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Related Concept Videos

Data Collection by Survey01:07

Data Collection by Survey

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The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
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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 I01:30

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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 by Observations01:08

Data Collection by Observations

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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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Data Collection III01:05

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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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Data Collection by Experiments01:13

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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
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Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events.

Luca Foschini1, Giuseppe Martuscelli1, Rebecca Montanari1

  • 1Department of Computer Science and Engineering (DISI), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy.

Journal of Grid Computing
|July 13, 2021
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Summary
This summary is machine-generated.

This study introduces ParticipAct, an edge-enabled mobile crowdsensing platform. It uses edge nodes and federated blockchain to detect dangerous crowd situations and provide timely safety notifications for smart cities.

Keywords:
BlockchainEdge computingMobile crowd sensingPandemic preventionSmart city

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Area of Science:

  • Computer Science
  • Urban Informatics
  • Mobile Computing

Background:

  • Smart cities leverage Information and Communication Technologies (ICT) to enhance public services and quality of life.
  • Mobile CrowdSensing (MCS) is a key paradigm for urban sensing, utilizing individuals' smart devices to gather city-wide data.
  • Tracking population movement is crucial during emergencies like pandemics to prevent overcrowding.

Purpose of the Study:

  • To propose an edge-enabled mobile crowdsensing platform, ParticipAct, for real-time crowd monitoring and risk mitigation in smart cities.
  • To utilize edge computing for detecting hazardous crowd formations and a federated blockchain for managing user rewards.
  • To enhance citizen safety by providing adaptive, context-aware crowd warnings.

Main Methods:

  • Development of the ParticipAct platform integrating edge nodes and a federated blockchain network.
  • Deployment of edge nodes for localized computation of crowd density and risk assessment.
  • Implementation of a smart push notification service with adaptive warning frequency based on user location and transport context.

Main Results:

  • Edge nodes effectively compute dangerous crowd situations within their operational range.
  • The federated blockchain securely stores and manages user reward states.
  • The adaptive push notification system successfully reduces alert fatigue by tailoring warnings to user context.

Conclusions:

  • ParticipAct offers a novel approach to managing urban crowdsensing data for enhanced public safety.
  • Edge computing and federated blockchain integration provide a scalable and efficient solution for smart city applications.
  • The platform demonstrates the potential of MCS in mitigating risks associated with population density during critical events.