# Self-Care IoT Platform for Diabetic Mellitus
## 2 The Proposed Self-Care IoT Platform for Diabetics
### Automatic Recording of Food Taken Information  
Everyone has a glucose level rise after they eat. Then, the glucose level gradually drops to the normal range as time passes. However, people with diabetes change their glucose levels out of the normal range and maintain a high level over time. For example, when a diabetic patient overeats, the BG level rises significantly, and the level does not fall easily and stays at a high-level. Adherence to dietary recommendations is the most critical part of diabetes self-management. Having a healthy and balanced diet helps in BG levels within the target range. Thus, it is essential to know what the patients eat, how much they eat, and adequately control the glucose level. Nonetheless, most patients fail to comply because of the lack of motivation, difficulty in changing dietary habits, and poor understanding of the direct impact nutritional choices have on glycemic control [24; 25; 26]. Each person has a different favorite food and eating habits. Also, the effect of diets on blood glucose is different for each patient. Thus, it is to accurately analyze the impact of meals on glucose level for each individual. First of all, patients should accumulate individual pre- and post-meal BG levels with associated meal information. This record can then be used to analyze personal eating habits and their effects on blood glucose. The conventional method to record the meal information is to self-report approaches, such as electronic questionnaires, databases, and diaries [24]. The data is transferred to a mobile device. It provides real-time feedback concerning dietary patterns, caloric intake, and nutrient distribution [27; 28]. However, this self-reporting places the patient's burden to remember the contents and portions of the food consumed. Therefore, it has the fundamental disadvantage that it is less accurate. We implemented a smart food tray, shown in Figure 4, to ensure that patients obtain the type and amount of food they eat each time they eat automatically. The plate and \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Packet Index** & **Patient ID** & **Length of Data** & **Date** \\ \hline Start time & Calories & Distance & Average speed \\  & & for 1 st min & for 1 st min \\ \hline Heart-rate & Distance & Average speed & Heart-rate \\   for 1 st min & for 2 nd min & for 2 nd min \\ \hline... &... &... &... \\ \hline Distance & Average speed & Heart-rate \\   for i-th min & for i-th min & for i-th min \\ \hline Average speed & Total exercise time & Total distance & End of Data Packet \\ \hline \hline \end{tabular}
\end{table} 
Table 4: A data packet format for the proposed IoT health DAQ device. blood glucose meter automatically record pre-and post-meal BG levels and accurate meal information, as shown in Table 5. By analyzing cumulative meals and blood glucose readings, patients can quickly determine which foods help blood glucose and vice versa. Furthermore, this lets the patient know what foods to eat and how much to eat according to the pre-meal BG level. The configuration and operation of the proposed food plate are as follows. As shown in Figure 3(a), the presented food may consists of a controller incorporating various peripheral devices and a load cell that can be weighed. We use strain gauge load cells that convert the load acting on them into electrical signals. As the force applied to the load cell increases, the electrical signal changes proportionally. The load cell's output is to a micro-controller via a 24-bit analog-to-digital converter (ADC) for weighing scales. The proposed food may includes six load cells to weigh the six different food intakes, as shown in Figure 3(b). Detailed operation descriptions are as follows. The patient performs the following operations at the time of eating to record meal information. First, the patient presses the start button in the food tray to indicate the meal's start. The controller recognizing a meal start acquires a meal start time obtained from the RTC.