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also take the opportunity to acknowledge the contribution of Dr. Vineet Sharma, Head of the Department of Computer Science & Engineering, KIET, Ghaziabad, for his full support and assistance during the development of the project. We also do not like to miss the opportunity to acknowledge the contribution of all the faculty members of the department for their kind assistance and cooperation during the development of our project. We also do not like to miss the opportunity to acknowledge the contribution of all faculty members, especially Professor Arvind Kumar, of the department for their kind assistance and cooperation during the development of our project. Last but not the least, we acknowledge our friends for their contribution in the completion of the projectIoT

History We’ve been intent with gadgets that function on a grander scale for decades, but it’s only been in the past several years that we’ve seen the IoT’s true potential. The concept evolved as wireless Internet became more pervasive, embedded sensors grew in sophistication and people began understanding that technology could be a personal tool as well as a professional one. e inter-dependent and should be jointly developed. In general, the deployment of IoT increases the amount of data in quantity and category; hence, offering the opportunity for the application and development of big data analytics. Moreover, the application of big data technologies in IoT accelerates the research advances and business models of IoT. The relationship between IoT and big data, can be divided into three steps to enable the management of IoT data. The first step comprises managing IoT data sources, where connected sensors devices use applications to interact with one another. For example, the interaction of devices such as CCTV cameras, smart traffic lights, and smart home devices, generates large amounts of data sources with different formats. This data can be stored in low cost commodity storage on the cloud. In the second step, the generated data are called “big data,” which are based on their volume, velocity, and variety. These huge amounts of data are stored in big data files in shared distributed fault-tolerant databases. The last step applies analytics tools such as MapReduce, Spark, Splunk, and Skytree that can analyze the stored big IoT data sets. The four levels of analytics The Internet of Things is the concept of everyday objects – from industrial machines to wearable devices – using built-in sensors to gather data and take action on that data across a network. So it’s a building that uses sensors to automatically adjust heating and lighting. Or production equipment alerting maintenance personnel to an impending failure. Simply put, the Internet of Things is the future of technology that can make our lives more efficient. start from training data, then move on to analytics tools, queries, and reports.