Advanced Deep Learning Applications in Big Data Analytics: Introduction of Internet of Things

Introduction

Introduction of Internet applications for end users during 80’s, it starts its journey as information provider and later it occupies the various real life sector like communication, science, education, business, government, and humanity. It clearly expose that, Internet is becomes powerful and most important innovations by human history.

The Internet of Things, or IoT, sometimes referred as Internet of Objects, is a system of interconnected computing devices, digital machines, mechanical machines, objects, or people that are identified by Unique Identifiers (UIDs) with the ability to transfer data over a network independently .

In IoT, a “thing” can be a person, a animal, an automobile or any other natural or man-made object with sensors and have the ability to transfer data over a network with or without human intervention. These sensor embedded devices had been assigned an IP address and protocols to transfer data over a network.

Now IoT represents the next evolution taking a huge leap in its ability to gather, analyze, and distribute data. It helps to turn these huge set of data into information, knowledge, and ultimately wisdom. This helps the Machine Learning Algorithm developers to have most accurate use cases in optimizing their codes.

However in present scenario, it becomes mandatory for government, businesses, standardizing bodies, and academia people to work together, to enrich and enhance IoT applications in more secure and cost effective devices. In this context, a “Smart” Object refers to the objects or things which holds the embedded sensors devices, and be the part of Internet of Things world.

According to Cisco’s Internet Business Solutions Group (IBSG) it is defined as, IoT is simply the point in time when more “things or objects” were connected to the Internet than people.(Drury, 2011) As IoT evolves, these networks, and many others, will be connected with added security, analytics, and management capabilities (refer Figure 1). This will allow IoT to become even more powerful in what it can help people achieve.

Figure 1.

IoT Can Be Viewed as a Network of Networks

In recent years, availability of “Smart Devices” explores that, attachment of a wide range of devices to the network is expanding in exponential process. These “Smart Devices” had includes household appliances, medical devices, vehicles, street lights, traffic controls, smart TVs and digital assistants such as Google Home, Amazon Alexa, etc. Industry analysts estimate that number of connected devices will expand to more than 25 billion by 2020. The increasing deployment of these devices has enabled new use cases for researchers in network technologies and security perspectives.

An Internet of Things makes computing truly ubiquitous – a concept initially put forward by Mark Weiser in the early 1990s.(Lukowicz, 2004) This development is opening up huge opportunities for both the economy and individuals. However, it also involves risks and undoubtedly represents an immense technical and social challenge.

The term “Internet of Things” was popularized by the work of the Auto-ID Center at the Massachusetts Institute of Technology (MIT), which in 1999 started to design and propagate a cross-company RFID infrastructure.(Ashton, 2009) In 2002, its co-founder and former head Kevin Ashton was quoted in Forbes Magazine as saying, “We need an internet for things, a standardized way for computers to understand the real world”.(Schoenberger, 2002) This article was entitled “The Internet of Things”, and was the first documented use of the term in a literal sense.(Coroama, 2006) However, already in 1999 essentially the same notion was used by Neil Gershenfeld from the MIT Media Lab in his popular book “When Things Start to Think”(Gershenfeld, 1999) when he wrote “in retrospect it looks like the rapid growth of the World Wide Web may have been just the trigger charge that is now setting off the real explosion, as things start to use the Net.”