What is Internet of Everything? How IoE helps businesses?

 1. Intro

The idea of connecting disparate parts of our infrastructure and services together by adding power, for example, has been around for decades but with the advent of cloud computing and smart sensors, there are many more connected components out there.

The notion of having a collection of connected devices that can work as a distributed network has been around since the early days of networking (remember all those LANs you had back in high school?).

It’s only recently that these devices have become more powerful and are connecting quickly to our existing infrastructures so we can use them to create even more powerful networks in our homes, offices, and elsewhere.

And it’s this interconnectedness that IoE has in mind by bringing together different components to form a distributed network instead of having them be combined into one centralized infrastructure like we’ve seen before. But how will this work? What technology will power these networks? What business model will they support?

Also Read: What is the Internet of Things? 

It seems that companies like Alibaba want to basically bring everything connected together using their own cloud-based platform, or something similar. They came up with their own names for these kinds of systems too: “cloud factories” “cloud factories-on-demand” or “cloud factories”, etc.

I don’t find this entirely convincing when you understand how much work goes into making these products work well and what kind of scaling issues they have (or lack) compared to “just doing it themselves” for example).

Therefore I think we need several articles on the subject (this one being just one), each focusing on different aspects so you get an overview from different sides together. Then let us know what you think!

2. The Internet of Everything (IoE)

"The Internet of Everything (IoE) is a concept that takes the IoT to an extreme and deeper level when other domains of computing also come into the picture such as Edge computing and Bigdata, etc." 

 

This concept is not new. The term was first coined by Google’s Juhani Pekkala-Lilja and was very popularised by his colleague John Chamberlin at MIT taking it from their research into distributed energy networks.

While we do have some elements of this (as does everyone else), we are not doing it for our sake, but for the purpose of enabling others to do it as well. For example:

• The Internet of Things can create an even wider opportunity for blockchain technology by allowing enterprises to bring their existing data-driven applications online as well as build new ones with broad support from end-users (you may have heard about some companies that have built mobile apps using blockchain technology). The possibilities are endless — and if you can find some way to develop your own content token on top of the blockchain, why not?

• Mining power will be concentrated in the end user’s devices and networks; there will be no need for centralized servers or centralized mining pools. Such mining will be done by individual devices and networks themselves — keeping power consumption low. 

Also read: Everything about the architecture of IoT 

This means that blockchains can help reduce carbon emissions because they will use less energy than centralized mining farms. For example, if all devices could be used as computers, there would be no need to buy land or electricity costs ($2/kW), which could make electricity more affordable while keeping overall energy usage low.

More specifically: The IoT can make electricity and land available much more cheaply than they are today ($1/kWh). We estimate that such savings could meet up to $8 billion per year from just one device per household.

3. Business Benefits of IoE

In the early days of the Internet, there was a single network on which everything happened. Today, this is no longer true: everything happens on thousands of networks that connect all the parties involved.

This means that not only are you going to have to worry about security and privacy but also about latency (how long it takes for data to reach its destination) and throughput (how many transactions can be processed or how fast). 

 

It’s also worth noting that networks can be just as slow as wire services — so you’ll want to consider what kind of edge services you need.

Also Read: AI and IoT: Great Integration

It is important to note that there are different types of edge computing (and they all have pros and cons). 

But generally speaking, edge computing is a computerized device with hardware access that can perform tasks in real-time over a very short distance. 

In combination with other devices, it allows for greater processing power and lower latency than traditional data centers. 

 5. Challenges in IoE Implementation

As seen in this blog post on the topic, the concept is simple: a network of different kinds of sensors, connected by some kind of hub and/or gateway. 

These sensors will be able to gather data from the environment and send it to a central hub where it will be processed and sent to other sensors (or other distributed systems) for further analysis. 

The idea is that if you aggregate all the data from your various sensor systems together, you can get a far better picture of what’s going on in the world around you than what’s being shown to you through your eyes.

What can go wrong with this approach?

 

Well, there are several ways things can go wrong with IoT, but none of them are necessarily bad:

• The data ends up being too big and unwieldy to process. (Which could lead to “big data” problems.)

• The data ends up being not useful enough for anything useful (which leads to “unstructured data” problems).

• Unscrupulous people use your collected data for nefarious reasons (the “bad actor problem”).

This brings us back to our first topic: we need a way of dealing with large amounts of unstructured data — which we call “big data” — that doesn’t require an enormous amount of computing power at any given point in time.

It also means that there needs to be an ecosystem that allows for smart devices that collect and analyze vast amounts of information about their own environment without additional human intervention or oversight. 

Also Read: What is the future scope of IoT? 

And unlike most IoT concepts out there, this idea is not about replacing human labor with machines; it involves improving the quality and quantity of information available about an environment so we don’t waste effort collecting irrelevant detail and making decisions based on noise. 

In short, we want more information per unit of effortless noise — which means fewer errors at any time. This is not a new idea; it was first proposed by Robert Metzger in 1966 when he talked about intelligent machines learning through experience rather than through programming instructions. 

It was later popularized by Jerry Yang & Yahoo! in 2001 when they coined the term “IoT" as an umbrella term for Internet-based devices that collect and process large amounts of unstructured information about an environment (a world beyond just computers).

6. Conclusion

The Internet of Everything is a broad term in computing and has been used in many different contexts, but the most popular one is that of the Internet of Things. This includes devices that are connected to the Internet and software that can control the device.

It is widely believed that if we create a trend like this within our society, it will be far more beneficial than technology like AI. The world simply cannot afford to be left out of this revolution.

A key question for any company trying to get into this space is: “What do I do?” Your answer will have much to do with how you think about your customers, your product’s features, and even your culture and organizational structure.

If you look at what people are doing today (looking at all these IoT-based companies), it’s clear that there is no real consensus on what exactly it means to be an IoT company: there are many definitions, many different approaches, and strategies (and the best ones may not be technically feasible).

But equally clear is that there are few IoT companies who know exactly how they intend to avoid falling prey to various pitfalls (such as copycats). So what should you be doing? What should you avoid? And what could you do instead?

The following opinions draw from my 15 years of experience as a machine learning engineer at Google as well as my consulting work with startups and established enterprises in this space. 

Most importantly, they aim to help founders understand their product from both ends: from inside their organizations, but also from outside their organizations (i.e., marketing).

So, that's it from my end today, we'll meet again with a new and interesting discussion. 

 So, till then, Ta-Da!