A hyper-scale data center can help in setting up an efficient command and control center as it can process large volumes of data.
A unified command and control center in a
smart city is a central hub where all the incoming data from different systems
are processed. This is required to ensure proper coordination among all the
public bodies. NEC India has shown how a hyper-scale data center can
help in setting up efficient command and control for a smart city.
Smart solutions for waste management and
parking require large volumes of sensor-based data to be processed in
real-time. Intelligent transport management systems and intelligent traffic
management systems are other systems that require efficient processing. A
hyper-scale data center can be used to house critical computing and network
infrastructure required for smart city operations.
A command and control center will be required
to process different data streams. Compared to a conventional data center, a
hyper-scale data center will be able to handle high volumes of data traffic of all types. It will be able to meet the
increasing demand for data processing and storage.
A unified command and control of a smart city
can be a power-guzzling behemoth. This is owing to the large scale of
operations in a smart city. However, a hyper-scale data center uses power
efficiently. One can compare it to a zero-emissions vehicle.
A master systems
integrator can design and develop a command center for running virtual machines
with the help of a single physical server.
This helps in
optimizing resource utilization and enabling better scalability and flexibility
in managing workloads.
Smart traffic and public safety solutions
depend largely on an efficient unified command and control. A master systems
integrator will ensure a seamless integration of various ICT components with
unified command and control.
This technology allows a single physical
server to run multiple virtual machines (VMs), optimizing resource utilization
and enabling better scalability and flexibility in managing workloads.
Source referred: https://in.nec.com/en_IN/press/201910/20191015_01.html
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