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| Събиране на данни от дистанционни сензори× | Мобилно събиране на преживявания× | |
|---|---|---|
| Област | Методология на проучванията | Методология на проучванията |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1990s–2000s (proliferated with wireless and IoT technologies) | 1983 |
| Създател≠ | Multiple contributors; foundational wireless sensor network (WSN) survey by Akyildiz et al. | Mihaly Csikszentmihalyi & Reed Larson |
| Тип≠ | Automated quantitative data collection | Intensive longitudinal data collection technique |
| Основополагащ източник≠ | Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422. DOI ↗ | Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗ |
| Други названия | remote sensing data acquisition, wireless sensor data collection, distributed sensor data collection, telemetric data collection | ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA |
| Свързани≠ | 6 | 5 |
| Резюме≠ | Remote sensor data collection is the systematic acquisition of measurements from geographically distributed sensing devices without requiring direct human presence at each location. Sensors continuously or periodically record physical, chemical, or biological variables — temperature, pressure, motion, light, GPS coordinates — and transmit readings wirelessly or via network to a central repository for analysis. Widely used in environmental monitoring, precision agriculture, health informatics, and smart infrastructure. | Mobile Experience Sampling (ESM) is an intensive longitudinal data-collection technique in which participants respond to brief, repeated questionnaires delivered to their smartphones at random or scheduled intervals throughout the day. By capturing thoughts, feelings, behaviors, and context at or near the moment they occur, ESM minimises retrospective recall bias and provides a high-resolution picture of psychological and behavioral fluctuations in everyday life. |
| ScholarGateНабор от данни ↗ |
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