International Research Journal of Engineering and Technology (IRJET) Volume: 10 Issue: 04 | Apr 2023
www.irjet.net
e-ISSN: 2395-0056 p-ISSN: 2395-0072
Sehat Co. - A Smart Food Recommendation System Shubham Mishra1, Aniket Pawar2, Jayesh Shadi3, Lifna CS4 1,2,3,4Computer Department, Vivekanand Education Society’s Institute of Technology, Chembur, Mumbai.
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Abstract- Amidst Covid-19, nutrition has become a very important aspect of everyone's life since the major factor in helping us prevent this deadly virus is a person's own immunity. In addition, picturing food has become a major hobby now-a-day. Social media comes with a huge amount of food images posted each day. Most people will not be able to identify food, and to determine it directly will be very difficult. The system proposed helps to not only help to track the food details but also eliminate the chance of eating ingredients which are poor against covid. As a result, it uses image processing techniques to extract features and convolutional neural networks that can distinguish and label different features in the image, and then provide a cooking environment. Recipe1M provides the largest open access to recipe data, allowing high-quality models to be trained in targeted, multimodal data. In addition, by adding a high-level separation process, we show that doing so enhances the return of full functionality to humanity while enabling semantic vector calculations. The ingredients predicted then are matched with our sophisticated Covid-dataset which contains ingredients useful for fighting against covid and accordingly stats for a recipe are displayed with recipe recommendation as well with the same set of predicted ingredients.
Keywords—Food
recommendation system, Diet, Recipe1M, Image processing, Nutrition, Health, Covid, Corona, Ingredient’s prediction, Food against covid.
INTRODUCTION
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Impact Factor value: 8.226
Huge data is being added to the internet every day and is made accessible for various educational as well as commercial purposes and with this we have a better chance of developing complex recommendation models which not only take into account user interests but also other factors like molecule interaction in foods, disease or virus or bacteria resistant qualities, etc. This would enable the user to make more informed choices while purchasing or making his subsequent meal. The website, “Sehat Co.” would exhibit detailed information on exactly where and how we fall in to fix the problem and bring awareness to the users visiting our platform. The user would be able to upload their daily food images and our system would then predict the ingredients with the recipe as well for the food image along with another recipe recommendation. Besides that, there would be test images to help users try our platform and see for himself/herself how it works.
LACUNAS IN THE CURRENT SYSTEM
There are numerous aspects that have been identified as having an impact on an individual's health. Physical activity, sleep, nutrition, inheritance, and pollution are only a few examples of external variables. Considering that eating is one of the most adjustable aspects of our life, it's no surprise that minor differences can have large consequences. Because our food has a deep connection in its culture, we can spin around every sector to recognize food that surrounds them. The very common elements in an area are closely linked to local factors such as climate. This has a significant impact on the supply of ingredients used in local cooking.
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Some chemicals have been shown to have a beneficial influence on health, specifically in the fight against Covid. Knowing which compounds have the highest amounts could aid in the treatment and prevention of the virus. Furthermore, by incorporating these products into delectable and economical meals, the population's dietary habits may be influenced. In a society where the consumption of fast food is on the rise, it's evident that, in addition to the two prior reasons, time in preparation is a key component.
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A) Non-existent automated models: The lack of a platform that can dynamically display the covid metrics for ingredients is a fundamental flaw in today's systems. The existing systems can just anticipate ingredients and display a recipe based on that prediction, with no participation of the covid beating factor whatsoever. B) Proprietary existing systems: The second issue is the availability of proprietary systems which means most of the companies develop these systems as a business product rather than a platform that helps everyone.
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