When it comes to three-letter acronyms, two that you’re probably hearing a lot about today are the Internet of Things (IoT) and the Internet of Everything (IoE). What you may not hear so much about is the subtle, but critical, difference between them. This difference boils down to one thing – an intelligent connection. It is only the intelligent connection that has precluded both IoT/IoE devices from being more pervasive than they already are. We have no problem generating mountains of data. But, being able to use this data meaningfully has been the main bottleneck. That, however, is rapidly dissipating.
Ordinary vs IoT Devices
For thousands of years, all tools and appliances required humans to physically interact with them to be useful. To turn on a simple light, someone had to hit the light switch.
What makes IoT or “connected” devices different? Two things:
- IoT devices have a unique identifier (UID) – an alphanumeric address.
- IoT devices can receive and/or transmit data over a wireless connection.
These two things make it possible for connected devices to collect, transmit, or share data with each other – with or without human-to-device interaction. As an example, motion detectors can automatically turn on lights as someone enters a hallway, then turn it off after they exit the area.
The Internet of Everything
IoE distinguishes itself from IoT by giving it an intelligent network connection. That “intelligence” tracks and makes use of data generated by people, devices, processes, and potential environmental or other conditions. Within an IoE environment, in addition to Smart Lighting, the network may track who is accessing specific work areas, for how long, what other devices they interact with, how many actions they conduct and how many errors they generate. Potentially, everything can be measured – and there is a relationship between everything.
That’s the kind of data Amazon actively tracks in their warehousing facilities:
The Intelligent Connection or… the Missing Link?
In the course of human evolution, scientists often talk about the “missing link” in the evolution of mankind from ape. We have sort of the same thing when it comes to the evolution of IoT and IoE devices. Electronic devices are mainly limited by the software that drives them. That software or app may only have a single function or small range of functions often predicated on statements like, “If This, then That.”
What makes the Internet of Everything possible is software capable of comparing and sorting multiple data points to produce a decision or action. It takes on the form of something like:
“If This, This and This, then That and That, unless A or B.”
With such a statement, each permutation could generate a different outcome or combination of outcomes. The kind of logic employed in IoE networks now does not come close to “Artificial Intelligence” as popularly envisioned, but it is capable of making complex decisions. IoE is capable of making use of multiple databases and data from multiple networks.
Amazon Go as a Prime IoE Example
To describe how Amazon Go works – you enter the store, pick up what you want, and when you leave your Amazon account is charged for everything you leave with. The technologies that make Amazon Go possible include:
- Computer vision
- Facial recognition
- Biometric data
- RFID readers
- Motion detection
- Smart shelving – weight sensors
- Sensor fusion
- Mobile Wallets
- Purchasing history
As an alternative to my describing it for you, you might check out the Amazon Go Patent Application itself. Everything and everyone is tracked by video cameras and a variety of sensors. Even if the video is not able to directly see what you are taking, proximity awareness via geofencing along with shelves tracking the weight of products can likely make the determination. Combined with your purchasing history, to compare against what you’ve bought in the past, Amazon Go is able to accurately determine what you’ve added to your cart.
Amazon Go also probably connects that to its inventory management system to determine optimal shelf space by product, stocking frequency, and order replenishment.
Assimilate or Be Assimilated
Regular readers know that I frequently reference what Amazon is doing and that I think the company is a serious threat to retailers. It’s not that I don’t like Amazon, just the opposite. I worked at Amazon from 2001 to 2004 in several roles including in the Lexington Secure Network Operations Center (SNOC) and loved it. Even then, Amazon tracked everything, automated what it could and aggressively worked to improve all of its performance metrics. Its growth since serves to underscore that it has only continued to improve upon its work processes, efficiency, and productivity metrics.
Some get on me for fear-mongering or crying, “Wolf!” over Amazon. That’s just silly. Comparing Amazon to anything less Borg, misses the mark completely. Yes, Borg – pretty much the epitome of the Internet of Everything. Okay… go ahead and say it.
Yes, but I’m not the only one. As I recently mentioned, many of today’s leaders in technology stopped listening to the experts on Mainstream Media years ago. Most, instead take their cue from sci-fi visionaries like Stanley Kubrik and Gene Roddenberry. That includes the Richest Man in the World, Jeff Bezos, and the Richest Man in China, Jack Ma – founder of Alibaba. Both men love Star Trek, both have companies that closely resemble how Borg works. Coincidence or Design?
Amazon and IoE – Taking it Too Far?
While on the topic of IoE, I came across this article on The Verge about “How Amazon automatically tracks and fires warehouse workers for ‘productivity’.” It does and always has fired both temporary and full-time workers for failing to “make quota” and “time on task” metrics. Typically, Amazon only hired the top-performing 10% of its temporary workers brought on each year before each holiday season. That 85% of its workforce is not fired for poor performance reinforces and justifies the effectiveness of its IoE-enabled tracking.
Amazon’s environment is intense – not everyone is going to like it. I started as a picker and if I recall correctly, the average picker walked about 15 miles during their 12-hour shift. At the time, the quota was around 120 items per hour – with books placed in random order at each location. At first, everyone struggles to hit their numbers but after 8 weeks of pre-holiday peak season, anyone who cared to hit quota was doing so quite handily – and with time to spare for an unplanned bathroom break.
Amazon has a near-religious devotion to defining all of its work processes. It constantly focuses on improving all of its performance metrics. There’s virtually nothing it does not track. One Six Sigma project focused on reducing the number and frequency of papercuts. That may sound exceedingly anal retentive.
If 3-5% of 300 employees get a papercut per shift, and each requires 15 minutes to treat, that’s $20-40k in employee downtime per year. But, that has a much higher impact on total throughput. Amazon’s general managers know exactly how much money is lost for every minute one of its lines isn’t running.
Data and IoE – Amazon IS your Case Study
Consider how Lanchester’s Laws might work in a (mostly) free market, capitalistic economy. Amazon has over 645,000 employees, 100,000 robots, over 2 million third-party sellers and over 400,000 affiliated webmasters. That’s the largest “army” in the world. The implication, unless something dramatic changes is that the “market” as we know it will be dominated by a handful of mega-corporations like Amazon, Ali Baba, Apple, Google, and Microsoft.
Amazon isn’t just tracking everything its army of employees, robots, affiliates, and sellers do. Amazon’s also tracking the purchasing habits associated with 50% of all online sales in the United States, with its Whole Foods chain and other brand name websites, too. In Amazon’s world, “Everything and Just About Everyone is Connected.”
In short, Amazon IS your case study for the Internet of Everything. Most (assuredly not all) of what Amazon is doing where IoE is concerned is public knowledge, almost entirely on public display. Their software and, algorithms may be closely guarded secrets, but are all based on logical processes and functions associated with real-world facilities, devices, and real people.
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