Compara mètodes

	Recollida de dades de sensors en línia	Recollida de dades de sensors mòbils
Camp	Metodologia d'enquestes	Metodologia d'enquestes
Família	Process / pipeline	Process / pipeline
Any d'origen	Late 1990s–early 2000s (Internet of Things paradigm formalized ~2000)	Mid-2000s (smartphone-era formalization ~2006–2010)
Autor original	Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000)	Andrew Campbell, Tanzeem Choudhury, and colleagues (early smartphone sensing research); broader field of ubiquitous computing
Tipus	Quantitative / mixed-mode data collection technique	Passive and active quantitative data collection technique
Font seminal	Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 38(4), 393–422.	Lane, N. D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. T. (2010). A survey of mobile phone sensing. IEEE Communications Magazine, 48(9), 140–150.
Àlies	networked sensor data collection, IoT data collection, remote sensor monitoring, wireless sensor data acquisition	mobile sensing, smartphone sensor data collection, wearable sensor data collection, passive mobile data collection
Relacionats	6	4
Resum	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 sensor data collection uses the built-in sensors of smartphones, tablets, or wearable devices to capture behavioral, physiological, and environmental data in real-world settings. Sensors such as accelerometers, GPS, heart rate monitors, ambient light detectors, and microphones record data passively or on demand, enabling researchers to study human behavior with high temporal resolution outside the laboratory.