The Internet of Things Can Stop Food Waste In Our Supply Chains

Out of all the food you buy, how much of it goes to waste? Approximately 40 percent of all food in America gets wasted on the journey from farm to table alone.

Fixing this will not only require a new perspective on the problem but technological innovation as well. Fortunately, the Internet of Things (IoT) is up to the challenge.

An Impact That Can’t Be Ignored

That’s right—40 percent. It’s equivalent to you spending $100 on grocery shopping and throwing $40 worth of your purchases away as soon as you walk out of the supermarket. This issue has been going on for decades, and the repercussions are severe.

Food waste actually constitutes roughly eight percent of all greenhouse gas emissions in our atmosphere. “If food waste were a country, it would come in third after the United States and China in terms of impact on global warming,” says Chad Frischmann.

He’s Vice President of Project Drawdown, a team of researchers focused on figuring out how to cool down our planet and reduce greenhouse gases over the next 30 years. On their website, a reduction in food waste comes in at number 3 for top ways to reduce greenhouse emissions.

When measuring the true impact of food waste, it’s important to consider other factors as well. For example, all of the effort and resources that went into growing and producing that food is also wasted as a result. That adds up to thousands of gallons of water, hundreds of kilowatts, and countless hours of labor.

On top of this, in the United States alone, 40 million people struggle with hunger issues. That includes 12 million children. That’s roughly 1.5 times the population of New York City.

Keep in mind, this doesn’t even begin to touch upon the financial consequences that consumers and retailers ultimately have to deal with. But enough about disparaging facts; let’s get to the root of the problem.

Why Is So Much Food Getting Wasted?

Obviously, food gets wasted because it spoils prematurely. But it gets tricky when you start investigating the “why” and “when” of the problem. Many retailers erroneously that food spoils due to poor in-store handling. After all, it was the grocer who last handled the produce, right?

Well, it turns out the issue actually originates much earlier in the supply chain. In fact, it can even occur in the first 24 hours post-harvest. Incorrect temperature management substantially decreases the “freshness capacity” (maximum shelf-life) of produce. Thus, it’s the main cause of premature spoilage.

Freshness capacity is determined from numerous variables, such as harvesting conditions, processing, and, of course, the temperature of the product during distribution.

There are many factors to account for, so it’s not unusual for two groups of produce harvested from the same field on the same exact day to have a difference in freshness capacity of as much as five days. With that said, it becomes readily apparent that the issue is related to how we monitor the food during distribution.

The Status Quo

By now, you’re probably asking, “Why hasn’t this problem been tackled yet?” There are two main reasons. First, this largely believed to be unsolvable. As a result, it’s been accepted as an inherent cost of being in the business. This cost is then factored into pricing, which consumers and retailers pay. Second, the technology and tools in the industry have focused on identifying waste instead of preventing it.

This brings us back to that point about monitoring. Let’s go over an example. Say you have 30 pallets of apples in a refrigerated trailer. Usually, a USB data logger is placed at the back of this trailer to ensure the proper temperature is upheld during transit. If the logger records a deviation above what’s acceptable, your load of apples could get rejected. This means all 30 pallets go to waste when possibly only one pallet near the sensor actually went bad.

And that’s how produce is currently monitored. Not only is this inefficient, but it’s also unacceptable. One logger is not sufficient for an entire truckload of produce. We should be able to track each pallet. To solve this conundrum, we need automated data collection that scales. Enter IoT.

Doing the Impossible With IoT

Before, monitoring each pallet was seen as a manual, arduous, and costly task. But with recent developments in IoT, artificial intelligence (AI), and the cloud, real-time, detailed analytics and insights are not only possible—they can be automated as well.

IoT sensors in each pallet would allow us to observe the conditions of produce on a more granular level. From the moment they’re put in the pallet, they can start collecting information about temperature and time, providing a more accurate picture of the produce’s health.

And with installed readers at each step of the supply chain, this data could be automatically fed into a cloud-based analytics platform each time the produce passes through a different waypoint. From there, analytics could even give us a more precise prediction of when each pallet will expire. This would ensure that the retailer receives produce that is fresh for a minimum number of days.

This example of an IoT solution is extremely scalable and cost-effective; there would be no drastic changes to supply chain processes and no increased costs in labor. Besides all of this, it would also help solve every issue resulting from food waste. Thanks to innovation, what was once seen as an insurmountable problem can now be solved elegantly and efficiently.

What other big problems is the Internet of Things tackling? Let us know your thoughts on this solution to food waste and what you’d like to see covered in our next edition of IoT doing the impossible!