Realizing future intelligent networks via spatial and multi-temporal data acquisition in disdrometer networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

- Datil acqulsitten and qualihltive precipitation estimation (QPE),'ia dlsdrnmeters pla y an important role in ntimaring rain-induced att enuation In wtretess networks. However, existing disdromcter observations do Dot provide sufficient information for mod elling intelligent wireless networks. Tbe design of intelligent wireless networks require s that QPE parameters for a location be known at different epochs. This requires that disdrometen with spatial variability should be capable of multi-temporal QPE observations. A disdrometer architecture that addresses this challenge is presented in this paper. The proposed multi-temporal disdrometer incorporates a computing payload for storing QPE related data at multiple epochs, Performance evaluation shows that the use of the proposed multi-temporal disdrometer in QPE related data acquisition increases data suitable for QPE related modelling by up to 52.l OY. and 49.4% in the short term and long term respectively.

Original languageEnglish
Title of host publication2020 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2020 - Proceedings
EditorsSameerchand Pudaruth, Upasana Singh
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728167701
DOIs
Publication statusPublished - Aug 2020
Event2020 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2020 - Durban, KwaZulu Natal, South Africa
Duration: 6 Aug 20207 Aug 2020

Publication series

Name2020 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2020 - Proceedings

Conference

Conference2020 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2020
Country/TerritorySouth Africa
CityDurban, KwaZulu Natal
Period6/08/207/08/20

Keywords

  • Disdrometefs
  • Disdrometer Networb, Siu o/modelling data
  • Quantitative Precipitation Estimatil"'
  • RemotOlSen.l"ing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Information Systems and Management

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