# Deep-cARe: Projection-Based Home Care Augmented Reality System with Deep Learning for Elderly
## 3 Material and Methods
### Object Detection Performance  
The precision of object detection is based on the environment and the distance from the system, the possibility of an implementation of the scenario can be experimentally determined. To provide notification and information for important scheduling to elderly people in daily life, objects that should be detected are selected. First, elderly patients have difficulty in taking medication at the appropriate time. By performing object detection on a medicine bottle, it is expected that patient compliance can be increased using an AR projection as a medicine-taking notification near the medicine bottle at the appropriate time. Furthermore, through objection detection of windows and doors, status information regarding the interior of the house can be obtained before the subject leaves the house, and guidance can be provided for taking the appropriate action. To verify whether this function can be smoothly performed when the proposed platform is used, a precision experiment on object detection was conducted in a real environment, where the correctly and incorrectly classified cases were categorized as TP and FP, respectively, and when the bounding box was not applied to an object, a detection failure (miss) was recorded. The experiment was conducted by changing the distance between the system and the object, and the detection and precision rates were calculated in terms of the distance in the 375 frames using the same proportional expression as in the face recognition experiment. For a medicine bottle (Figure 11), the COCO dataset was used. When the distance from the system was 0.5 m, 100% detection precision was observed, and when the distance was 1 m or larger, the DR was 88.00%. Furthermore, when the distance was 1.5 m, the DR was 86.93%, and when it was 2 m, the DR decreased sharply to 30.13%. When the distance was greater than 2 m, the object was not detected. When the resolution of the object in the input image (1350 \(\times\) 1000 pixel) was 80 \(\times\) 140 pixels or less, the precision of detection decreased by more than half, and when it was 50 \(\times\) 80 pixels or less, the object was not detected. For the medicine bottle, there was only one miss and no FP. Therefore, although the detection precision for the medicine bottle is high, a scenario should be created by considering the DR according to the distance. Accordingly, it was determined that it may be challenging to detect a medicine bottle in a real environment. In the experimental results, object detection was limited to the case of a medicine bottle placed on a dining table within 1 m from the system. In the case of windows (Figure 12) and door, the Open image dataset was used. In the experimental environment, two windows and one door were present. When the distance from the system was 2 m or  
Figure 11: Bottle detection results based on distance: (**a**) 0.5 m, (**b**) 1 m, (**c**) 1.5 m, and (**d**) 2 m.  
more, the two windows were input into the system camera, and when the distance was less than 2 m, only one widow was input. A DR of 12.5% and a precision of 86.57% were recorded when the distance from the system was 0.5 m. At 1 m, only one window was input, and a DR of 40.40% and a precision of 58.20% were recorded. The reason for the lower precision compared with the case of 0.5 m was the increased number of cases in which the window was misrecognized as a door. At 1.5 m, a DR of 79.31% and a precision of 83.29% were recorded, confirming that both the DR and the precision increased. When the distance from the system was 2 m or more, two windows were input, the number of objects to be detected in all frames accordingly increased two-fold. At 2 m, a DR of 86.23% and a precision of 100% were recorded, and for 5 m, a higher DR of 90.10% was recorded with 100% precision this was the highest DR. For the door, when the distance from the system was 5 m, a DR and precision of 100% were observed. When the distance from the system was 2 m or less, the door was not detected.