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Extracting Elusive Value from the Embedded Cloud – A Consumer Perspective – Part 2

As we continue this blog series looking at the embedded cloud, I thought I would look at a few more typical household/consumer activities as a place where M2M could deliver value to many stakeholders. In this part 2 we look to food storage and preparation.

Food Storage: As food costs rise, there are many ways expenses can be cut with respect to food that is wasted due to spoilage after purchase. In many supermarkets, loyalty cards allow stores to track purchases in exchange for automatic discounts and other benefits. Some stores allow customers to use hand held scanners or even their own HMIs to scan items in the store. Items such as produce can be weighed and a bar-code label that represents the product is printed to be scanned.  If the store can track all this, there can be a system that would allow for this information to be used by the consumer too. In this way, methods could be developed where the consumer’s home inventory of products could be tracked. When an item is used, they would scan the empty container barcode with their HMI and it would be deducted from their inventory. This system could be further augmented if expiration dates were bar-coded. To initiate the integrated M2M inventory system, the consumer needs to go through their residence and scan the items they already own, enter the expiration dates, and purge the expired items as necessary. Appliances might eventually have M2M scanning and measurement features that make this process more automated and precise. 

Food Preparation/Cooking: This is where things come together literally and with respect to the M2M process. It could start where consumers scan all of the cookbooks they own. These would be augmented with the huge variety of recipes available on the web. Then, the process would look to the inventory of products in the home particularly emphasizing the ones that should be used sooner. How much time is available to cook and eat the meal? What is the capability of the person doing the cooking and the available appliances?  Are there dietary concerns? How many servings are needed and, perhaps most importantly, what do the people want to eat? Processing power from the Embedded Cloud could be leveraged to find an optimal set of menu options. Need to buy a few more things to complete the menu? A connected system could allow nearby suppliers to make offers – and even deliver them! Need instructions? Sponsored media sites could allow video/audio clips on the mobile device to provide the needed help. Perhaps the ideal recipe is in a cookbook you own; the system could tell you which book/page has the recipe it. This type of system would work well for a single meal planned on the spot but it could also be ideally suited for those that plan ahead. In this way, a weekly shopping list could be assembled.

A few last thoughts:

  • Based on the cloud data, local restaurants can determine menus that might attract more customers.
  • Automatically linking home food inventory through the cloud to store delivery services would be a logical next step.
  • Booksellers can encourage more cookbook sales in competition with the recipes available for free on the web.
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