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Related Concept Videos

Data Collection I01:30

Data Collection I

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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Data Collection III01:05

Data Collection III

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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the...
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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Data Collection II01:29

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The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
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Data Collection by Observations01:08

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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Ethical Standards I01:25

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The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
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Decentralized identifiers based IoT data trusted collection.

Baitao Zhang1, Rui Shi2, Xiaolin Li3

  • 1School of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.

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|February 8, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces TrID, a novel IoT data security scheme using Decentralized Identifiers (DIDs) to enhance data collection. TrID offers a distributed, efficient, and secure solution for Internet of Things (IoT) data, overcoming limitations of centralized and blockchain models.

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Internet of Things (IoT)

Background:

  • IoT data collection faces critical security challenges in access, transmission, and storage.
  • Existing solutions like Certificate Authorities (CAs) are centralized, and blockchain methods lack efficiency.
  • Sectors like smart healthcare, homes, and cities are particularly vulnerable due to limited user control over IoT devices.

Purpose of the Study:

  • To propose a novel trust model for IoT data collection utilizing Decentralized Identifiers (DIDs).
  • To introduce TrID, an IoT data security collection scheme designed for enhanced security and efficiency.
  • To address the limitations of centralized and blockchain-based security solutions in IoT environments.

Main Methods:

  • Developed a trust model based on Decentralized Identifiers (DIDs).
  • Proposed the TrID (Trustworthy and Integrated Data) scheme with a distributed architecture.
  • Implemented and evaluated TrID's performance in a mutual authentication protocol and data decryption.

Main Results:

  • TrID resolves the centralization issue inherent in traditional IoT security models.
  • The authentication time cost of TrID is approximately 10% of on-chain solutions.
  • Decryption of 10 MB of data with a 1000 KB block size takes less than 100 ms, demonstrating high efficiency.

Conclusions:

  • TrID offers a significantly more secure and efficient approach to IoT data collection compared to existing methods.
  • The distributed nature and independence from blockchain enhance both security and performance.
  • TrID provides a viable solution for securing data in sensitive IoT applications like smart healthcare and cities.