Data-Driven Analytics for Production Impact Assessment during Unplanned Facility System Events

2015 ◽  
Author(s):  
Andrei S. Popa ◽  
Hugo Leon ◽  
Juan Medel ◽  
Tuan Nquyen ◽  
Steve Cassidy ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Data Driven ◽  
Facility System

Data-Driven Production-Impact Assessment During Unplanned Facility-System Events

2015 ◽  
Vol 67 (10) ◽  
pp. 90-91
Author(s):  
Chris Carpenter
Keyword(s):  
Impact Assessment ◽  
Data Driven ◽  
Facility System

Impact Assessment for Data-driven Innovation in Cognitive IoT Architectures

2019 ◽  
Author(s):  
G. Carvalho ◽  
A. Madaan
Keyword(s):  
Impact Assessment ◽  
Data Driven

scholarly journals Rapid Multi-Dimensional Impact Assessment of Floods

2020 ◽  
Vol 12 (10) ◽  
pp. 4246 ◽  
Author(s):  
David Pastor-Escuredo ◽  
Yolanda Torres ◽  
María Martínez-Torres ◽  
Pedro J. Zufiria
Keyword(s):  
Social Media ◽  
Impact Assessment ◽  
Rural Areas ◽  
Disaster Response ◽  
Heterogeneous Data ◽  
Data Driven ◽  
Sensor Data ◽  
Mobile Phone Data ◽  
Aggregated Data ◽  
The Impact

Natural disasters affect hundreds of millions of people worldwide every year. The impact assessment of a disaster is key to improve the response and mitigate how a natural hazard turns into a social disaster. An actionable quantification of impact must be integratively multi-dimensional. We propose a rapid impact assessment framework that comprises detailed geographical and temporal landmarks as well as the potential socio-economic magnitude of the disaster based on heterogeneous data sources: Environment sensor data, social media, remote sensing, digital topography, and mobile phone data. As dynamics of floods greatly vary depending on their causes, the framework may support different phases of decision-making during the disaster management cycle. To evaluate its usability and scope, we explored four flooding cases with variable conditions. The results show that social media proxies provide a robust identification with daily granularity even when rainfall detectors fail. The detection also provides information of the magnitude of the flood, which is potentially useful for planning. Network analysis was applied to the social media to extract patterns of social effects after the flood. This analysis showed significant variability in the obtained proxies, which encourages the scaling of schemes to comparatively characterize patterns across many floods with different contexts and cultural factors. This framework is presented as a module of a larger data-driven system designed to be the basis for responsive and more resilient systems in urban and rural areas. The impact-driven approach presented may facilitate public–private collaboration and data sharing by providing real-time evidence with aggregated data to support the requests of private data with higher granularity, which is the current most important limitation in implementing fully data-driven systems for disaster response from both local and international actors.

Observation impact assessment for dynamic data-driven coupled chaotic system

2016 ◽  
Vol 10 ◽  
pp. 2239-2248
Author(s):  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Alexander Danilov
Keyword(s):  
Impact Assessment ◽  
Chaotic System ◽  
Data Driven ◽  
Dynamic Data ◽  
Observation Impact

Impact assessment of extreme weather events on transport networks: A data-driven approach

2015 ◽  
Vol 34 ◽  
pp. 168-178 ◽  
Author(s):  
Iraklis Stamos ◽  
Evangelos Mitsakis ◽  
Josep Maria Salanova ◽  
Georgia Aifadopoulou
Keyword(s):  
Impact Assessment ◽  
Extreme Weather ◽  
Data Driven ◽  
Extreme Weather Events ◽  
Transport Networks ◽  
Weather Events ◽  
Data Driven Approach

Data-driven Approach to Environmental Impact Assessment of Real-World Operations

2021 ◽  
Author(s):  
Ameya Behere ◽  
Jirat Bhanpato ◽  
Tejas G. Puranik ◽  
Michelle Kirby ◽  
Dimitri N. Mavris
Keyword(s):  
Environmental Impact ◽  
Impact Assessment ◽  
Environmental Impact Assessment ◽  
Real World ◽  
Data Driven ◽  
Data Driven Approach
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