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IoT From Connected to Getting Smart | @ThingsExpo #BigData #IoT #M2M
The end point for many IoT initiatives is to create ‘smart’ entities – smart cities, smart cars, smart schools, etc.
By: William Schmarzo
Aug. 27, 2016 12:45 PM
Internet of Things: Getting from Connected to Smart
I wanted to gather all of my Internet of Things (IOT) blogs into a single blog (that I could later use with my University of San Francisco (USF) Big Data “MBA” course). However as I started to pull these blogs together, I realized that my IOT discussion lacked a vision; it lacked an end point towards which an organization could drive their IOT envisioning, proof of value, app dev, data engineering and data science efforts. And I think that the IOT end point is really quite simple…
Creating “Smart” Entities
Creating a “smart” entity is an outcome of optimizing the decisions and business initiatives that support an entity’s business and operational objectives
Yes, I think creating “smart” is as simple as that. But before I go any further, let me define some terms and a process that I am going to use throughout this blog (and likely in the forthcoming IOT and “smart” blog series):
Maybe the easiest way to understand the “smart” concept is with an example. For example, creating a “smart” city starts by first understanding the city’s business and operational objectives, which could include citizen quality of life, proactive business development, promoting tourism, top-quality schools and community safety. Next we need to identify the city’s 9 to 12 month business initiatives. One of the city’s business initiatives could be “improving traffic flow.” The decisions (or clusters of decisions) necessary to support the “improve traffic flow” business initiative could include (see Figure 1):
Note: decisions tend to cluster around common objectives or “themes.” We call these “clusters of decisions” around a common objective use cases.
Getting Smart Exercise
The results were very impressive. The students came up with a load of different business initiatives (and associated clusters of decisions) that a “smart” university would need to cover (see Figure 1).
Figure 1: Sample of Business Initiatives and Supporting Decisions
We consolidated the key business initiatives across the different teams and came up with the list in Figure 2.
Figure 2: Creating a “Smart” University of San Francisco
By applying advanced analytics (yielding predictive and prescriptive insights) to the growing wealth of internal and external data sources, organizations can make better decisions and enhance the success of the organization’s key business initiatives. Ultimately, this is what helps the university become smarter.
BTW, Don’t Forget the Human Component of IoT
Most of the decisions that we are trying to optimize to create a smart operating entity involve humans. We’re not trying to create Skynet. We’re trying to make the humans that are involved in the operations more effective with respect to the decisions that they need to make in support of their business initiatives.
1. Skynet is from the Terminator movies. Skynet is a highly advanced, artificial intelligence system that saw humanity as a threat to its existence and triggered a nuclear holocaust and an army of Terminators against humanity. Not a good situation.
The post Internet of Things: Getting From Connected To Smart appeared first on InFocus.
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