Investor ’ s Guide to IoT : Understanding the Ecosystem
By Mike Kavis
Editor ’ s Note This is the first installment of a 4-part series entitled An Investor ’ s Guide to IoT . The full series is available at cloudtp . com / insights
The goal of this series is to bring clarity to what IoT is and what types of companies make up this complex ecosystem , so that investors new to the space can get their arms around this vast market .
Disclaimer : The views and opinions expressed herein are those of the author , are not intended to provide tax , legal , insurance or investment advice and should not be construed as such .
The IOT Ecosystem
Just about every technology company now says they ’ re an IoT player . This of course happens with each new technology shift . In most cases , a company will have some products or services that touch the IoT industry . However , many are just repackaging and renaming existing products or services . To truly understand whether a company is an innovator in this space or just putting IoT lipstick on their legacy pig , one must understand the overall IoT ecosystem , as well as its parts .
I created the image to the left in an attempt to organize IoT technologies and processes into a collection of categories , which I call layers .
There are 7 layers that make up the IoT stack . I ’ ve grouped the technologies and processes into four domains : Fog Computing , Cloud Computing , Big Data , and Business Value . Let ’ s start at the bottom .
Fog Computing
Fog computing , often referred to as edge computing , refers to the technologies and processes that occur outside of our clouds and datacenters , and are distributed across the user base . The user base can be made up of humans , machines , or objects with mobile devices , GPS , sensors , or other technologies that can store and process data at its source .
I covered this topic last year in an article entitled Forget Big Data – Small Data is Driving the Internet of Things . Small data refers to the data that is processed in the “ fog ” at the device level . Small data is often used to determine when the status or condition of an attribute changes . For example , when an application detects that a person has entered a location within five miles of a retail establishment , the application may push an offer or a message to that person ’ s device . A package containing perishable items may trigger an alert that the current temperature condition of the container is becoming too warm . A plant manager might get an alert from the assembly line that a part in the robotic machine is starting to fail and should be replaced before the entire machine is nonfunctional .
All these examples are applications that happen in the “ fog ” and do not ever need to transmit data back to a virtual or physical datacenter for processing .
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