Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Онлайн събиране на сензорни данни× | Събиране на данни чрез мобилни сензори× | |
|---|---|---|
| Област | Методология на проучванията | Методология на проучванията |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | Late 1990s–early 2000s (Internet of Things paradigm formalized ~2000) | Mid-2000s (smartphone-era formalization ~2006–2010) |
| Създател≠ | Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000) | Andrew Campbell, Tanzeem Choudhury, and colleagues (early smartphone sensing research); broader field of ubiquitous computing |
| Тип≠ | Quantitative / mixed-mode data collection technique | Passive and active quantitative data collection technique |
| Основополагащ източник≠ | Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 38(4), 393–422. DOI ↗ | 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. DOI ↗ |
| Други названия | 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 |
| Свързани≠ | 6 | 4 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
|
|