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Big Data in the Food Industry

Add numbers to food, yummy, delicious or precise?

· data scientist,Industry,cognitive

The big data revolution has led to multiple advancements in a variety of industries. One of the many areas it has had an effect on is the food industry. Technologies such as IoT, Big Data Analytics and Crowdsourcing have all contributed and revolutionized how the food industry functions today.

IBM Watson is capable of helping many industries in a variety of ways. For restaurants, it is able to generate original recipes that are unusual but delicious. It is a fantastic tool for chefs to create new, out of the box ideas for their menu.

What does a chef need to do on Big Data?

A chef has to set out some parameters for the type of recipe he or she wants to create. For example, selecting a regional cuisine, a particular ingredient or type of dish. IBM Watson will review its massive database that includes compounds and molecules, relationships of certain ingredients, and preferences with flavors. Once all this information is combined, the program will then begin to generate ideas based on the newly discovered information and preset parameters. The recipe is then presented to the chef who will then be able to experiment in the kitchen. The food industry has also been able to improve its efficiency in different areas – resulting in reduced spending. A real-life example would be McDonalds. McDonalds has resorted to trend-analytics to help it understand what individual restaurants are doing differently and how these decisions make an impact. With this new perspective of information, the decision-makers can now understand what works and what doesn’t. Clearer decisions can now be made to save money.

With the help of big data analytics, fast-food chains are looking to improve customer drive-through experiences. By obtaining information about the timings and type of food that people are ordering, fast-food chains are able to better prepare themselves for a more efficient drive through experience.

Something about precision agriculture...

Precision agriculture uses IoT sensors to monitor different variable like moisture, pH and nitrogen levels. With this information, farmers will be able to make better decisions on how to look after their crops. For example, approximately 90% of a farm’s yield is lost due to weather-related damage. By implementing precision agriculture, weather-related crop damage can be reduced by 25%. Accurate forecasts can predict upcoming weather assisting farmer to make better decisions on when to schedule fertilizing the crop. Precision agriculture also benefits the environment by conserving water. Water will only be used on the crops that require it or if dry weather is predicted.

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