ABSTRACT
Recently, face masks have received increasing attention due to the COVID-19 pandemic, as their correct use can reduce and prevent the spread of outbreaks. Thus, several research studies focused on developing new strategies for identifying if individuals are wearing a face mask before they can be admitted into public spaces, buildings, and transportation systems. In this paper, we present an alternative approach to face mask detection pipeline for automatically detecting whether an individual is equipped with a face mask. Our proposed solution utilizes MediaPipe, a popular image segmentation and object detection machine learning model designed especially for cross-platform operation, with specific regard to mobile devices. We present the architecture of our pipeline, detail its operation, and report the results of an evaluation study in which we analyzed the performance of our model in real-world scenarios. © 2022 Croatian Society MIPRO.
ABSTRACT
The unprecedented emergency determined by the COVID-19 pandemic required national governments to enact countermeasures to contain the spread of the Coronavirus disease. Nevertheless, several research studies highlighted the acceptance issues and short- and long-term consequences of restrictions such as lockdown orders, social distancing, contact tracing, and face masks. In this paper, we present the results of a study in which we analyzed individuals’ knowledge, attitude, and behavior regarding the health-safety measures implemented during the COVID-19 pandemic, and we outline the human factors that can play a key role in designing solutions that have better usability and result in higher compliance from users. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
In addition to health consequences, impactful life changes, and losses, the COVID-19 pandemic has resulted in a worldwide economic emergency. Particularly, small businesses in key sectors, such as the hospitality and food industries, have incurred significant losses due to mobility restrictions, distancing requirements, and reduced service. Simultaneously, individuals have reduced their travels and visits to businesses and public places because of concerns related to the Coronavirus outbreak. In this paper, we introduce a web- and mobile- based platform dedicated to health-safety ratings and reviews. The system aims at helping businesses maintain a health-safety profile, address their customers’ expectations, and invite them to restore their habits safely. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The COVID-19 pandemic required the adoption of several health-safety practices that have been demonstrated to be crucial for limiting the spread of the virus, including the use of personal protection equipment (PPE). Particularly, face masks have become a ubiquitous component of our daily lives. However, despite their effectiveness, they have several drawbacks. In addition to being uncomfortable for many users, they entirely cover the mouth, which, in turn, poses limitations to non-verbal communication and interpersonal interaction. In this paper, we present the user-centered design process of a solution that augments face masks with additional features that support interaction, awareness, and engagement. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.