Privacy-preserving Social Distance Monitoring on Microcontrollers with Low-Resolution Infrared Sensors and CNNs

Low-resolution infrared (IR) array sensors offer a low-cost, low-power, and privacy-preserving alternative to optical cameras and smartphones/wearables for social distance monitoring in indoor spaces, permitting the recognition of basic shapes, without revealing the personal details of individuals. In this work, we demonstrate that an accurate detection of social distance violations can be achieved processing the raw output of a 8x8 IR array sensor with a small-sized Convolutional Neural Network (CNN). Furthermore, the CNN can be executed directly on a Microcontroller (MCU)-based sensor node.With results on a newly collected open dataset, we show that our best CNN achieves 86.3% balanced accuracy, significantly outperforming the 61% achieved by a state-of-the-art deterministic algorithm. Changing the architectural parameters of the CNN, we obtain a rich Pareto set of models, spanning 70.5-86.3% accuracy and 0.18-75k parameters. Deployed on a STM32L476RGMCU, these models have a latency of 0.73-5.33ms, with an energy consumption per inference of 9.38-68.57\muJ. © 2022 IEEE.

Burnout and work engagement among healthcare workers during the COVID-19 pandemic: the role of satisfaction with job resources.

Objectives: The COVID-19 pandemic represents a major public health challenge, particularly among frontline healthcare workers. This study examines the impact of satisfaction with job resources (leader-, task-, team-and organizational-level) on burnout and work engagement. Material(s) and Method(s): one-hundred and twenty-five healthcare workers (physicians, nur-ses) from a private health institution filled an anonymous online survey. Seventy-six participants were females. Result(s): Bivariate correlation and multiple regression analyses showed that satisfaction with job resources positively influences work engagement, and negatively influences burnout. In particular, regression analyses showed that burnout symptoms were mainly predicted by satisfaction with organizational resources (betaexhaustion =-.22;betacynicism =-.53) and work engagement was best predicted by satisfaction with task resources (betadedication = .45;betaabsorption = .34). Conclusion(s): Current findings point the value of satisfaction with job resources to protect the mental health of frontline healthcare workers during health crises and extreme work overload. Suggestions aimed at reducing burnout, promoting work engagement and protecting the well-being and mental health of healthcare workers during future public health crises are proposed. Copyright © 2022, Federacion Argentina de Cardiologia. All rights reserved.