performance academic models and their are secure and scalable to implementation in the clinical practice.

Healthcare IOT systems, Temporal Anomaly Detection models,Cloud computing Artificial Intelligence and Machine Learning

"Intelligent Healthcare with Cloud-Based Security Systems Using Temporal Anomaly Models", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.e522-e527, November-2025, Available :http://www.jetir.org/papers/JETIR2511465.pdf

"Intelligent Healthcare with Cloud-Based Security Systems Using Temporal Anomaly Models", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppe522-e527, November-2025, Available at : http://www.jetir.org/papers/JETIR2511465.pdf