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Пилотное тестирование сбора данных с датчиков×Сбор продольных сенсорных данных×
ОбластьМетодология опросовМетодология опросов
СемействоProcess / pipelineProcess / pipeline
Год появления1990s–2000s (formalized with proliferation of digital sensing technologies)1990s–2000s (accelerated with IoT and wearable devices from ~2010)
Автор методаGeneral research methods practice; sensor pilot testing codified through IoT and environmental monitoring literatureEmerging from ambulatory assessment and wearable technology research communities
ТипData collection procedure with pre-deployment validation phaseLongitudinal quantitative/mixed data collection technique
Основополагающий источникCreswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). Sage Publications. ISBN: 978-1506386706Lanza, S. T., Collins, L. M., Lemmon, D. R., & Schafer, J. L. (2005). PROC LCA: A SAS procedure for latent class analysis. Structural Equation Modeling, 14(4), 671–694. [For longitudinal intensive repeated-measures designs context, see also: Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1–32.] link ↗
Другие названияsensor pilot study, sensor pre-deployment testing, instrument validation with sensors, sensor calibration pilotlong-term sensor monitoring, longitudinal sensing, continuous sensor logging, repeated-measures sensor collection
Связанные63
СводкаPilot-tested sensor data collection is a structured data gathering approach in which sensor instruments — hardware or software-based devices that measure physical, environmental, physiological, or behavioral signals — are deployed in a small-scale trial before the main study. The pilot phase verifies sensor accuracy, communication reliability, data format consistency, and placement adequacy, allowing researchers to identify and correct technical problems before full-scale data collection begins.Longitudinal sensor data collection deploys physical or digital sensors to record phenomena continuously or at regular intervals across an extended study period — days, months, or years. Unlike one-shot measurement, the repeated temporal structure captures change, trajectory, and variability in outcomes such as physical activity, environmental exposure, sleep, or physiological state. The approach combines the ecological validity of real-world sensing with the analytical power of longitudinal design.
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Pilot-tested Sensor Data Collection · Longitudinal Sensor Data Collection. Получено 2026-06-17 из https://scholargate.app/ru/compare