| dc.description.abstract | In internet of things (IoT) paradigm, crowdsourcing
is the process of obtaining and analyzing information or input to a
particular task or project generated by a number of sources such
as sensors, mobile devices, vehicles and human. Cloud computing
is widely used for the services such as analyzing crowdsourced
data and application implementation over the IoT. Nowadays,
every country and human are prone to natural and artificial
disasters. Early detection about disasters such as earthquakes,
fire, storms, and floods can save thousands of people’s life and
effective preventive measure can be taken for the public safety.
All the crowdsourced data which are providing the information
of a certain geographic region are analyzed in a cloud platform.
But, by the time the crowdsourced data makes its way to the
cloud for analysis, the opportunity to act on it might be gone.
Moreover, thousands of people’s life will be lost. Therefore, fog
computing is the new and efficient way to analyze such critical
crowdsourced IoT data of disasters. In this paper, in order
to detect and take necessary steps for public safety during a
disaster, we propose a crowdsourcing-based disaster management
using fog computing (CDMFC) model in IoT. Further, we also
proposed a data offloading mechanism for our CDMFC model
to send disaster-related IoT data to the fog even if a direct link
to the fog is not available. Our proposed CDMFC model and
its data offloading mechanism can detect real-time disasters and
disseminate early information for public safety as compared to
the conventional cloud computing based disaster management
models. | language |
