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Electronic healthcare systems are the most emerging field of today’s digital world which are used for remote health monitoring, evidence-based treatment, disease prediction, modeling, etc. In this method, patient data is kept on a health cloud, where doctors have 24/7 access to it. Thus, safe data transfer is necessary for monitoring or treating patients. Every time, a cloud-based solution is adopted for the collection and preservation of collected personal health information. Nowadays, IoT plays a very important role in real-time. IoT had used in smart healthcare, smart vehicle, smart home, smart city, and smart care. IoT-based e-healthcare framework collects healthcare data, and this health data is stored in a cloud server or hard disk. Health data is required for classification and regression using machine learning techniques. This paper’s main objective is to improve patient monitoring and care by putting IoT-based electronic healthcare systems into place. We hope to address contemporary issues in healthcare, including remote monitoring, real-time patient data collecting, and effective patient-provider communication, by utilizing IoT technologies. The focus of this effort is on using creative IoT solutions to improve healthcare outcomes and delivery.

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Cyber Attack on IoT-Based Smart Healthcare System Using Machine Learning Techniques

  • 会议论文

  • 发表日期：

    2025年

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  • Ravi Raushan Kumar Chaudhary,
  • Sarvendra Kumar Pankaj,
  • Sonika Thapak,
  • Surbhi Kushwah

摘要

Electronic healthcare systems are the most emerging field of today’s digital world which are used for remote health monitoring, evidence-based treatment, disease prediction, modeling, etc. In this method, patient data is kept on a health cloud, where doctors have 24/7 access to it. Thus, safe data transfer is necessary for monitoring or treating patients. Every time, a cloud-based solution is adopted for the collection and preservation of collected personal health information. Nowadays, IoT plays a very important role in real-time. IoT had used in smart healthcare, smart vehicle, smart home, smart city, and smart care. IoT-based e-healthcare framework collects healthcare data, and this health data is stored in a cloud server or hard disk. Health data is required for classification and regression using machine learning techniques. This paper’s main objective is to improve patient monitoring and care by putting IoT-based electronic healthcare systems into place. We hope to address contemporary issues in healthcare, including remote monitoring, real-time patient data collecting, and effective patient-provider communication, by utilizing IoT technologies. The focus of this effort is on using creative IoT solutions to improve healthcare outcomes and delivery.