Foodzy @ Quantified Self Meetup Amsterdam #6
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The presentation that I gave during the Quantified Self Meetup in Amsterdam on November 19th, 2012. For more info and a detailed transcript, check http://www.okgo.nl
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Foodzy @ Quantified Self Meetup Amsterdam #6
- 10. 6.694.073 bits
- 13. break down
- 15. break down calories consumed calories burned
- 16. break down calories consumed calories burned weight statistics
- 17. break down calories consumed calories burned weight statistics real-time dashboards
- 20. 100.000 liter
- 22. 100.000 liter 35.000 liter 14.000 liter
- 29. +
- 30. +
- 31. + 30%
- 42. Thanks.
Editor's Notes
- \n
- In the next few years, obesity will become one of the world's biggest health issues with diabetes cases doubling each year, all over the world. It's not just the American culture anymore, if you might think so. South-America, Asia and all over Europe we see a massive negative shift in food culture. Making obesity the number one slow-sniper on a global base.\n
- Looking back in history, we are on a logical point in the evolution of the machine that is our body. Over the past 100 years, we've over-innovated our food culture to match a need that is thought to be necessary.\n
- While the first automobiles took the streets at the end of the 1800's, it wasn't until the second decade of the 20th century that a speedometer became a default tool for every automobile. The reason why they were needed was obvious: the technology had improved drastically, making driving a car an activity that no longer was to be done using common sense. People needed some extra tools to control the machine. And since Otto Schulze made the speedometer easy to implement on low costs\n
- it soon became a essential part of driving an automobile and, later on, motorcycles and mopeds.\nWe are at exactly that point in time when looking at our eating habits. We've been shifting our food culture to a point where getting a grip on your eating pattern or habits can no longer be done using common sense by everyone. Yet we decide to control the greatest machine we ever own based on feeling over facts. On the other hand, in the last 5 years, we've slowly transformed in the real life cyborgs.\n\n
- Not this guy\n
- more like them\n
- My name is Johan Voets and I'm the co-founder of a company that works with little big data. Bite size data, actually!Foodzy is your personal food journal. With the apps for iPhone and Android and the website www.foodzy.com, you are able to keep track of everything you eat and drink. We turn this into a live activity stream and real time dashboards to show you how your day looked, and where you could do better.\n
- Named as Amsterdam's hottest startup in Wired's yearly overview, \n
- Our users gobbled up an impressive 6.6 million bits or 133 million calories in little over a year.\n
- Of course, intake is just one part of the equation, so that's why we've launched a Fitbit integration a little while back to give you a realtime overview of bits versus burned. We're using the same algorithm as Fitbit to calculate your average burn in case you don't own a fitbit, by the way.\n
- so at the end of the day, Foodzy gives you a complete breakdown of your food intake, it shows you calories consumed versus calories burned and the effect it has on your weight. All nicely designed real-time dashboards. \n
- so at the end of the day, Foodzy gives you a complete breakdown of your food intake, it shows you calories consumed versus calories burned and the effect it has on your weight. All nicely designed real-time dashboards. \n
- so at the end of the day, Foodzy gives you a complete breakdown of your food intake, it shows you calories consumed versus calories burned and the effect it has on your weight. All nicely designed real-time dashboards. \n
- so at the end of the day, Foodzy gives you a complete breakdown of your food intake, it shows you calories consumed versus calories burned and the effect it has on your weight. All nicely designed real-time dashboards. \n
- \n
- It gives us a really nice chance to analyze big chunks of data, like this:\nWe can deduct that if our users have had a 100.000 liters of drinks, about 35K of that is water. And 14K is alcohol. Cheers!\n\n
- It gives us a really nice chance to analyze big chunks of data, like this:\nWe can deduct that if our users have had a 100.000 liters of drinks, about 35K of that is water. And 14K is alcohol. Cheers!\n\n
- It gives us a really nice chance to analyze big chunks of data, like this:\nWe can deduct that if our users have had a 100.000 liters of drinks, about 35K of that is water. And 14K is alcohol. Cheers!\n\n
- This stuff really gets interesting if you zoom in a little bit. If you look at this stuff from a personal level, you'll bump into some pretty fascinating stuff. Looking at a snapshot of an average week of my data, I noticed something peculiar:\nYou see  that odd jump on friday? It surprised me, also looking at the fact that my checkins are lower. Investigating it further, it hit me:\n\n
- Hitting the pub after work on friday usually leads to skipping dinner, but those beers pack some bits!\nThis got me thinking: exactly how does all the food I eat relate to each other, what does my foodprint actually look like. \nAnd this is why I love to call it little big data: \n
- this is a networked graph of the food I had in the past year and which food I had it with on the same day as well. So, the nodes represent food, size the amount of times I had it and the edges linking nodes represent the amount of times I had them together.\n\n
- Zooming in a little bit: this tells me that if I have a glass of water, I'm most likely to have an espresso of lungo as well. \n
- In the end, coming full circle, I needed to know just one thing: how big was the chance that I would fall for the traditional dutch pub-combo?.\nThat's not that good. ;)\n\n
- In the end, coming full circle, I needed to know just one thing: how big was the chance that I would fall for the traditional dutch pub-combo?.\nThat's not that good. ;)\n\n
- In the end, coming full circle, I needed to know just one thing: how big was the chance that I would fall for the traditional dutch pub-combo?.\nThat's not that good. ;)\n\n
- In the end, coming full circle, I needed to know just one thing: how big was the chance that I would fall for the traditional dutch pub-combo?.\nThat's not that good. ;)\n\n
- I guess for me the most obvious next step would be for us to enable people to set alerts for themselves: give me a warning each time I check in a certain product: "Enjoy a beer or two, but skip the balls dude". And since getting healthy can be a group process as well, peer pressure could be generated by alerting your mates that you just checked in a second stroopwafel! \n
- Where do possibilities stop? I’m a runner myself, mostly in the morning, so it would be fascinating to cross-reference my running data with my caloric activity and weight stats to see how my activities stack up there.\n
- Or what about that late night snack? That glass of milk before bed or those crisps you had while watching the match, how do they influence my sleeping pattern? \n
- \n
- Imagine Foodzy cross-referencing your Foursquare check-in with your last checkin there, the nutritional value of the meal you had, the average of your consumption for the next day (or the rest of the day) based on your history and your weight stats and eventually advising the best possible choice on the menu.\n
- Imagine Foodzy cross-referencing your Foursquare check-in with your last checkin there, the nutritional value of the meal you had, the average of your consumption for the next day (or the rest of the day) based on your history and your weight stats and eventually advising the best possible choice on the menu.\n
- Imagine Foodzy cross-referencing your Foursquare check-in with your last checkin there, the nutritional value of the meal you had, the average of your consumption for the next day (or the rest of the day) based on your history and your weight stats and eventually advising the best possible choice on the menu.\n
- Imagine Foodzy cross-referencing your Foursquare check-in with your last checkin there, the nutritional value of the meal you had, the average of your consumption for the next day (or the rest of the day) based on your history and your weight stats and eventually advising the best possible choice on the menu.\n
- But even a more proactive approach could be a possibility. Connecting your doctor or dietician to your profile, you could create a personalized menu with daily nutritional goals. With each checkin you would be updates with your scores in each area of the menu and Foodzy could create a complete week menu based on your own recipes, automatically varying with it based on your consumption through the day or week. Based on your personal needs and habits the platform could even help you discover new recipes and food groups. \n
- At Foodzy we don't believe that getting healthy is about extreme exercise or crash dieting. We don't even think it's about avoiding fast food or never eating another cupcake or donut again.\nWe do believe that the first step to a healthy lifestyle is getting insight in what your lifestyle currently embodies. \nWhen it comes to your body, it's time to start making changes based on insights, not just intuition.\nThank you.\n\n