Autonomous Fever Detection, Medicine Delivery, and Environmental Disinfection for Pandemic Prevention
Abstract
:1. Introduction
- Novel algorithms for automatic fever detection and medicine-taking recognition that ensure both human safety and comfort, as well as environmental disinfection that covers blind spots well, were developed.
- A quantitative assessment method for evaluating the reduction in infection risk through the use of robots based on the duration and proximity of contact with confirmed cases was developed.
- Via integration with multi-sensors and a collision-free path planning strategy, an autonomous system that was capable of navigating the mobile robot manipulator among static obstacles and moving people was developed and applied for a field study in a hospital-like environment.
2. Proposed System
2.1. Posture and Action Recognition
- Step 1:
- Input the patient’s time sequence of medicine taken, measured via the depth camera, and process it to become the posture sequence O. Classify the postures into corresponding sub-actions A~E via the CNN and rename O to be Ol.
- Step 2:
- Obtain the standard posture sequence R to serve as the reference for comparison from a number of demonstrations of successful medicine taking.
- Step 3:
- Generate Matrix M for similarity evaluation between R and Ol. Derive the dynamic time warping distance for its elements M(i,j) for similarity measurement.
- Step 4:
- If the value of the similarity measurement in Step 3 is smaller (larger) than a preset threshold, the patient is judged to have (not) taken the medicine.
2.2. Safety Control
- Step 1:
- Confirm that the patient is seated and stationary.
- Step 2:
- Utilize the depth camera on the robotic arm to calculate the coordinates of the patient’s forehead.
- Step 3:
- Compute the path from the robotic arm to the forehead and restrict the orientation of the end-effector.
- Step 4:
- Dynamically adjust the arm’s speed based on the distance from the patient.
2.3. Environmental Disinfection
- Step 1:
- Activate the mobile robot manipulator to explore the environment and objects.
- Step 2:
- Generate the 2D map of the environment by using the Lidar and GMapping algorithm and the 3D map for the object in the environment by using the depth camera and RTABMap algorithm.
- Step 3:
- Navigate the mobile platform for disinfection in the open area. Conduct path planning for contour following of the object by using the PRM and NN algorithms and proceed with corresponding disinfection.
- Step 4:
- Estimate the UVC irradiation intensity for the locations on the object by using (7). If the intensity exceeds a preset value, move the robotic arm to the next disinfection location; otherwise, let it remain in the same location.
- Step 5:
- The process continues until the entire environment is fully disinfected.
2.4. Infection Risk Assessment
2.5. Real-Name System
3. Experiments
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Dose Card | Proposed System | Conventional System |
---|---|---|
1 | 20 | 0 |
2 | 25 | 10 |
3 | 20 | 5 |
4 | 25 | 15 |
5 | 20 | 10 |
Questions | Strongly Disagree | Strongly Agree | ||||
---|---|---|---|---|---|---|
1. | I think I am willing to use this system in the fever station (isolation ward). | |||||
2. | I think the use of this system in the fever station (isolation ward) is too complicated. | |||||
3. | I think this system is easy to use. | |||||
4. | I think I need help to use this system. | |||||
5. | I think the functions of this system are well integrated. | |||||
6. | I think there are too many inconsistencies in this system. | |||||
7. | I think most people can learn to use this system soon. | |||||
8. | I think this system is troublesome to use. | |||||
9. | I am confident that I can use this system. | |||||
10. | I need to learn a lot of extra information to use this system. |
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Su, C.-Y.; Young, K.-Y. Autonomous Fever Detection, Medicine Delivery, and Environmental Disinfection for Pandemic Prevention. Appl. Sci. 2023, 13, 13316. https://doi.org/10.3390/app132413316
Su C-Y, Young K-Y. Autonomous Fever Detection, Medicine Delivery, and Environmental Disinfection for Pandemic Prevention. Applied Sciences. 2023; 13(24):13316. https://doi.org/10.3390/app132413316
Chicago/Turabian StyleSu, Chien-Yu, and Kuu-Young Young. 2023. "Autonomous Fever Detection, Medicine Delivery, and Environmental Disinfection for Pandemic Prevention" Applied Sciences 13, no. 24: 13316. https://doi.org/10.3390/app132413316
APA StyleSu, C.-Y., & Young, K.-Y. (2023). Autonomous Fever Detection, Medicine Delivery, and Environmental Disinfection for Pandemic Prevention. Applied Sciences, 13(24), 13316. https://doi.org/10.3390/app132413316