Report by Cristina Mele, Tiziana Russo Spena, Marco Tregua, Marialuisa Marzullo, and Adriana Carotenuto from the Innovation & Technical Transfer Area (Lab on Cognitive Technologies and Value Co-creation in Service Ecosystems, Interdepartmental Research Center LUPT) and the Smart Innovation Lab (Department of Economics, Management, Institutions) of the University of Naples Frederico II, Italy.


In the current pandemic, smart technologies (e.g., artificial intelligence, machine learning, cognitive computing, chatbot, wearables, blockchain) can adequately support the collection, analysis, and processing of big data and the decision-making processes of citizens, entrepreneurs, managers, and policy makers. Digital innovation is born more and more from the connections between companies and technology providers as well as with lead users and intermediaries; in this interconnected context, new open and interactive spaces for collaboration and participation are created, overcoming traditional models led by single innovators.

Both the advancement of knowledge and the updating of specialist and professional preparation require new paths of knowledge and new tools for analysis. On the one hand, the specialized press is full of new concepts and terminologies typical of disciplines such as engineering and information technology that contaminate the field of knowledge in medicine, economics, and psychology; on the other hand, the unpublished experiences of cases and practical applications contribute to raising the character of the discontinuity with which innovations in new digital scenarios manifest themselves. The peculiarities of a new technological solution, with its characteristics of innovation and uniqueness, detailed analysis, and identification of a turning point—introduced in the operations of institutions and firms and in daily social routines—create a database of knowledge and experiences to be presented and shared.

Four macro areas are identified: prevention, diagnosis, treatment, and research to analyse and outline the contribution of smart technologies to address the current pandemic. Each is defined by two specific application actions, for which application technologies and experiences are presented. Some of these are already in use, while others are in the design and development phase, capable of providing a first picture of the complexity of the phenomenon being analyzed.

Being able to implement effective measures to fight against the onset and spread of the coronavirus is of crucial importance for citizens, companies, healthcare institutions, and public administrators. The use of smart technologies offers a valid tool for the prevention of COVID-19. Support for prevention is expressed in the monitoring of data related to the health conditions and location of patients and other citizens and in the protection from infection.
Preventing actions:
Monitor (Artificial Intelligence, Bluetooth, Chatbots, Wearables):
– Systematically observe and verify the evolution of the phenomenon
– Check the physiological/vital parameters of citizens
Protect (Artificial Intelligence, Bluetooth, Computer-Aided Design, Drones, Robots, Wearables):
– Protect from viral agents
– Protect citizens by reducing the risk of contagion

The co-presence of skills and tools can play a key role in diagnosing the symptoms of the coronavirus and limit the transference of the disease. Smart technologies assist doctors and healthcare institutions in quickly identifying patients with COVID-19 and detecting and classifying aspects of the disease. Support for diagnosis is expressed in the self-evaluation of symptoms and in the acceleration of the diagnostic process.
Diagnosing actions:
Self-Evaluate (Chatbots):
– Identify the symptoms simply and independently
Accelerate (Artificial Intelligence):
– Make the analysis process faster

The treatment of infected subjects is an activity as crucial as it is complex, given the widespread contagion and pressure on healthcare structures.
Smart technologies favor the implementation of suitable solutions to support therapy in emergency conditions. Support for treatment is expressed in the improvement of knowledge and in the management of therapeutic processes.
Treating actions:
Improve (Artificial Intelligence):
– Enrich medical knowledge related to drug therapies
– Enhance the ability to deliver care
– Identify best practices
Handle (Computer-Aided Design, Virtual Reality):
– Avoid the dangers of managing care due to lack of medical tools
– Strengthen the supply network of medicine and medical material

The activity of research is important for identifying disease countermeasures. Smart technologies support the research process by making it more efficient and effective, given the importance of time in obtaining a valid solution. Research support is expressed in the study of the information available and in the development of new drugs.
Research actions:
Study (Artificial Intelligence, Blockchain, Cloud Computing):
– Analyze the characteristics of the disease
– Find the information needed
Develop (Artificial Intelligence, Deep Learning):
– Define the characteristics of molecules and compounds
– Create new drugs to start testing

The innovations described in this report outline a framework of knowledge and offer general reflections. Technologies not only open up new horizons and scenarios that are not always imaginable but also make more evident the need to radically rethink the practices and methods of organizing human, social, and economic relations. Challenged by this hyper-complexity, all actors must face the indeterminacy and ambivalence of the ongoing metamorphosis of political, social, and cultural processes and the inadequacy of the interpretative frameworks offered by traditional cognitive schemes. At the same time, the technologies described uncover issues with regard to ethics and privacy; some of these technologies offer firm guarantees in terms of cybersecurity, while others are unexplored, leaving room for doubt on their use. The challenge is in the communication between different languages, between people, between machines, and between people and machines.

The support of smart technologies also materializes in diagnostic activities mainly through the use of AI-based chatbots, which help relieve the pressure of too many patients on healthcare structures, for a first diagnosis, offering an effective triage and self-assessment system through simple and intuitive interfaces. Furthermore, the added value afforded by smart technologies to the diagnosis phase of COVID-19 lies in the ability to accelerate, through the instrument of artificial intelligence and deep learning, the process that leads to suitable outcomes with all the obvious advantages in operational and epidemiological terms.

At this time, there is still no vaccine for COVID-19, but the technologies provided in this report offer improved ways to administer treatment, increase management skills of the people involved, avoid the dangers arising from the lack of medical equipment, and strengthen the supply network of pharmaceutical and medical material. We are confident that through the ability of artificial intelligence to analyze therapeutically relevant characteristics and through additional learning in the vast scientific literature, treatments to end the pandemic will be found.

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