NutriNet – a personal assistant for your grocery shopping

18

October

2024

No ratings yet.

Have you ever taken hours browsing around supermarkets searching for the most nutritious food options? Did it take you too much time figuring out which recipes to cook best, with the groceries you bought? Struggles when dealing with food are numerous, starting from choosing products with appropriate nutrients simply not knowing enough recipes.

Therefore, we introduce NutriNet – a mobile application that is going to make shopping and meal planning easier!

• Grocery shopping & meal planning simplification:

NutriNet simplifies grocery shopping and meal planning, by analyzing which products and recipes fit the users’ desired grocery item wishes, nutrition values and store preferences best. NutriNet aims to address the challenges being implicit to personalized nutrition and helps consumers make healthier food choices by simplifying the grocery shopping and meal planning process. This shall be done by eliminating the need to perfectly understand all nutrition values or to search for numerous recipes. NutriNet completes all these tasks for you in real-time and provides clear and accessible recommendations for you.

• Real-time personal assitant: NutriNet acts as a multifunctional application providing value to consumers by solving various food related problems in real-time. Appearing as a chatbot, it is aimed at taking general grocery shopping lists or meal wishes as input query, combined with preferences for food characteristics (e.g., nutrients, allergies) and grocery stores. It then provides brand specific and personalized grocery shopping lists, as well as meal recommendations, if so desired. Moreover, grocery items can also be added into the initial grocery shopping list query, by scanning them with the integrated AR tool. The product will then be detected visually and thus will be integrated into the shopping list input query.

• Long-term customer engagement: NutriNet distinguishes from competition by providing personalized and customized advice. This is possible, as NutriNet consists of a database, having incorporated stock and product information of the major supermarkets in the Netherlands. In contrast, classic applications, which try to meet similar needs (e.g., meal recommendation) rather focus on counting nutrients for the purpose of short-term weight loss, instead of personalizing grocery shopping lists and meal recommendation to enable a healthier lifestyle for users. Those applications are usable on short term but are proven to have low adherence over the time (Chen et al., 2015).

• Personalized recommendations: NutriNet leverages generative AI to offer accurately personalized recommendations. Users can simply enter their preferences, while prompting a grocery list or a meal, such as gluten-free or high in protein, and the generative AI powered application will provide accurately personalized results.
However, personalization and raising awareness for healthy foods are not the only purposes of NutriNet. It also addresses sustainability issues that supermarkets are facing. By gathering consumer purchase and search data in the application, consulting services can be offered to supermarkets, enabling them to plan ordering and stockholding processes more efficient. Hence, supermarkets should be able to reduce food waste due to overstocking on long-term.

NutriNet offers a 2-sided network platform, yielding important value to both, consumers as well as supermarkets.

Contributors

574051 – Duong Dao
728070 – David Wurzer
738898 – David Do
562387 – Roxi Ni

References

Chen, J., Berkman, W., Bardouh, M., Ng, C. Y. K., & Allman-Farinelli, M. (2019). The use of a food logging app in the naturalistic setting fails to provide accurate measurements of nutrients and poses usability challenges. Nutrition, 57, 208-216.

Please rate this

Grab and Go stores, but then literally

20

September

2021

5/5 (1)
Author: Jesper Goudswaard, 20/09/2021

Nowadays, almost every major supermarket chain offers the opportunity to pay at self-service checkouts.  Self-service checkouts use less space than registers, have reduced wait times compared to cashier lanes, and need fewer staff members to be controlled. A downside is an increase in shoplifting (Schmidt-Jacobsen, n.d.). Unfortunately, there is no alternative that offers at least the same convenience with almost zero shoplifting.. or is there?

You may have heard of it already, but Amazon has already opened 28 stores with so-called ‘Just walk out’ technology (Statista, 2021). They are called Amazon Go or Amazon Go Grocery stores. By scanning a QR code in the Amazon app on your phone, you get access to the store. Whenever you take an item from the shelf, the app automatically adds the item to your virtual shopping cart. When the customer changes their mind and puts the item back, the app will update the virtual shopping cart automatically. After you have gathered all the desired products, you can just leave the store and you will be billed for the products that you have taken via the app (Cheng, 2019).

So, how does this ‘Just walk out’ technology work? Amazon is using a combination of deep learning, computer vision, and sensor fusion. To get a better understanding of these technologies, I will explain each technology briefly. Deep learning is the creation of machines that use techniques inspired by the human brain’s ability to learn (Mandal, Mehta & Mishra, 2017). It is used to recognize objects, in Amazon’s occasion customers and products. However, just deep learning alone will not recognize anything that happens in the store. That is when computer vision comes into play. It mimics the human vision to look, discover, and method images (Mandal et al., 2017). This is done with the help of hundreds of sensors in the store that register every movement. Sensor fusion is the technology that tracks the movement of customers when cameras cannot register the movement, for example, because the visual input is blocked by another customer. This is done by the combination of accelerometers and gyroscopes in the customer’s mobile phone that together registers the location (Mandal et al., 2017). This technology is so accurate that shoplifting is almost impossible. Apart from that, even when a customer puts an item back on the wrong shelf, the technology will register that action and the customer will not be charged for that product (Cheng, 2019).

However, as disruptive as this concept might look, Amazon has not yet reached the 3000 stores they intended to have by 2021 (Statt, 2018). One possible explanation is the costs of the technology. According to Focal Systems (2019), the system will not prove a break-even in a large-format grocery store compared to operating the front-end with cashiers until after 2040. For now, Amazon should therefore stick with smaller stores.

What do you think about the technology and do you think we will see this much more often in the near future? Let me know in the comments.

References: https://www.researchgate.net/publication/315380585_JUST_WALK_OUT_TECHNOLOGY

https://www.theverge.com/2018/9/19/17880530/amazon-go-cashier-less-stores-new-locations-2021

https://sprintingretail.com/blog/retail-self-checkout-systems/

https://www.forbes.com/sites/andriacheng/2019/01/13/why-amazon-go-may-soon-change-the-way-we-want-to-shop/?sh=7e652bb56709

https://www.pocket-lint.com/gadgets/news/amazon/139650-what-is-amazon-go-where-is-it-and-how-does-it-work

https://www.statista.com/statistics/1155873/amazon-store-openings-number/

Please rate this

Digital Transformaton Project – self-driving carts

14

October

2016

No ratings yet. Chris Anderson argues in his book on the Long Tail that there are retail scientists who are dreaming of smart shopping carts which can detect content in the carts by their RFID tags, and consequently give the customer recommendations of products that fit next to the products in the cart (Anderson, 2009). This means that one could have cheese in his cart, and through recognition, the cart would recommend certain bread that fits with the cheese. After this, Anderson mentions that “even these scientists still can’t transport matter into reach and make acting on those recommendations easy. In the physical world, shoppers move; products don’t.” (Anderson, 2009). This is exactly the point where Chris Anderson could be wrong, and where modern day scientists could be right, by designing a self-driving shopping cart. Even though the products won’t fly into one’s cart literally, the cart brings itself toward the products, leasing little to the imagination of the customer. The self-driving shopping cart is the emerging technology which will be discussed further in this report. The company which is the subject of the report is Albert Heijn. Albert Heijn is a supermarket which was founded in 1895 and currently has over 850 branches spread in the Netherlands. (AH, 2016)

Emerging technology of self-driving cart

The concept of self-driving (shopping) carts is a concept that could potentially change the whole way of shopping. With the Internet of Things growing and the expectation of over 50 billion things being connected in 2020 (Hbr, 2016), it becomes clear that self-driving carts fit right into the future. It is an emerging technology for which Wal-Mart has filed a patent in March of 2016 (Atherton, 2016). The shopping-carts will contain a robotic device under the cart and this will cause it to drive in the way the customer wants. Additionally, the entire system will work in a “sensor-rich world, where central computers track inventory and match customer needs to what’s available in the store for the shopper” as Atherton also mentions. Also, the carts will be able to bring themselves back, after being left by customers in, for example, the garage. This causes the employees to have more time to spend on other duties, instead of assembling carts. The concept of self-driving carts resembles online shopping, in a way that one is working with a digital device. However, with a physical purchase, its advantage being an immediate purchase instead of waiting for shipping, it might even win more ground over online shopping (in the supermarket industry) (Atherton, 2016). As more and more customers are switching to online shopping, retail stores are probably looking for way to nevertheless attract these customers (Mintel, 2016).

Customer Experience

Customer experience is an important aspect of shopping, and it is very likely that it is easier to gain a positive customer experience in a traditional brick-and-mortar store than online. It is true that online shopping may have a larger inventory and more possibilities, however it loses on the aspect of instant gratification. Also, doing the groceries with a few clicks on one’s keyboard will never top the physical experience of strolling through the supermarket with one’s family. It is important to realize that this concept of self-shopping carts has many possibilities, such as a screen being connected to the cart, with enables the customer to, for example, browse through available products or a see a map. However, it would probably be easier, and cost effective, to let an application on a smart-phone control the carts. The implementation of this concept of self-driving carts could cause Albert Heijn to stay ahead of its competitors, and this is ultimately what also causes them to have a first-mover advantage in the Netherlands with the introduction of this technology.

 

Group 5

 

References

AH (2016) Alles over Albert Heijn Retrieved from: http://www.ah.nl/over-ah

Anderson, C. (2006) The Long Tail: Why the Future of Business is Selling Less of More. New York City, N.Y.: Hyperion.

Atherton K., (2016), Walmart patents robot carts for better shopping. Can robot carts compete with Amazon? Retrieved from: http://www.popsci.com/walmart-patents-robot-carts-for-better-shopping

Harvard Business Review (2016) To Predict the Trajectory of the Internet of Things, Look to the Software Industry. Retrieved from: https://hbr.org/2016/02/to-predict-the-trajectory-of-the-internet-of-things-look-to-the-software-industry

IMAgency (2016) Albert Heijn. Retrieved from: http://imagency.com/work/albert-heijn/

Mintel (2016) 29% of UK online grocery shoppers are shopping for groceries more online now than a year ago. Retrieved from: http://www.mintel.com/press-centre/retail-press-centre/29-of-uk-online-grocery-shoppers-are-shopping-for-groceries-more-online-now-than-a-year-ago

Please rate this