A generic definition of a smart city [1] implies modern technologies typically deployed by public bodies in urban areas with the intent of improving the inhabitants’ quality of life. Deploying such technologies can be costly, requiring the installation of, e.g., monitoring sensors throughout the city, followed by management efforts throughout their lifetime. This is also a limiting approach, since you can only offer the smart city services supported by the sensors that you have deployed. There are numerous situations when a collaborative approach would work better. We can easily imagine a scenario in which there is a need for a certain service (we call this a collaborative service), in a certain area of a city, in a specific time frame, that is not entirely covered by the smart city technology fabric (even if it is, additional information could intuitively increase the usefulness of the service).

Nowadays, the amount of technology present on city grounds is enormous. Numerous parties, including organizations, as well as private individuals, have transformed their properties in more-or-less cyber-physical systems (CPSs). Facilities have become smart facilities and homes have become smart homes. Most of these parties have implemented flavors of Digital Twins (DTs) of those CPSs, accessible from a laptop or even smartphone. However, these are siloed DTs as long as there is no information shared with the outside world. We believe that many would be willing to share parts of their information, under very well-defined conditions, if it is for the public good (e.g., enhancing the coverage of air quality measurements in a city by using some private sensors that cover an area not covered by the public monitoring infrastructure).

Building upon the concept of collaborative networks [2][3], in this project we aim to explore the realization of a system that enables the ad-hoc organization of DTs in a community [4] to achieve a common goal, i.e. the delivery of a collaborative service for smart cities. We are going to investigate aspects such as formalizing the needs of a collaborative service, how the DT parts (and which of them) can respond to the aforementioned needs, modeling the conditions under which the parties are willing to make the information available (enabling thus an automated release mechanism). The study will converge towards a proof of concept, aiming for an evaluation with real-world data from DTs on university’s campus.

[1] Hall, R. E., Bowerman, B., Braverman, J., Taylor, J., Todosow, H., & Von Wimmersperg, U. (2000). The vision of a smart city (No. BNL-67902; 04042). Brookhaven National Lab.(BNL), Upton, NY (United States).

[2] Nazarenko, A. A., & Camarinha-Matos, L. M. (2017, May). Towards collaborative cyber-physical systems. In 2017 International Young Engineers Forum (YEF-ECE) (pp. 12-17). IEEE.

[3] Nazarenko, A. A., & Camarinha-Matos, L. M. (2019). Basis for an approach to design collaborative cyber-physical systems. In Technological Innovation for Industry and Service Systems: 10th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2019, Costa de Caparica, Portugal, May 8–10, 2019, Proceedings 10 (pp. 193-205). Springer International Publishing.

[4] Nazarenko, A. A., & Camarinha-Matos, L. M. (2020). The role of digital twins in collaborative cyber-physical systems. In Technological Innovation for Life Improvement: 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, Costa de Caparica, Portugal, July 1–3, 2020, Proceedings 11 (pp. 191-205). Springer International Publishing.