scholarly journals Risk assessment to curb COVID-19 contagion: A preliminary study using remote sensing and GIS

2020 ◽  
Author(s):  
Shruti Kanga ◽  
Gowhar Meraj ◽  
Sudhanshu ◽  
Majid Farooq ◽  
M. S. Nathawat ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Reduction ◽  
Industrial Revolution ◽  
Risk Mitigation ◽  
Intelligent Decision Making ◽  
Risk Indices ◽  
Intelligent Decision ◽  
Eastern Zone ◽  
Integrated Hazard

Abstract Globally, COVID-19 pandemic has become a threat to humans and to the socio-economic systems they have developed since the industrial revolution. Hence, governments and stakeholders are calling for strategies that could help to restore the normalcy while dealing with this pandemic effectively. Since, till now, the disease is yet to have a cure; therefore, only risk-based decision-making can help governments to achieve a solution that is sustainable in the long term. To help the decision-makers to explore viable actions, we here propose a risk assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water and associated land use/ land cover, are related with COVID-19 contagion and calculated them in a GIS-based multi-criteria risk reduction method. The results showed disparateness in COVID-19 risk areas with higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed to prioritize wards that are under higher risk zones for intelligent decision-making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

Intelligent decision-making with bird-strike risk assessment for airport bird repellent

2018 ◽  
Vol 122 (1252) ◽  
pp. 988-1002 ◽  
Author(s):  
Weishi Chen ◽  
Jie Zhang ◽  
Jing Li
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Real Time ◽  
Expert Knowledge ◽  
Assessment Model ◽  
Classification Model ◽  
Support Vector ◽  
Bird Strike ◽  
Intelligent Decision Making ◽  
Intelligent Decision

ABSTRACTAn intelligent decision-making method was proposed for airport bird-repelling based on a Support Vector Machine (SVM) and bird-strike risk assessment. The bird-strike risk assessment model is established with two exponential functions to separate the risk levels, while the SVM method includes two steps of training and testing. After the risk assessment, the Bird-Repelling Strategy Classification Model (BRSCM) was trained based on the expert knowledge and large amount of historical bird information collected by the airport linkage system for bird detection, surveillance and repelling. Then, in the testing step, the BRSCM was continuously optimised according to the real-time intelligent bird-repelling strategy results. Through several bird-repelling examples of a certain airport, it is demonstrated that the decision accuracy of BRSCM is relatively high, and it could solve new problems by self-correction. The proposed method achieved the optimised operation of multiple bird-repelling devices against real-time bird information with great improvement of bird-repelling effects, overcoming the tolerance of birds to the bird-repelling devices due to their long-term repeated operation.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

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