Nutrition Monitoring and Calorie Estimation using Internet of Things (IoT)

Abstract

Diet observation is one of the principal aspect in precautionary health care that aims to cut back varied health risks. The various recent advancements in smartphone and wearable sensing element technologies have paved way to a proliferation of food observation applications that are based on automated image processing and intake detection, with an aim to beat drawbacks of the standard manual food journaling that's time overwhelming, inaccurate, underreporting, and low adherent. The currently developed food logging methods are very much time consuming and inconvenient that limits their effectiveness. The proposed work presents an Internet of Things (IoT) based mobile-controlled calorie estimation system to make technical advancements in healthcare industry. The proposed system operates on mobile environment, which allow the user to acquire the food image and quantify the calorie intake mechanically. The Mqtt protocol based MyMqtt broker is used to connect the application and the edge device and also to store the data in the Thingspeak cloud. A deep convolutional network is employed to classify the food accurately within the system. The volume estimation is done using sensors and the calorie approximation is done using formula.