GEOSPATIAL BIG DATA ANALYTICS FOR SUSTAINABLE SMART CITIES

M. O. Mete*

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Konferans makalesibilirkişi

1 Atıf (Scopus)

Özet

Growing urbanization cause environmental problems such as vast amount of carbon emissions and pollution all over the world. Smart Infrastructure and Smart Environment are two significant components of the smart city paradigm that can create opportunities for ensuring energy conservation, preventing ecological degradation, and using renewable energy sources. Since a great portion of the data contains location information, geospatial intelligence is a key technology for sustainable smart cities. We need a holistic framework for the smart governance of cities by utilizing key technological drivers such as big data, Geographic Information Systems (GIS), cloud computing, Internet of Things (IoT). Geospatial Big Data applications offer predictive data science tools such as grid computing and parallel computing for efficient and fast processing to build a sustainable smart city ecosystem. Effective management of big data in storage, visualization, analytics, and analysis stages can foster green building, green energy, and net zero targets of countries. Parallel computing systems have the ability to scale up analysis on geospatial big data platforms which is key for ocean, atmosphere, land, and climate applications. In this study, it is aimed to create the necessary technical infrastructure for smart city applications with a holistic big data management approach. Thus, a smart city model framework is developed for Smart Environment and Smart Governance components and performance comparison of Dask-GeoPandas and Apache Sedona parallel processing systems are carried out. Apache Sedona performed better on the performance test during read, write, join and clustering operations.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)141-146
Sayfa sayısı6
DergiInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Hacim48
Basın numarası4/W7-2023
DOI'lar
Yayın durumuYayınlandı - 22 Haz 2023
Etkinlik2023 Free and Open Source Software for Geospatial, FOSS4G 2023 - Prizren, Serbia
Süre: 26 Haz 20232 Tem 2023

Bibliyografik not

Publisher Copyright:
© 2023 International Society for Photogrammetry and Remote Sensing. All rights reserved.

Finansman

This work was supported by the Scientific Research Projects Coordination Unit of Istanbul Technical University [Grant No. MAB-2023-44579].

FinansörlerFinansör numarası
Istanbul Teknik ÜniversitesiMAB-2023-44579

    Parmak izi

    GEOSPATIAL BIG DATA ANALYTICS FOR SUSTAINABLE SMART CITIES' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

    Alıntı Yap