Linganisha mbinu

	Ukusanyaji wa Data wa Kihisi mtandaoni	Uzoefu wa Simu ya Mkononi
Nyanja	Metodolojia ya Dodoso	Metodolojia ya Dodoso
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	Late 1990s–early 2000s (Internet of Things paradigm formalized ~2000)	1983
Mwanzilishi	Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000)	Mihaly Csikszentmihalyi & Reed Larson
Aina	Quantitative / mixed-mode data collection technique	Intensive longitudinal data collection technique
Chanzo asilia	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.
Majina mbadala	networked sensor data collection, IoT data collection, remote sensor monitoring, wireless sensor data acquisition	ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA
Zinazohusiana	6	5
Muhtasari	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.