Sulis - Process-driven methods and techniques in green and public health. - Bando "Grant for Internationalization - GFI" 2022

Questo progetto si concentra sull'insieme delle attività di gestione supportate dai sistemi informativi. Nel Green Business Process Management (Green BPM) le attività aiutano a monitorare e ridurre l'impatto ambientale dei processi aziendali nelle loro fasi di progettazione, miglioramento, implementazione o funzionamento. Oltre all'analisi dei dati secondari e delle statistiche spaziali, è sempre più importante analizzare i processi reali attraverso tecniche di estrazione della conoscenza da dati reali (event logs). Il Process Mining (PM) ha mostrato eccellenti applicazioni nelle organizzazioni tradizionali e moderne. In questo progetto, l'attenzione si concentrerà sulla necessità di riorganizzazione attraverso l'introduzione di nuove tecnologie basate sull'AI. I processi, spesso impliciti e nascosti nella conoscenza tacita dei lavoratori, devono essere ricostruiti in modo ottimizzato per massimizzare i benefici dell'innovazione dell'IA. Inoltre, i processi possono essere adattati per affrontare le sfide della sostenibilità e per la simulazione di emergenze in ambito sanitario, come quella di Covid. Ambito di ricerca: This project focuses on Green Business Process Management (Green BPM) "From the perspective of an information systems (IS) researcher, Green BPM is the set of all IS-supported management activities that help monitor and reduce the environmental impact of business processes in their design, improvement, implementation, or operation phases, as well as lead to cultural change within the process life cycle" [1]. In addition to the analysis of secondary data and spatial statistics, it is increasingly relevant to analyze real processes through techniques of knowledge extraction from logs. Process Mining (PM) [2] techniques have shown excellent applications in traditional and modern organizations [3,4]. In this project, the focus will be on the need for reorganization by the introduction of new AI-based technologies. Processes, often implicit and hidden in the tacit knowledge of workers, need to be reconstructed and optimized in order to maximize the gain from AI innovation and at the same time benefit from the increasing amount of data generated by the use of 'process-aware' information systems, sensors, internet-of-things. Moreover, processes can be adapted to address sustainability challenges, as well as for simulation of emergencies, such as the covid one [5]. One of the important aspects of Green BPM for industrial organization is transportation. An example of a transportation-intensive industry is healthcare. In fact, in addition to ambulance fleets, hospital vehicles, and delivery vehicles, a major impact is patient travel to healthcare services and facilities. Not only are patients on the move, but so are relatives and caregivers to get to treatment centers. Not surprisingly, air pollution is concentrated near large-scale hospital facilities, driven by these patient and caregiver trips. For example, the UK's National Health Service recently estimated that CO2 emissions related to transport to healthcare facilities account for about 18% of their total carbon emissions [6]. This significant figure can be reduced by placing facilities near public transportation infrastructure and within communities. An alternative that does not require the construction of new facilities is telemedicine. Sustainability initiatives in healthcare can improve the impact on the environment and promote a more satisfying and healthy experience for patients and staff, Computational simulation can be used to perform scenario analysis in a decision-making perspective [7]. A recent work already investigated the impact of different modeling techniques [8]. The Turin research group already explored the role of PM techniques in combination with different techniques, e.g. with optimization in a predictive perspective [9]. Telemedicine. One of the most recent and innova