It's crucial to balance your nutrient intake, especially for young children. Lack of vital nutrients in the body can result in major illness and organ degradation, which can have a major impact on an adult's health. For the sake of the infants' healthy growth, automated food content monitoring is necessary both at home and at childcare facilities. In order to meet this challenge, this article introduces Smart-Log, a novel fully automated nutrition monitoring system based on the Internet of Things (IoT) that will push the boundaries of smart healthcare. This research presents an accurate meal prediction method based on Bayesian Network and a unique 5-layer perceptron neural network for the Smart-Log implementation. A smartphone application that gathers nutritional information about food ingredients and WiFi-enabled sensors for food nutrition quantification make up the Smart-Log prototype, a consumer electronics product. An open IoT platform is used by the Smart-Log prototype for data analytics and storage. Based on 8172 food items for 1000 meals, the experimental findings demonstrate that Smart-Log has a 98.6% prediction accuracy.