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Problem statement

Today we produce enough food to feed 10 billion people. However, the population is only 7,5 billion. At the same time, in some parts of the world, humanity experiences a high level of hunger. Our inability to feed the entirety of the world’s population is mostly due to food waste. One-third of all food produce ends up in a trash bin. Huge quantities of high-quality food end up in the bin for several reasons.

Among others, the main reasons are:

• Optical quality deficits
• Harvest surpluses
• Market disruptions e.g. COVID-19
• Supply chain disruptions e.g. container delays
• Reject in production processes

Small-scale food producers are hit harder due to insufficient use of resources globally. With the technological boom, farmers are still missing transparency in a supply chain caused by old-fashioned ways of working. One of the main issues is a lack of data about what fruits and vegetables have little shelf life remaining and which ones are already wasted. To perform quality control today farmers rely on their employees’ judgment and understanding of the quality of all sorts of produce within their facility. This approach requires a lot of time and effort while not guaranteeing an objective and up to date outcome.

Many times food is being wasted due to the wrong estimation of the shelf life caused by a lack of communication between farmers and traders. For the traders, it is crucial to be able to evaluate regularly the current amounts of stock and the time within which they have to sell it. Every day they receive tons of different products that have very different shelf life expectations. For the trader, it is hard to estimate when the product was harvested, how long it took for its transportation, and how long it can stay on a shelf taking into account all different factors like temperature, humidity, sunlight, and others. The main job of a trader is to sell all of the goods with little to preferably zero waste to avoid financial losses. Additionally, the traders are facing problems such as finding upcycling solutions for identified surplus, keeping transportation per produce as low as possible as well as having enough time to find new buyers. The trades who are committed to reducing food waste would be interested in ways of proving and promoting their sustainability efforts to retailers and end consumers.

Challenge

How can we help traders to improve quality control practices, predict surplus food early and sell their stock more efficiently by using image recognition when working towards reducing food waste instead of sending it as donation, discarding it in the biogas facility or dumpster?

Sub-questions

How can we help retailers to prove their claims of zero-waste supply chains by providing them a certificate when consumers want proof instead of CSR greenwashing?

• How can we help farmers and traders to make quick decisions about the quality of the food?
• How can we ensure transparency in the supply chain?
• How can we help traders to find buyers faster?
• How can we help traders and farmers to avoid financial losses because of unrealized sales/commissions?
• How to prevent the dumping of produce?

This challenge will influence farmers, traders, operators, retailers,transportation departments and the end customers.

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Criteria

• A solution should be a form of visualization of the crucial information for traders such as shelf estimation, quality of the product, expiration date, and other important information
• It should provide daily information based on image recognition, not real-time input using cameras
• Take into account the temperature of warehouses
• Logistic data should be transparent for traders
• A solution can be based on AI or other modern technology
• A solution should help to identify defects in a quicker and intuitive manner
• The solution can currently get insights on tomatoes and potatoes, with next point of interest - mangos
• Taking into consideration the AI training process of approx 1-3 months

The goals of the solution are to allow for a more efficient production and distribution and to provide transparency to retail clients, end customers and organizations.In the end, all people, either involved in the supply chain or at the end of it, should have access to good quality produce.

Sources for open data

• HDG - quality control company that can provide data to program the image recognition
• Data from traders, logistics, farmers?