Two Proposed Efficient DET Deep Learning Algorithms based on Vision for Touch less Hand Sanitizer Mobile Robot

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Rand Zuhair Khaleel, Firas A. Raheem


The sanitizer dispensers are too useful in a variety of settings to sterilize and protect people from illness, including patients and medical staff in hospitals, teachers, and students in schools or universities, and so on especially in coronavirus. The hand sanitizer dispenser mobile robot is one of the medical applications that is used to detect people who want to sanitize their hands. The object detection-based deep learning technique helps to recognize humans. In this paper, two algorithms based on the EfficientDet deep learning using a camera vision technique for a touchless hand sanitizer mobile robot are proposed. Each algorithm has been 80% trained dataset and 20% validation dataset. The AP is equal to 96% for algorithm-1 and 94% for algorithm-2. In algorithm-2 the first person can sanitize his/her hands and the second person also sanitize his/her hands after the first person. While in algorithm-1 just only one person can sanitize his/her hands. The loss errors of validation and the training of the proposed EfficientDet algorithm-2 are better than the loss errors of the proposed EfficientDet algorithm-2. The proposed EfficientDet algorithm-2 has two classes but the proposed EfficientDet of algorithm-1 has 7 classes.  The two proposed algorithms have good AP results. The training time of algorithm-1 = 6 hours while the training time of algorithm-2 = 1 hour.  The other proposal step includes changing the input-equal image size to a non-equal size, while the second proposal step presents a new flowchart for a mobile robot hand sanitization application which will be too useful for the COVID-19 pandemic to sanitize each person’s hand in public and closed places. Dataset has been created and prepared using image processing and a graphical tool called as LabelImg. The Dataset images were taken using a vision-based Raspberry Pi version 4 mini-computer. Then the dataset has been trained by the EfficientDet algorithm. The Python 3.7.4 programing language has been used. This proposed method has very good results, an efficient and scalable technique for hand sanitization person with a mobile robot application.   In future work, the full version of the hardware implantation will be done where the mobile robot will recognize the people using a deep learning approach and move to the person who wants to sanitize her/his hand.

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