Context Presentation

The development of sustainable smart cities requires the deployment of Information and Communication Technology (ICT) to ensure better services and available information at any time and everywhere. As IoT devices become more powerful and low-cost, the implementation of an extensive sensor network for an urban context can be expensive.

This thesis addresses the problem of estimating missing information in urban contexts. The objective is to estimate accurate environmental information where physical sensors are not available. The proposed solution, HybridIoT, uses the Adaptive Multi-Agent System (AMAS) to estimate accurate environmental information under conditions of uncertainty arising from the urban application context in which the project is applied, such as openness, heterogeneity and large-scale, which have not been explored by the state-of-the-art solutions.

illustration - Davide Guastella


Smart city, Cooperative Multi-Agent Systems, Missing Information Estimation, Heterogeneous Data Integration

Scientific goals

- Limiting the number of ad hoc devices to be deployed in an urban environment

- The exploitation of heterogeneous data acquired from mobile, intermittent devices

- Real-time processing of information

- Self-calibration of the system