Federated AI for Privacy-Preserving Analysis of Wearable Nanobiosensor Data

Federated AI for Privacy-Preserving Analysis of Wearable Nanobiosensor Data

Authors- Shruthi

Abstract--The emergence of wearable nanobiosensors has opened new frontiers in real-time, continuous health monitoring by enabling detection of physiological and biochemical changes at the molecular level. These sensors generate highly personalized data streams that are crucial for early diagnosis, chronic disease management, and adaptive therapeutic interventions. However, the sensitive nature of such data introduces substantial privacy risks, especially in centralized data processing systems. Federated artificial intelligence (AI) has recently gained traction as a solution for decentralized machine learning that protects user data. This article investigates the integration of federated AI with wearable nanobiosensor networks, emphasizing its ability to facilitate large-scale, privacy-respecting biomedical analytics without compromising the utility or integrity of health data.

DOI: /10.61463/ijset.vol.13.issue2.428