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Robust AI Methodologies in Bigdata and IoT

Santosh Kumar Nanda

Speedy developments in hardware, software, and communication technologies have allowed the emergence of Internetconnected
sensory devices that provide observation and data measurement from the physical world. In addition to
increased volume, the IoT generates Big Data characterized by velocity in terms of time and location dependency,
with a variety of multiple modalities and varying data quality. This AI trend will allow businesses to gain insight into
their processes by using all the information contained in their system and creating an overall, real-time, and accurate
visual model of all the processes. Throughout the last few decades, Big Data has become a perceptive idea in all the
noteworthy technical terms. Additionally, the accessibility of wireless connections and different advances have facilitated
the analysis of large data sets. Organizations and huge companies are picking up strength consistently by improving
their data analytics and platforms. Intelligent processing and analysis of this Big Data is the key to developing smart IoT
applications. It more important to use specific and proper data pre-processing tool to handle big data. Especially it is
important to choose a distributive architecture to read the big data and then reuse it for machine learning model. In
a world of advanced technologies where IoT and remotely controlled devices having top-notch protection is of critical
importance. To make faster and safer IoT application, now researchers focused on wider application of machine learning
in IoT. .