Expertise: The CNIT research unit based at the CNR research area in Pisa includes two different research groups: the Ubiquitous Internet Group of the CNR Institute for Informatics and Telematics (CNR-IIT), and the Wireless Networks Lab of the CNR “Istituto di Scienza e Tecnologie dell’Informazione” (CNR-ISTI).
The research unit, which includes around 30 tenured researchers, does research in the following areas:
- 5G and next generation networks (6G), including multiple-access edge computing (MEC)-based network architectures
- Internet of Things and wireless sensor networks
- Mobile networking and computing
- Indoor localization systems
- Satellite communications
Research topics in the area of 5G and beyond networks, and MEC-based network architectures:
- Edge-centric networking approaches based on a synergic use of D2D and V2V communications, alongside communications with the Base Stations (BSs). The communications between mobile terminals are used to assist the BSs in the downlink of popular contents (also known as D2D data offloading), or in the uplink. In this context, our approach integrates information related to the physical layer, including information on the radio signal propagation, to the application layer, e.g., the popularity of some content in the packets’ payload or the “social” connectivity of the mobile terminals and/or users.
- Distributed computing in MEC/FOG environments and serverless edge computing, including (i) Distributed computing for Low-latency applications through the efficient dispatch of stateless functions in edge systems. Our approach is compliant with the ETSI MEC standard and is tested using a testbed implemented with low power devices. (ii) Distributed and resource constrained computing models based on artificial intelligence (AI). The models allow to combine partial datasets acquired at multiple locations by first performing computations on each dataset, thus learning the partial models, and combine them refining an overall model through smart exchange of local data models.
- End-to-end system integration in different application domains building on the 5G infrastructure, with end-to-end field trials. This activity includes the development of drone-based systems in the public surveillance and agriculture application domains, railway network monitoring systems using diagnostic trains, water pipe system monitoring through acoustic tomography.
Research topics in the area of mobile networking and computing:
- Distributed communication middleware for context awareness (identification, recognition), with the goal of abstracting out layer-2 technologies from the application domain design, development, and implementation. This includes considering wearable devices as well as environmental sensors as data source, and uses protocols like MQTT.
- Algorithms and protocols for mobile edge server selection for different applications (e.g., crowdsensing).
- Mobile context aware recommender systems based on data gathered on users’ devices and about users’ habits and interests.
- Mobile social networks to enable mobile user social interactions at specific physical aggregation points, based on common interest identification.
Research topics in the IoT and wireless sensor networks areas:
- Wireless access protocol design (layer-2) for wireless sensor networks
- Congestion control for scalable networks based on the Web of Thighs paradigm
- Data brokering services for shared sensor networks
Indoor localization systems:
- RSSI-based algorithms and systems for indoor localization
- D2D communications-aided algorithms and systems for indoor localization
- Integration of multiple localization systems in large complex indoor scenarios (e.g. airports, shopping malls, hospitals, railway stations, etc…), including taxonomy definition and the discovery of available location services.
The research unit activity is carried out within the framework of multiple national and international projects, and customized for different verticals, including the following items:
- Distributed data management in fog environments for Industry 4.0 applications.
- Data provisioning with optimisation of industrial fog nodes energy resources under real-time delay constraints.
- Distributed AI approached for industrial process monitoring.
m-health, s-health (smart health) and Ambient Assisted Living (AAL):
- Development of distributed cloud/fog home-based health monitoring systems, including the design of API and healthcare services based on them, privacy preserving tools, design and implementation of home based on heterogeneous biomedical devices and a local fog server.
- Development of m-health solutions for physiological and behavioral monitoring.
- Development of online decision support systems and personalized coaching based on the analysis of data gathered through m-health and remote monitoring applications and tools.
- System integration and application development for AAL environments.
Smart buildings and smart cities:
- Development of a dashboard for the energy management in smart building and building automation scenarios.
- Smart spaces system design based on ambient intelligence.
Address: Via G. Moruzzi, 1 – 56124 PISA
Phone: +39 050 315 8281 [Root + ext]
Fax: +39-050 315 2113
Research Unit Responsible: Dr. Loreto PESCOSOLIDO
Members of the Research Unit