The Edgy Advantage (Part 2)

Can our grocery store owner turn data into meaning?

The Edgy Advantage (Part 2)

Part 1 of The Edgy Advantage introduced us to a grocery store owner who wanted a more reliable way of monitoring a large number of refrigerators in her store. The problem was simple: if the temperature goes above a specific temperature threshold, she must take quick action or risk lost product (and perhaps a city financial penalty). Our owner used a simple IoT solution to help her employees more reliably stay on top of the situation.

Our owner has an opportunity: the power company wants to know if she will agree to their deal that would require her to drop power consumption by a certain percentage. In return, she would receive a large amount of credit in her account.

The opportunity sounds like a good deal, but our owner is worried that dropping the power consumption will cause her refrigerators to heat up past the safe threshold. The store owner knows that she has the necessary data: live temperature readings, and the power meter's live data (same format as the temperature data: watt readings every half minute).

Over the next week, our owner takes careful note of measurements from the power reader and temperature data. She tries experimenting with lower power consumption, noting the resulting temperature change. However, the number of variables that she must now account for is vast - for example, a more substantial amount of customers in the store means the more frequent opening of the refrigerator doors. It seems impossible to build a definitive trend to agree to the power company's offer. Our savvy owner goes home defeated.

However, before leaving for the evening, the owner happens to speak with a customer well versed in IoT. He tells her about an augmentation to her smart store setup that might help her: IoT Edge.

IoT Edge won't provide her with any more raw data; it will, however, take the live data streams as inputs into its modules. As data flows into the edge device, any modules deployed to it can run sophisticated programs against the data. Consider a simple example: one module might record each temperature data point that flows into the edge device and report the average temperature every 10 minutes (so, 20 data points). This aggregated data might be considered more meaningful to someone.

As time passes, individual temperature data points lose their value, but aggregated data can still provide value! Put another way: our owner probably won't care what the exact temperature of refrigerator #2 was at 1:34:30 PM on September 1st, 2019. However, our owner might care that on September 1st, 2019, the temperature trend over the day had a particular shape. This historical trend can be applied to another data set (perhaps a collection that represents the number of times customers opened the refrigerator door) backing a sophisticated analytics view.

Modules can manage an arbitrary number of data inputs, so writing a module that can map temperature data to power usage data should be trivial! However, as I stated in Part 1, IoT Edge relies on "IoT" - one does not replace the other, and the need for Edge only appeared after the power company presented our owner with an offer. To make the point clear - had the owner never been approached with the power company's deal, her existing "classic" IoT setup was perfect for what she needed.

Our owner, armed with new tech and ambition, is ready to take action! In Part 3, we will finalize our owner's story and provide her with the tools needed to give the power company a confident answer.

I am looking forward to it!