Please use this identifier to cite or link to this item: https://repository.hneu.edu.ua/handle/123456789/38549
Title: Integrated differential privacy learning system for edge computing in iot networks
Authors: Zhu Yinqiang
Keywords: analys
developed
software
method
modeling
system
Issue Date: 2025
Citation: Zhu Yinqiang Integrated differential privacy learning system for edge computing in iot networks / Yinqiang Zhu, Yuriy Skorin (Scientific Supervisor) // Матеріали ІІ Міжнародної науково-практичної конференції, присвяченої 30-річчю кафедри маркетингу, управління репутацією та клієнтським досвідом ДБТУ, 23 жовтня 2025 р. / Держ. біотехнологічний універси-тет. – Харків, 2025. – С. 157–158.
Abstract: As a result of the significant growth of the Internet of Things (IoT), a large nmnber of smart devices are being deployed around the world in various industries, from smart homes and smart cities to industrial automation and connected healthcare. These devices, such as portable health monitors, smart vehicles, and industrial sensors, form a vast network, generating a continuous and massive stream of data. This data provides an unprecedented opportunity to use machine learning to create intelligent applications that can provide accurate predictions and highly personalized services.
URI: https://repository.hneu.edu.ua/handle/123456789/38549
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