Confronta i metodi

	Raccolta di Dati da Sensori Online	Raccolta dati tramite sensori mobili
Campo	Metodologia delle indagini	Metodologia delle indagini
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	Late 1990s–early 2000s (Internet of Things paradigm formalized ~2000)	Mid-2000s (smartphone-era formalization ~2006–2010)
Ideatore	Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000)	Andrew Campbell, Tanzeem Choudhury, and colleagues (early smartphone sensing research); broader field of ubiquitous computing
Tipo	Quantitative / mixed-mode data collection technique	Passive and active quantitative data collection technique
Fonte seminale	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.
Alias	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
Correlati	6	4
Sintesi	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.