If those internet buzz words still blurry in your mind or you just heard everyone is murmuring around or even not yet clear-cut the differences. Well, you’re in the right place with no need to worry about it simply because we’re all in the same learning journey.

Internet of Things—IoT

In my previous post, we debated pretty good on Big Data! In this column today, we’re going to explore the world of IoT then underwent its eager relationship with Big data! So what is IoT? Think about anything that can be connected of a kind wearables, cars, homes, cities and industrial for instance.

In anticipation of your understanding, I do not mean the Internet of Things is a technology. It’s simply a concept! Yes, the technology used to connect devices frames this notion called IoT. In fact, this term was first introduced in 1999 by Kevin Ashton, a technology pioneer from MIT. Technically speaking, IoT framework is built upon three main blocks: enablers, platforms and industrials.

Enablers: we need Wifi, cellular, sensors, and some micro-controllers.

Platforms: any software capable to manage all those connections between devices further to data analytics.

Industrials: any industrial vertical you can think about from healthcare to transportation. But, it’s not limited to a specific industry by its literal meaning. As mentioned earlier, homes, cars, cities and other landscapes can be empowered by IoT alike.

To sump up this definition, the Internet of Things is a new mega-trend concept in technology. It enables people and any other device or equipment to be connected to the network with the purpose to increase efficiency, adds intelligence to manual processes and extend productivity gains to things that can arrange from our wearables to industrial verticals.

Back to our question of Big Data versus IoT, we mentioned enablers as one of the building blocks that form IoT. Big Data is the cornerstone of the whole concept of IoT to be successfully enabled afterwards! Imagine dozen of devices that are interconnected at your home flooding hefty information to auto-execute orders or specific tasks. In similar fashion, exabytes of real time data will be generated, processed, analyzed and accomplished. Bingo! Big Data is the “oxygen” and the “currency” of IoT.

Well, you would wonder what’s the benefit of pondering on this concept then using its technology? In our Big Data post, we mentioned some very good examples where IoT is the mainstream of the entire process. You remember TfL or Transport for London case raised earlier, we saw how the city of smoke is managing smartly its transportation system making life easy for millions of people who use public transportation on a daily basis.

Or let’s think from a micro-level angle, if we take our homes where so many daily routines either lighting, entertainment, appliances, security or Air Conditioning, can be handed over smart technologies then easy managed via our smartphones, smartwatch, smartbracelet or tablets. on the same line, we can brainstorm hundreds of things that can make our lives better, save us money, save lives, preserve our natural resources and so forth. Having said that, privacy concerns and security issues is the next big myth challenging to realize the full potential of IoT. A study by HP found 7o% of oftentimes devices used in IoT have security faults! WHAT? Unfortunately YES! So, thinking about what you say or do in your own home or office will become a nightmare!

This concern is aggrandized with the number of IoT devices “likely to be connected” will reach 20.4 billion by 2020 as per some analysts! I’m not trying to hyperbolize this concern herein but notifying anyone who gets to know those concepts for the first time. Nevertheless, I’m shortening this privacy affair with a statement of John MacAfee, who founded the first VirusScan company in the world, in 1987: “Privacy is complex. It’s not as simple as ‘I’ve got nothing to hide therefore, I’ve got nothing to fear.’ If everyone knew everything about everyone else, there would be riots in the streets”.

Artificial Intelligence—AI

What’s next, a shining emerging area in computer science with an aspiring plan to develop highly intelligent machines called Artificial Intelligence or AI. This later is  not a new field since it was born in 1950s during the time a computer is capable of performing a task that requires human intelligence.

Today, AI is tackling many areas where machines and robots are fed with a sizeable amount of data so they can mimic humans in performing and completing assorted intelligent jobs. Well, AI is not anymore a science-fiction movie but a reality we see nowadays happening before our eyes! Everyone must heard of the AI robot Sophia or what is called a social humanoid robot developed by Hanson Robotics, a Hong-Kong based company specialized in human like robots and AI.

Sophia for instance learns from any human interaction she has with public added to her prowess across many other industries. She can process visual data by recognizing faces or emotional data by expressing her sentiments so then relationships with people can be formed to some extent. It’s purely backed by a user interface software programmed to run different situations as per some specialists.

In parallel, this mesh robot uses machine learning techniques helping Sophia to match a preloaded text with her facial expressions while spelling it out. Also, this bot has a dialogue system that runs lot of algorithms when it turns to see a face then listen to a question. In like manner, it chooses a pre-filled response that corresponds exactly what an interviewer just said.

What’s amazing about AI compared to IoT is the mechanism of what a machine is capable to do is not limited. So you cannot tell what will happen or what would be the answer until the machine does it or delivers it to you. In IoT, you’re expecting what a particular connected device would do for you like switching off your living room light, or locking your main door, or adjust your home temperature.

Another feature which makes AI a phenomenal research area is its deep learning aptness that machines are compiling at once the fitful data gathering process. Again, Big Data is “the atomic number 8” of Artificial Intelligence.

Initiating this section with our chatbot Sophia example doesn’t mean that AI is all about humanoid robots! As a matter of fact, AI is being used in dissimilar industries and fields namely healthcare where machine learning is applied to make faster and better human diagnoses. In finance, many AI softwares can perform personal loan applications like Mint or IBM Watson.

Other areas are witnessing lot of robotic automation such as business, education, law, manufacturing and the list goes on. Regardless, security and privacy will remain breathtaking concerns similar to what we raised about above IoT feebleness in the  first section of this post.