Abstract
Web sensing devices capture and transmit data from the physical
environment to a central place using rapid advances in software, hardware, and IoT
technologies. Depending on the source, the overall count of web-connected devices is
estimated to be between 50 and 100 billion by 2025. The amount of data released will
increase as the population expands and technology improves, which is already
happening. The Internet of Things (IoT) technology connects and interacts with the
physical and virtual worlds. A gadget linked to the Internet is called an IoT. Intellectual
data handling and investigation are required to construct smart IoT requests. This
article gives knowledge about the Machine learning (ML) algorithms available for
dealing with IoT data challenges, using smart cities as the primary use case. This article
looks at common IoT diagnostic applications. This research compares and evaluates the
predicted precision and understandability of supervised and unattended ML models.
These technologies are briefly addressed in desktop, mobile, and cloud computing
settings.