SENSORLARDA MA’LUMOTLARNI YIG‘ISH VA UZATISH

Main Article Content

Аннотация:

Narsalar Interneti(IoT)ning so‘nggi davrida sensorlar va internet turli xil hayotiy muammolarni hal qiladi. Bunday ilovalarga aqlli shahar, aqlli sog‘liqni saqlash tizimlari, aqlli bino, aqlli transport va aqlli muhit kiradi. Biroq, real vaqtda IoT sensori ma’lumotlari nopok sensor ma’lumotlarining to‘lqini va resurslarni yuqori iste’mol qilish xarajatlari kabi bir nechta qiyinchiliklarni o ‘z ichiga oladi. Shunday qilib, ushbu maqola IoT sensori ma’lumotlarini qanday qayta ishlash, boshqa ma’lumotlar manbalari bilan birlashtirish va tezkor qarorlar qabul qilish uchun yashirin ma’lumotlar modellari to‘g‘risida bilimli tushuncha olish uchun tahlillarni ko‘rib chiqadi. Ushbu maqola ma’lumotlarni zararsizlantirish, ma’lumotlarni aniqlash, etishmayotgan ma’lumotlarni hisoblash va ma’lumotlarni yig’ish kabi ma’lumotlarni qayta ishlash usullarini korib chiqadi.

Article Details

Как цитировать:

Umarov, B. ., & Raxmatullayeva, M. (2024). SENSORLARDA MA’LUMOTLARNI YIG‘ISH VA UZATISH. Центральноазиатский журнал академических исследований, 2(11 Part 2), 96–100. извлечено от https://in-academy.uz/index.php/cajar/article/view/40589

Библиографические ссылки:

An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques by Rajalakshmi Krishnamurth, Adarsh Kumar, Dhanalekshmi Gopinathan, Anand Nayyar* and Basit Qureshi

Liu, Y.; Dillon, T.; Yu, W.; Rahayu, W.; Mostafa, F. Missing value imputation for Industrial IoT sensor data with large gaps. IEEE Internet Things J. 2020, 7, 6855–6867. [Google Scholar] [CrossRef]

Chernick, M.R. Wavelet Methods for Time Series Analysis. Technometrics 2001, 43, 491. [Google Scholar] [CrossRef]

Gartner Inc. Available online: https://www.gartner.com/en/newsroom/press-releases/2019-08-29-gartner-says-5-8-billion-enterprise-and-automotive-io (accessed on 10 April 2020).

Deng, X.; Jiang, P.; Peng, X.; Mi, C. An intelligent outlier detection method with one class support tucker machine and genetic algorithm toward big sensor data in internet of things. IEEE Trans. Ind. Electron. 2019, 66, 4672–4683. [Google Scholar] [CrossRef]

Sanyal, S.; Zhang, P. Improving quality of data: IoT data aggregation using device to device communications. IEEE Access 2018, 6, 67830–87840. [Google Scholar] [CrossRef]

Yang, C.; Puthal, D.; Mohanty, S.P.; Kougianos, E. Big-Sensing-Data Curation for the Cloud is Coming: A Promise of Scalable Cloud-Data-Center Mitigation for Next-Generation IoT and Wireless Sensor Networks. IEEE Consum. Electron. Mag. 2017, 6, 48–56. [Google Scholar] [CrossRef]

Cao, N.; Nasir, B.S.; Sen, S.; Raychowdhury, A. Self-Optimizing IoT Wireless Video Sensor Node with In-Situ Data Analytics and Context-Driven Energy-Aware Real-Time Adaptation. IEEE Trans. Circuits Syst. I Regul. Pap. 2017, 64, 2470–2480. [Google Scholar] [CrossRef]