What is IoT?

The term Internet of Things or also known as IoT was brought in by industry researchers but has turned into mainstream public view very recently. IoT is a network of physical devices, including things like smartphones, vehicles, home appliances, and more, that connect to and exchange data with computers. A lot says that the Internet of Things will completely transform how computer networks are used for the next 100 years, while others believe IoT is simply hype that will not bring much impact into the daily lives of most of the people .

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Internet of Things manifests a very common concept for the competence of network devices to sense and collect data from the world around us, and then share that data all over the Internet where it can be accessed and used for many intellectual and interesting purposes.Some also use the term industrial Internet interchangeably with IoT. This refers primarily to commercial applications of IoT technology in the world of manufacturing. The Internet of Things is not limited to industrial applications.

IoT a key component for a better business world

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The paradigm shift that the industrial and digital revolution altogether is unable to bring will soon be brought with the help of ARTIFICIAL INTELLEGENCE (AI) and INTERNET OF THINGS (IoT) into the world of business and society which will also greatly help in modifying and give it a better shape .However , on our way towards future what we find people talking about is, how AI components are actually enforced in IoT resulting in an productive consequence . The wisdom is where a factor is thought to be critical but is actually not critical influences the IoT architecture.

Most of the managements believe that the appropriate place for AI is in the cloud , since it is the actual space where they are transferring their data and IT computing force. However , the most essential requirement for functional IoT is interpretable connections between the various sensors at the edge to a portal/entrance and directionalize from the cloud – which poses the problem of quiescence thereafter.

Almost all the AI and the machine learning applications that can actually transform industries and modify the shape of our world and society stands in need for appropriate responsiveness . For example , while Google Home takes in replying our questions about daily weather report , the response to the random vehicles on the road or any machine in a random factory is both a different issue.

Many AI applications requires a lot of computational potential to access algorithms and device data .When real time response and low quiescence is critical , you need edge computing architectures , but not always . AI can still be done in the cloud, in a data warehouse, at the edge, or on an IoT device — or with a mixture of all of these. So before making a magnificent IoT architecture , the very basic criteria is that you need to know which computer power goes where, which will help you to create a balance between the economies of scale provided by the cloud with the performance requirements of having AI processing performance at the edge.As Lou Lutostanski,( vice president, Internet of Things, Avnet) rightly points out as “fluid computing” , where there are various levels computing intelligence and processing throughout the network architecture , but it’s really an encircling term for this transformation of term for IT computing power in the cloud to operational technology (OT), computing power at the edge.

IoT opens ways for various unworthy actors, since encryption and other security protections those are very much difficult pack into endpoint devices, and thus security becomes another concern. The architectures that implements secure entrances between the cloud and IoT devices can alleviate security risks, also providing low latency. If there is not prominent security then problem may occur throughout the architecture, where the implementation of the AI system may get vulnerable. Thus, there needs to be a trust of data from the device to the cloud, if not then the probability of compromised or bad data decision increases.

Overabundance : An important factor in IoT.

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The matter of overabundance is important as well. Managements needs to determine if they have enough overabundance into their architectonics, so that if something is wrong then the network will recover . Thus we can assume that AI driven IoT will go through a highly complex ecosystem with many savvy and eloquent parts that will unfold over time as we move more closer to the world we are shaping, or else problem like security risks, unexpected downtime, low efficiency and information quiescence will cripple an organization’s ability to hand over on the promises of IoT.

IoT is a complete game-changer, propagandist and a mammoth business opportunity for everyone.

However, the reality is that what most of the companies have eyes opened wider when it comes to INTERNET of THINGS . Business are struggling to implement IoT initiatives because compared to the conventional information technology projects , they require various hardware and software resources as well as assimilation in a more wider range.

Galvanizing the edge:

Power availability is a major issue for edge devices in many IoT applications – not so much for activators, but very often for senators.

  • If for example, a tracker application in which a device is dropped into a parcel consigned for shipment; the user can track the parcel during its journey and check its progress or even if it has been mistreated. Clearly, no wired connections are possible, so the device must communicate wirelessly while relying on an internal power source. However, in other scenarios, edge devices may be located in urban areas, and possibly in large quantities.
  • No mains power is available, while maintenance visits to replace batteries are time consuming and expensive. Edge sensor designers can respond by using rechargeable batteries or super capacitates together with an energy collecting strategy to generate charging current for them. Energy accumulation is alluring, as it taps into an inexhaustible supply of ambient energy, but it is also challenging as it may not meet the power needs of the node without careful design.

Therefore, taking each and every possible step to abbreviate the node’s power demand is essential in achieving viability for the energy harvesting approach. Even if a standalone battery must be used, power optimization remains important. Saving just a few micro Joules a second can mean changing a battery only after 10 years instead of every year.

IoT’s contribution to hybrid computing services:

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One essential point that should be added before we conclude is the new hardware and software development. As we will go through the time as AI moves towards the edge, we will see more manufacturers designing and creating specific AI chips, especially for IoT implementations. Venture capitalist have started lowering the startups and also the large power houses such as Google , Apple , Microsoft , Intel which are even getting on custom chips. The major cloud players like Amazon and Microsoft will bring new edge into the world of hybrid computing services.

Supplying power to this new proliferation of IoT devices and their network connections can be expensive and logistically difficult, however if all these eloquent points or pieces are joined together means providing a great deal of pliability in the solutions and consequences, and thus to conclude AI implemented IoT , at the edge will be key to a paradigm shift which highly stands in need for a long term business growth.

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Barry Davis is a Technology Evangelist who is joined to Webskitters for more than 5 years. A specialist in Website design, development & planning online business strategy. He is passionate about implementing new web technologies that makes websites perform better.


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