scholarly journals Computational Tools for Data Processing in Smart Cities

Author(s):  
Danilo Hernane Spatti ◽  
Luisa Helena Bartocci Liboni
2021 ◽  
Author(s):  
Yehia Kotb ◽  
Mouhammad Alakkoumi ◽  
Hassan Kanj

2021 ◽  
Author(s):  
Gabriele Leoni ◽  
Federica Ferrigno ◽  
Paolo Maria Guarino ◽  
Luca Guerrieri ◽  
Francesco Menniti ◽  
...  

<p>EO4GEO is an Erasmus+ Project aiming at defining a long-term and sustainable strategy to fill the gap between supply of and demand for space/geospatial education and training in the Copernicus domain. To test and validate the approach a series of training actions are ongoing for selected scenarios in three sub-sectors: 1) Integrated Applications, 2) Smart Cities, 3) Climate Change. ISPRA, which includes the Geological Survey of Italy, is contributing to the development of Integrated Applications, coordinating different scenarios fostering the uptake of EO data, services and standardized methodologies of analysis. Available EO data were tested to evaluate their effectiveness and efficiency in different fields (e.g. ground motion monitoring on Cultural Heritage, agro monitoring to support regional decision-making; land change detection, geohazard zoning, risk assessment, etc.). Here we present the preliminary results concerning the InSAR analysis and the development of different training actions on ground motion monitoring on potential slope instabilities affecting Cultural Heritage sites. The selected site is the Roman Thermae at Baia (Naples), being part of the “Parco Archeologico dei Campi Flegrei”, located close to active calderas. The area is characterized by a sequence (from the bottom to the top) of volcanic breccia, pyroclastic deposits and surge deposits; Phlegrean Fields represent an exceptional example of volcanic-related subsidence with unrest cycles characterized by intense ground uplift and lowering. The instability phenomena depend mainly on the acclivity of the top sector of the slope, with the activation of small collapse events, and on the lack of ordinary management and maintenance of the area (e.g. invasive vegetation, absence of drainage system). A preliminary InSAR analysis was performed exploiting ERS datasets (1993–2003), showing regional ground lowering, with deformation rates (5-10 mm/yr) that are consistent with the general down lift cycle affecting the whole area in that that period. Ongoing InSAR data processing are focused on SENTINEL-1 data (April 2016 - August 2020) allowing us to explore most recent evolution of instability phenomena. Data processing has been performed using the SeNtinel’s Application Platform (SNAP-ESA) and the Stanford Method of Persistent Scatterers (StaMPS). The dataset is composed by 79 descending and 81 ascending scenes, and the single master stack contains 76 interferograms from the descending and 80 from the ascending geometry. Additionally, SRTM DEM was used in the interferometric processing. Obtained results clearly show a ground uplifting in the investigated period, with displacement rates ranging between 5 and 10 mm/yr (5.2 mm/yr average value of the study area). Any differential displacement has been observed on the exposed elements of the site. A training module focused on this use case is under development, thus contributing to fill the gap between supply and demand in the Copernicus domain, main goal of the EO4GEO project. The definition of step-by-step methodology from EO data to final processing will be defined and connected to learning outcomes, sectorial and transversal skills contributing to finalize the main goal of the EO4GEO project.</p>


2017 ◽  
Vol 52 ◽  
pp. 335-342 ◽  
Author(s):  
Cristian Chilipirea ◽  
Andreea-Cristina Petre ◽  
Loredana-Marsilia Groza ◽  
Ciprian Dobre ◽  
Florin Pop

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2994 ◽  
Author(s):  
Bhagya Silva ◽  
Murad Khan ◽  
Changsu Jung ◽  
Jihun Seo ◽  
Diyan Muhammad ◽  
...  

The Internet of Things (IoT), inspired by the tremendous growth of connected heterogeneous devices, has pioneered the notion of smart city. Various components, i.e., smart transportation, smart community, smart healthcare, smart grid, etc. which are integrated within smart city architecture aims to enrich the quality of life (QoL) of urban citizens. However, real-time processing requirements and exponential data growth withhold smart city realization. Therefore, herein we propose a Big Data analytics (BDA)-embedded experimental architecture for smart cities. Two major aspects are served by the BDA-embedded smart city. Firstly, it facilitates exploitation of urban Big Data (UBD) in planning, designing, and maintaining smart cities. Secondly, it occupies BDA to manage and process voluminous UBD to enhance the quality of urban services. Three tiers of the proposed architecture are liable for data aggregation, real-time data management, and service provisioning. Moreover, offline and online data processing tasks are further expedited by integrating data normalizing and data filtering techniques to the proposed work. By analyzing authenticated datasets, we obtained the threshold values required for urban planning and city operation management. Performance metrics in terms of online and offline data processing for the proposed dual-node Hadoop cluster is obtained using aforementioned authentic datasets. Throughput and processing time analysis performed with regard to existing works guarantee the performance superiority of the proposed work. Hence, we can claim the applicability and reliability of implementing proposed BDA-embedded smart city architecture in the real world.


Author(s):  
Xihuang Sun ◽  
Peng Liu ◽  
Yan Ma ◽  
Dingsheng Liu ◽  
Yechao Sun

The explosion of data and the increase in processing complexity, together with the increasing needs of real-time processing and concurrent data access, make remote sensing data streaming processing a wide research area to study. This paper introduces current situation of remote sensing data processing and how timely remote sensing data processing can help build future smart cities. Current research on remote sensing data streaming is also introduced where the three typical and open-source stream processing frameworks are introduced. This paper also discusses some design concerns for remote sensing data streaming processing systems, such as data model and transmission, system model, programming interfaces, storage management, availability, etc. Finally, this research specifically addresses some of the challenges of remote sensing data streaming processing, such as scalability, fault tolerance, consistency, load balancing and throughput.


Author(s):  
Mohamed El Beqqal ◽  
Mostafa Aziz

The Internet of things(IoT) is now considered among  the most emerging technologies aiming to interconnect  heterogeneous smart  devices in several areas without human interaction . From sensing  and identification to data processing and storing. The Building and the monitoring of smart systems like smart homes, smart campus and smart cities pass through several stages on which different tools and platforms coexist to answer this need. In this paper, we present a survey on recent works using IoT tools to build their systems. Particularly, we classify and compare them according  to layers and characteristics that we have defined such as data acquisition, data processing , software used, conformity to standards.  Hence , our study aims to provide a clear vision on available functionalities during the process of building IoT systems based on most used IoT tools and to help users to choose the most adapted tool depending on their needs.


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