方法对比

	在线传感器数据收集	Web Scraping
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)	Late 1990s–2000s
提出者	Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000)	Early internet practitioners; systematised in research contexts from the late 1990s onward
类型	Quantitative / mixed-mode data collection technique	Automated digital 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.	Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571
别名	networked sensor data collection, IoT data collection, remote sensor monitoring, wireless sensor data acquisition	web harvesting, screen scraping, web crawling, automated data extraction
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.	Web scraping is a computational data collection technique in which software automatically retrieves and extracts structured or semi-structured content from websites. Widely used in social science, computational linguistics, economics, and information science, it enables researchers to assemble large datasets from publicly accessible web sources — such as news archives, social media platforms, government portals, and online marketplaces — that would be impractical to collect manually.