Salīdzināt metodes

	Tiešsaistes sensoru datu vākšana	Mobilā pieredzes izlase
Nozare	Aptauju metodoloģija	Aptauju metodoloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	Late 1990s–early 2000s (Internet of Things paradigm formalized ~2000)	1983
Autors	Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000)	Mihaly Csikszentmihalyi & Reed Larson
Tips	Quantitative / mixed-mode data collection technique	Intensive longitudinal data collection technique
Pirmavots	Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 38(4), 393–422.	Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536.
Citi nosaukumi	networked sensor data collection, IoT data collection, remote sensor monitoring, wireless sensor data acquisition	ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA
Saistītās	6	5
Kopsavilkums	Online sensor data collection is a systematic technique for gathering continuous or event-triggered measurements from physical sensors that transmit readings in real time over a network — the internet, a local wireless network, or a dedicated IoT protocol. It is used widely in environmental monitoring, health informatics, smart-city research, industrial systems, and behavioral science to capture objective, high-frequency data without requiring manual recording by participants or observers.	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.