  An important aspect of health monitoring is effective logging of food
consumption. This can help management of diet-related diseases like obesity,
diabetes, and even cardiovascular diseases. Moreover, food logging can help
fitness enthusiasts, and people who wanting to achieve a target weight.
However, food-logging is cumbersome, and requires not only taking additional
effort to note down the food item consumed regularly, but also sufficient
knowledge of the food item consumed (which is difficult due to the availability
of a wide variety of cuisines). With increasing reliance on smart devices, we
exploit the convenience offered through the use of smart phones and propose a
smart-food logging system: FoodAI, which offers state-of-the-art deep-learning
based image recognition capabilities. FoodAI has been developed in Singapore
and is particularly focused on food items commonly consumed in Singapore.
FoodAI models were trained on a corpus of 400,000 food images from 756
different classes. In this paper we present extensive analysis and insights
into the development of this system. FoodAI has been deployed as an API service
and is one of the components powering Healthy 365, a mobile app developed by
Singapore's Heath Promotion Board. We have over 100 registered organizations
(universities, companies, start-ups) subscribing to this service and actively
receive several API requests a day. FoodAI has made food logging convenient,
aiding smart consumption and a healthy lifestyle.
