An iSpace-based Dietary Advisor

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Abstract
With the prevalence of smart homes, systems that realize the Ambient Assisted Living paradigm are getting increasingly common. This paper presents an AAL application that aims to assist its users with a sedentary Iifestyle improving their health by suggesting gradual changes in their diet that align with their personal tastes, and by warning them if they had not taken a break from sitting by their computer or workstation for a given period of time. The former is a high complexity optimization problem, as the task is to achieve a diet in the long term that balances the daily intake of dozens of important nutrients, while making sure that the changes align with the personal taste and dietary restrictions (e.g., celiac disease) of the user.

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