Mobile cloud based system recognizing nutrition and freshness of food image

As people across the globe are becoming more interested in watching their weight, eating healthier and avoiding obesity, a system that can measure calories and nutrition in every day meals can be very useful. As well as mobile-based applications have become ubiquitous in numerous aspects of people's lives over the past few years. Harnessing the capability of this trend for healthcare purposes has become a focal point for researchers and industry, in specific designing applications that can be utilized by patients as a major aspect of their wellness, prevention, or treatment process. Along the way, mobile cloud computing (MCC) has been introduced to be a potential paradigm for mobile health services to overcome the interoperability issues over distinctive information formats. In this paper, we propose a mobile cloud-based food calorie measurement framework. Our framework provides clients with advantageous and intelligent mechanisms that permit them to track their food intake and monitor their calorie count. The food recognition technique in our system uses Naive Bayes training mechanism in a cloud computing environment with classifier machine learning. Also this system checks the freshness of the fruit, by using the image processing techniques. This system improves the accuracy of calories consumption measurement process.