In this blog post will be presented the infographic from the SecureIoT project, which is an outcome of the joint pilot between Innovation Sprint and LuxAI.
We are nearing the completion of the great SecureIoT project. Nowadays, the complexity, heterogeneity, and dynamic behaviour of emerging IoT deployments pose tremendous security challenges. These require more dynamic, scalable, decentralized, and intelligent IoT security mechanisms that are addressed by our SecureIoT project and especially our SecureIoT-enabled socially assisted robots (SAR) usage scenario. The aim of the SAR usage scenario is to integrate and validate the SecureIoT services in the scope of personalized healthcare and ambient assisted living scenarios, involving the secure integration of QTrobot (QT) of our partners LuxAI and the CloudCare2U platform (CC2U) of Innovation Sprint. This includes a risk assessment of communications security, predictive analysis of security risks, implementing access control policies to enhance the security of the solution, and auditing of the solution against security, safety, and privacy guidelines and regulations.
In the scope of the SecureIoT socially assisted robots use case, the plan is to demonstrate the secure integration of a QT robot developed by LuxAI in an environment provided by the CloudCare2U (CC2U) IoT healthcare platform developed by iSPRINT, which holds the promise to enhance the functionalities offered by both QT and CC2U.
The integration of QT with CC2U focuses on the delivery of personalized ambient assisted living functionalities, fully in-line with the business strategies of both partners. In particular, QT will be used to deliver personalized rehabilitation and coaching exercises, as part of wider (rehabilitation or coaching) programs, managed and delivered through CC2U.
The integration between QT and CC2U can be directly realized, as CC2U is already a virtual robot interface for interaction with end-users, which will be replaced by QT. The integration challenge, however, lies in keeping track of the state of QT and the environment, as well as in implementing distributed task assignment strategies (such as the Consensus-Based Bundle Algorithm (CBBA)), which enable the distribution of application logic across different smart objects. Such mechanisms can be extended to more dynamic and heterogeneous environments.
We have come a long way from the start of the project and our work is bearing fruit. We have summarized our achievements as well as SecureIoT-enabled business opportunities in the excellent infographic prepared by our SecureIoT project.
Personalized healthcare and ambient assisted living services and scenarios have numerous security requirements that are difficult to accommodate and pose numerous challenges. Within SecureIoT we addressed said challenges exploiting the emergence of paradigms such as Machine Learning, process mining, and developer support.
We look forward to the final months of the project, where our work will be wrapped up, and all services will be completely integrated and validated within our pilot.
Alexandru Vulpe & Razvan Craciunescu
Senior Research Engineers
Dr. Alexandru VULPE has a Ph.D. since 2014 and has broad technical expertise with about 10 years’ involvement in international and European research projects. His research ranges from algorithms for wireless communications, 4G and beyond 4G networks to Big Data, Security and Internet-of-Things. He is the author and co-author of over 70 scientific papers related to Big Data, Security, Cloud Computing, 3G and 4G systems, as well as Machine-to-Machine (M2M) communications. Furthermore, he has managed and participated in over 25 research projects (over 10 international projects) where he was involved in all the major technical achievements, including WP leader, deliverable, and annual report editor. In SecureIoT, Dr. Vulpe is the main researcher involved in integrating CC2U in the overall SAR scenario as well as integrating, deploying, and validating the SECaaS services within the SAR use case.
Dr. Razvan Craciunescu has a Ph.D. since 2018 and has more than 8 years’ experience in IoT, eHealth, communication systems, and product development from both a research point of view but also from a start-ups/spinoffs one as a founder of product manager. He worked as research in academia both in Romania and Denmark and as an invited professors in the US. Beside his involvement with Innovation Sprint, he is also a mentor for acceleration and incubation IT&C programs. In SecureIoT, Razvan is involved in integrating, deploying, and validating the SECaaS services within the SAR use case.
