Tescore

Tescore

Team name / Company name: 42 London
Team leader: Fred Charbonnier
Challenge: no. 4: EcoEats
Problem: People tend to struggle when it comes to choosing a healthy next snack, meal, or weekly shop. The only information the customer has to aid them is a very unattractive nutrition facts label. Reading them takes time, effort and is ultimately not a sustainable solution to picking healthy options. Current diet loggers and trackers are inconvenient and require vast amounts of manual input from the user which in many cases leads to people dropping them and giving up on their diet goals.
Solution: Our proposed software offers an easy and readily available tech solution through the use of text / image recognition combined with an algorithm which uses data from TESCOs health rating system in combination with users dietary goals / needs. It lets customers point their phone at the shelf from which they’d like to choose something and provides them with an overall score according to how healthy the item is and how compatible it is with their diet.
Impact: With a new easy access way to manage people's diet with positive connotations, the amount of “healthy foods” TESCO can provide and sell will increase dramatically and potentially exceed their 53% by 2027 goal. It is simple and intuitive and will have a massive impact just through the accessibility alone. A person's diet is one of the most dictating factors when it comes to their overall physical and mental health. If we can aid people in the foundations of their health the rest will follow.
Feasibility: Text recognition is already prevalent in everyday life. Big conglomerates already offer it as a service, it just needs to be utilised in the correct way. The unique names of items make it possible to identify every item in a TESCO store in this way. iOS already includes text recognition in their vision kit so there is no need to develop this further on this OS. The algorithm is the only other part of our software aside from a simple profile and can be fine tuned to provide correct results.
What you built: A basic iPhone Augmented Reality app which can render a three dimensional score next to the product in the scene. https://github.com/SimpleLuke/FoodScannerAR
What you had before: A dream.
What comes next: We would like to further develop the algorithm and product in order to roll out Tescore into every TESCO worldwide and make it accessible to every customer with a smartphone (95%+). We'd love to help TESCO achieve their healthy food offerings goal before their proposed year of 2027 and we believe it is very possible with this solution. Moreover we’d like it to be a viable alternative to diet loggers by implementing a system of our own where users can log items by tapping the object on screen.
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