Data Mining in Internet of Things

Data generated by commercially internet of things (CIoT) have been growing in a very large exponential rate. Data mining plays an essential role in deriving actionable information from these raw data. By applying a variety of data mining technologies to historical and real time data, building supervised or unsupervised models, deploying them into the production environment to help business make better decisions, significant value can be created resulting in reduced waste, improved efficiency and broaden opportunity.  The relation between data mining and CIOT has found applications in commercial industries such as manufacturing, energy, healthcare, retail, smart city and transportation.

A range of IoT devices can be connected over a network and have data driving in from all directions. That sure is a lot of data. But how do we make sense of all this data to obtain valuable insights about customer’s health, home, and electricity consumption? That’s where data mining comes to the save. If you look at the whole data, it might appear as garbage. However, hidden patterns can be traced and extracted by leveraging smart data mining algorithms to assemble and examine the data to provide useful analytics.

Internet of Things (IoT) means making the everyday objects ‘smart.’ It involves the installation of sensors and controllers in the devices, allowing them to stay connected, communicate, and share data over a network. The interesting catch here is that any device that can generate data falls under the umbrella of ‘Internet of Things’ (IoT), including smart homes, drones, wearable devices, smart vehicles, health monitoring devices, and a range of sensors. Our college conduct many workshop on Data mining, artificial intelligence, machine learning, IoT. Our college is the best college in Faridabad. It is the top BBA and BCA College in Delhi NCR as well as Haryana. It is the best B.tech College in Faridabad.

The data preparation stage involves the integration of data from various data sources and cleaning the data. On the other hand, the data mining stage is one where algorithms are applied to find and evaluate the patterns from the data. The final stage is the data presentation stage where the data is presented to the user to obtain useful insights. However, the process of big data mining from IoT comes with its own set of challenges such as disparate datasets, large volumes of data, and the integrity of data sources. With the increasing popularity of IoT, new solutions and data mining algorithms are being developed to tackle such problems.

 

                                                                 Ms. Bhawna

                                                                  Assistant Professor

Department of Computer Science Engineering

Echelon Institute of Technology Faridabad