Internet of Healthy Things: From a General Picture to the Case of Trauma Management

In the last decade, IoT technologies made an impressive progress. Modern smartphones are powerful computing devices, featuring a variety of onboard sensors, a robust support for pervasive interaction with an ecosystem of Bluetooth-enabled external devices and wireless networking, eventually including
Internet and cloud-based services. Besides mobile computing, wearable computing and eyewear computing are achieving a level of maturity that makes it possible to exploit them out of labs, in real-world professional contexts. Personal Assistant Agents have been developed in different domains, supporting users in various tasks. Cognitive computing became a reality, leveraging complex algorithms from AI to enable advanced analytical processing, sophisticated data discovery, prediction generation.
Even though we recently witnessed to a progressive computerisation of healthcare services, whose quality, efficacy and efficiency significantly improved thanks to the introduction of novel ICT infrastructures and services, IoT in hospital daily routine is still far from reality.
In this seminar I will present the vision and expected impact of introducing IoT in hospital applications to support the primary efforts of healthcare systems and organisations which are devoted to improving (i) safety and quality of care, reducing adverse events and medical errors; (ii) efficiency and organisation, thus decreasing costs, expenses and waste.
To demonstrate the feasibility of the approach, I will present the case of TraumaTracker, a system designed, developed and evaluated – in cooperation with the Trauma Team of the Bufalini Hospital in Cesena, Italy – for real-time documentation and alerting during trauma resuscitation. TraumaTracker is an agent-based system composed of three main subsystems: (1) a mobile/wearable component assisting documentation activities of physicians during a trauma and possibly providing alerts, (2) a front-end web app with functionalities to access, manage, analyse and print reports, (3) a back-end part, based on a set of services to collecting and managing data, to interacting with existing hospital services (such as the one which acquires vital parameters), to real-time analysing patient data via AI algorithms.


Sara Montagna - Università di Bologna

Docente di riferimento

Marco Bernardo


Luogo Data Orario Crediti (CFU)
Aula Von Neumann 2 Aprile 2019 16:00 0,125