Designing the intelligent epidemic control robot control system for epidemic prevention and control

In response to the current problem of highly contagious new coronavirus and repeated epidemics, which cause great threat and inconvenience to people's production and life, In this paper, a multifunctional intelligent epidemic prevention robot control system based on a single chip microcomputer is designed to realize the intelligent management of community epidemic prevention and control. Stm32 microcontroller is used as the control core. In order to improve the efficiency of prevention and control management and reduce contact, the Jetson Nano controller is designed to provide map reproduction, positioning navigation, and path planning functions. It is used to summarize patient status information quickly and efficiently, the design provides face recognition and remote monitoring functions to realize real-time uploading of accurate data to cell phone console APP and computer terminal integrated monitoring platform. Through the map reconstruction and positioning simulation test, an optimal path is selected to ensure the stable movement of the epidemic prevention robot. The face_recognition algorithm's error reception rate, error rejection rate, and accuracy rate are 0.35%, 11.12%, and 88.53%, respectively, which are better than the face-net algorithm in three aspects and can well meet the needs of small communities. The face recognition needs of small community areas can be well met. This epidemic prevention and control system can realize efficient community epidemic prevention and control management, reduce contact transmission, and lower the difficulty of epidemic prevention and control. © 2022 IEEE.

Low-Cost Remote Laboratory for Robotics Undergraduate Learning during Covid Context

The article proposes to develop, and implement a low-cost, open-source robotics' remote laboratory, to improve online, and hybrid STE learning experience facing COVID-19 context. Electronic modules were developed using digital fabrication, and a Raspberry Pi 4 as a core. Enabling students to connect by a remote access via a VNC port, and control robot elements to complement theoretical content controlling sensors, and actuators using Python scripts. The project was implemented in two iterations, fitting data security, and network accessibility requirements. Those features, in comparison to other state-of-the-art proposals developed outside of South America, highlight our proposal as a low-cost, and open-source alternative suitable to replicate in different resource-constraints context, and to other advanced STE courses. © 2022 IEEE.