Today’s Machine Learning (ML) (a subset of Artificial Intelligence) in a blend with Internet of Things (IoTs) based cloud applications which play a significant role in our everyday life. As indicated by Gartner’s recent study, there are around 25 billion devices and a gadget interfacing with IoT including wearable’s and automated vehicles to smart homes and smart cities applications. All such connected (smart) devices generate immense data that needs to be examined and analyzed, to ensure that they continually learn from the available data sets and better themselves without any manual interference. This is where the prerequisite for machine learning comes into being. The numerous ML algorithms and techniques that are introduced in a short time to easily evaluate big data measurements, increasing the IoT’s productivity. Similarly, special ML techniques, such as decision trees, clustering, neural and Bayesian networks, allow devices and gadgets to discern trends from various sources in different kinds of data sets and take appropriate decisions based on their analysis.
It would really be difficult for smart devices to make smart decisions gradually without including and enforcing ML. The IoT helps to interconnect various hardware devices, such as houses, cars, electronic gadgets and other devices that are integrated with actuators, sensors and software, so that data can be collected and shared. As various organizations understand the progressive capability of the IoT, they have begun finding various obstructions they have to deliver to use it productively. Numerous organizations and businesses use ML to exploit the IoT’s latent capacity. We will discuss different methods of machine learning (or Artificial Intelligence) that deal with the challenges posed in the handling of IoT data. Note that this big data is generated through the communication of Internet of things/ smart devices, and this data stored at cloud.
Amit Kumar Tyagi will be speaking at International Congress on Grid, Distributed & Parallel Computing 2021 which is scheduled to happen on 13th and 14th August 2021 at Hong Kong, HKSAR.