scholarly journals A Survey on Big Multimedia Data Processing and Management in Smart Cities

2019 ◽  
Vol 52 (3) ◽  
pp. 1-29 ◽  
Author(s):  
Muhammad Usman ◽  
Mian Ahmad Jan ◽  
Xiangjian He ◽  
Jinjun Chen
Keyword(s):  
Data Processing ◽  
Smart Cities ◽  
Multimedia Data ◽  
Big Multimedia Data

scholarly journals An IoE and Big Multimedia Data Approach for Urban Transport System Resilience Management in Smart Cities

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 435
Author(s):  
Emanuele Bellini ◽  
Pierfrancesco Bellini ◽  
Daniele Cenni ◽  
Paolo Nesi ◽  
Gianni Pantaleo ◽  
...  
Keyword(s):  
Communication Networks ◽  
Smart City ◽  
Structural Information ◽  
Smart Cities ◽  
Urban Transport ◽  
Multimedia Data ◽  
Urban Systems ◽  
Transport Systems ◽  
Big Multimedia Data ◽  
The City

Today, the complexity of urban systems combined with existing and emerging threats constrains administrations to consider smart technologies and related huge amounts of data generated as a means to take timely and informed decisions. The smart city needs to be prepared for both expected and unexpected situations, and the possibility to mitigate the effect of the uncertainty behind the causes of disruptions through the analysis of all the possible data generated by the city open new possibility for resilience operationalization. This article aims at introducing a new conceptualization for resilience and presenting an innovative full stack solution to exploit Internet of Everything (IoE) and big multimedia data in smart cities to manage resilience of urban transport systems (UTS), which is one of the most critical infrastructures of the city. The approach is based on a novel data driven approach to resilience engineering and functional resonance analysis method (FRAM), to understand and model an UTS in the context of smart cities and to support evidence driven decision making. The paper proposes an architecture taking into account: (a) different kinds of available data generated in the smart city, (b) big data collection and semantic aggregation and enrichment; (c) data sense-making process composed by analytics of different data sources like social media, communication networks, IoT, user behavior; (d) tools for knowledge driven decisions able to combine different information generated by analytics, experience, and structural information of the city into a comprehensive and evidence driven decision model. The solution has been applied in Florence metropolitan city in the context of RESOLUTE H2020 research project of the European Commission.

Loop Parallelism Maximization for Multimedia Data Processing in Mobile Vehicular Clouds

2019 ◽  
Vol 7 (1) ◽  
pp. 250-258 ◽  
Author(s):  
Meikang Qiu ◽  
Wenyun Dai ◽  
Athanasios V. Vasilakos
Keyword(s):  
Data Processing ◽  
Multimedia Data

Sensor Network Data Processing in Smart Cities

2021 ◽  
Author(s):  
Yehia Kotb ◽  
Mouhammad Alakkoumi ◽  
Hassan Kanj
Keyword(s):  
Data Processing ◽  
Sensor Network ◽  
Smart Cities ◽  
Network Data

Copernicus InSAR applications for the protection of Cultural Heritage: EO4GEO use case at Baia Roman Thermae

2021 ◽  
Author(s):  
Gabriele Leoni ◽  
Federica Ferrigno ◽  
Paolo Maria Guarino ◽  
Luca Guerrieri ◽  
Francesco Menniti ◽  
...  
Keyword(s):  
Data Processing ◽  
Cultural Heritage ◽  
Ground Motion ◽  
Smart Cities ◽  
Supply And Demand ◽  
Drainage System ◽  
Campi Flegrei ◽  
Use Case ◽  
Average Value ◽  
Persistent Scatterers

<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>

A hybrid framework for multimedia data processing in IoT-healthcare using blockchain technology

2019 ◽  
Vol 79 (15-16) ◽  
pp. 9711-9733 ◽  
Author(s):  
Geetanjali Rathee ◽  
Ashutosh Sharma ◽  
Hemraj Saini ◽  
Rajiv Kumar ◽  
Razi Iqbal
Keyword(s):  
Data Processing ◽  
Multimedia Data ◽  
Blockchain Technology ◽  
Hybrid Framework
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