Edge Analytics

Nanosensors are redefining telehealth by combining advanced nanotechnology with computational intelligence to enable real-time monitoring, precise diagnosis and automated treatment support. Their integration with Internet of Medical Things (IoMT) architecture allow seamless collection, transmission and analysis of physiological data through cloud platform and edge computing system. These networks helps continuous remote patient monitoring, early anomaly detection using AI-driven analysis and reduced dependence on hospital-centric care model. The implementation of nanosensors in teleICU and hospital- at-home frameworks also addresses scalability and resource optimization in healthcare systems. However, challenges such as secure data transmission, interoperability between heterogeneous devices, fault tolerance and privacy protection must be resolved to ensure reliable deployment. This paper presents a comprehensive review of nanosensor technologies from computational perspective, detailing their communication protocols, data processing pipelines and cybersecurity requirement. Future research direction emphasize energy-efficient sensor design, federated learning for distributed analytics and blockchain-enabled security model for trustworthy remote healthcare ecosystems.