方法对比

	在线传感器数据收集	Mobile Experience Sampling
领域	调查方法论	调查方法论
方法族	Process / pipeline	Process / pipeline
起源年份	Late 1990s–early 2000s (Internet of Things paradigm formalized ~2000)	1983
提出者	Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000)	Mihaly Csikszentmihalyi & Reed Larson
类型	Quantitative / mixed-mode data collection technique	Intensive longitudinal data collection technique
开创性文献	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.
别名	networked sensor data collection, IoT data collection, remote sensor monitoring, wireless sensor data acquisition	ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA
相关	6	5
摘要	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.