Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Ukusanyaji wa Data kwa Kutumia Vihisi vya Mbali× | Uchimbaji wa Wavuti× | |
|---|---|---|
| Nyanja | Metodolojia ya Dodoso | Metodolojia ya Dodoso |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1990s–2000s (proliferated with wireless and IoT technologies) | Late 1990s–2000s |
| Mwanzilishi≠ | Multiple contributors; foundational wireless sensor network (WSN) survey by Akyildiz et al. | Early internet practitioners; systematised in research contexts from the late 1990s onward |
| Aina≠ | Automated quantitative data collection | Automated digital 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. DOI ↗ | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 |
| Majina mbadala | remote sensing data acquisition, wireless sensor data collection, distributed sensor data collection, telemetric data collection | web harvesting, screen scraping, web crawling, automated data extraction |
| Zinazohusiana≠ | 6 | 5 |
| Muhtasari≠ | Remote sensor data collection is the systematic acquisition of measurements from geographically distributed sensing devices without requiring direct human presence at each location. Sensors continuously or periodically record physical, chemical, or biological variables — temperature, pressure, motion, light, GPS coordinates — and transmit readings wirelessly or via network to a central repository for analysis. Widely used in environmental monitoring, precision agriculture, health informatics, and smart infrastructure. | 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. |
| ScholarGateSeti ya data ↗ |
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