ABSTRACT
The COVID-19 pandemic has impacted the lifestyle of people in every community and workplace, including universities. There, places like cafeterias where people are expected to not wear a mask for the majority of time, i.e., while eating or drinking, are potentially very risky. In such scenarios, the Internet of Things (IoT) technological stack and Edge Intelligence paradigm represent really useful solutions for the safe provision of essential services by predicting, monitoring, and contrasting potentially dangerous situations. Therefore, in this chapter, we present an example of cognitive building denominated as Smart Cafeteria: it is a highly sensor-and-actuator-augmented environment, aimed at monitoring the users' presence in order to detect those dangerous situations for COVID-19 virus spreading. Driven by the development guidelines of the ACOSO-Meth methodology, the Smart Cafeteria exploits a set of heterogeneous edge devices, IoT technologies, cloud services, and neural networks for acquiring, gathering, analyzing, and predicting temperature and humidity values, since the latest studies have recently suggested that cold, dry, unventilated air contributes to virus transmission, especially in the winter season. The Smart Cafeteria has been designed within the campus of the University of Calabria, in Italy, as the specific target, but it can be adapted to any popular building or workplace. The obtained prototype testifies the suitability of approaches based on the Edge Intelligence paradigm for the development of effective and cheap solutions aimed at safer living spaces, within and beyond emergency situations. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.