Gateways are necessary cog of IoT ecosystems to maintain security to a certain extent.
They engage in encryption algorithms to mask data. Hence, as an intermediary, it is responsible
to shield the entire IoT systems from any cyberattack like botnets.
Cloud
IoT deals with vast data sets; it is one of the most important assets in the ecosystem. This data
is generated from users, devices, and applications and requires some sort of management. This
management is provided by the IoT cloud which accepts data, accumulates, maintains, and
stores in real time. Since, we are talking about the cloud which can be easily accessed via the
internet at any time, from any place; therefore it is valuable for management to view data from
remote locations. As a result, this remote monitoring helps the leadership to assess and come
up with rational decisions.
IoT cloud can also be seen as a huge network that contains plenty of optimized servers
which require speedy processing of incoming data from millions and billions of devices as well
as manage trac and oer key insights.
But how is this data stored exactly? Due to so many devices, sensors, and other elements in
the infrastructure, the centralized databases are not suitable to address performance and query
issues. Therefore, Cloud often uses DDBMS or distributed management databases to manage
data.
A cloud in an IoT solution may cover billions of sensors, protocols, gateways and collect
data from them to apply machine learning algorithms. The foresight gained from the cloud
can facilitate businesses to understand their products and services better and rectify their
vulnerabilities.
Name a real life IoT deployment took place in Cloud?
Flash Question
Analytics
Today, data is a priceless asset. The rise of “big data” is based on certain realities. Heavy competi-
tions across dierent industries has made organizations excel by collecting large data sets from
their client-bases and extract meaning out of it to address major concerns. These analytics are
also an integral part of IoT systems.
Analytics refers to the procedure which indulges in the conversion of data in the analog
format (coming from a wide range of sensors and IoT-enabled devices). The conversion results
in an output detailing meaningful suggestions and recommendations. This output then goes on
to reflect the existing state of the user’s organization and helps managers to gain new insights.
An IoT infrastructure without analytics is incomplete because if proper analytics are not per-
formed on the data, then all the collected and accumulated data becomes pretty meaningless.
For organizations analytics in IoT is a big opportunity to reform their traditional busi-
ness processing. The sales department can use this information to understand consumer hab-
its. The marketing department can use these suggestions as part of its integrated marketing
campaigns. The operation managers may realize the lack of required machinery in an area and
re-compensate with the allocation of budget for a fresh piece of machinery.
42 Internet of Things
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