Smart-Log: A Deep-Learning Based Automated Nutrition Monitoring System in the IoT

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Aim:

The main aim of this project is to propose automated monitoring of the nutritional content of food provided to infants, not only at home but also in daycare facilities, is essential for their healthy development.

Existing System:

Balance of nutrient intake is very important, particularly in infants. When the body is deprived of essential nutrients, it can lead to serious disease and organ deterioration which can cause serious health issues in adulthood. This condition can be caused by both undernourishment, in which not sufficient nutrients are consumed, as well as overeating, which results in excessive consumption of non-nutrient rich food, particularly in fats and salt. Overeating can lead to obesity which is a serious health concern in affluent societies today. Imbalance nutrition in infants and children can manifest in numerous modalities in adulthood including weak immune systems, cognitive disorders, weakened skeletal structure, thinning hairlines and bleeding gums, to mention just a few.

Proposed System:

The proposed Smart-Log system, which can be part of any household, is presented. The primary enabler for this research is the Internet of Things (IoT). The IoT is used as the link between sensor-derived data and cloud-based analytics. The IoT is a network of physical devices where each device is recognizable within the network. Each recognizable component in the IoT is a “thing” which can connect to the Internet. With the IoT covering a wide range of the business spectrum, it has helped researchers and developers to make intelligent systems. The IoT is also the enabling technology of smart cities where diverse infrastructure components (e.g., vehicles, services, hospitals, traffic, buildings, and homes) are interconnected. In the context of health care, the IoT has enabled remote assistance and has enriched people’s quality of life.