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Emphasizing privacy and security of edge intelligence with machine learning for healthcare

International Journal of Intelligent Computing and Cybernetics 2022年第1期15卷 92-109页

作者： Sukumar Rajendran Sandeep Kumar Mathivanan Prabhu Jayagopal Kumar Purushothaman Janaki Benjula Anbu Malar Manickam Bernard Suganya Pandy Manivannan Sorakaya Somanathan Vellore Institute of Technology VelloreIndia

Purpose-Artificial Intelligence(AI)has surpassed expectations in opening up different possibilities for machines from different walks of *** service providers are *** computing reduces latency,improving availability and saving ***/methodology/approach-The exponential growth in tensor processing unit(TPU)and graphics processing unit(GPU)combined with different types of sensors has enabled the pairing of medical technology with deep learning in providing the best patient care.A significant role of pushing and pulling data from the cloud,big data comes into play as velocity,veracity and volume of data with IoT assisting doctors in predicting the abnormalities and providing customized treatment based on the patient electronic health record(EHR).Findings-The primary focus of edge computing is decentralizing and bringing intelligent IoT devices to provide real-time computing at the point of presence(PoP).The impact of the PoP in healthcare gains importance as wearable devices and mobile apps are entrusted with real-time monitoring and diagnosis of *** impact edge computing of the PoP in healthcare gains significance as wearable devices and mobile apps are entrusted with real-time monitoring and diagnosis of ***/value-The utility value of sensors data improves through the Laplacian mechanism of preserved PII response to each query from the *** scalability is at 50%with respect to the sensitivity and preservation of the PII values in the local ODL.

关键词： Edge computing Deep learning Cloud computing Fog computing Electronic health record tensor processing unit Graphics processing unit Point of presence

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