Projects

PROSDS proposes a set of research actions that start from the modeling of the problem of collaborative perception (PeCo) in the context of Smart Mobility Spaces (SDS), propose different solutions, and arrive at evaluating the performance of some of the proposed solutions. PeCo is a central theme for the development of SDS in which different actors (vehicles, infrastructure, pedestrians, etc.) cooperate to optimize common objectives: safety, reduction of emissions, more efficient use of infrastructure, impact on pedestrians and other fragile users (VRUs - Vulnerable Road users), etc. PeCo is still a vague term, which includes many aspects: sharing of sensory measurements and expected trajectories from autonomous vehicles, reporting of unexpected events and more. It is necessary to define the different flavors of the term in the context considered, the assumptions implied by the context itself, and the metrics for evaluating performance based on the different levels of the system. PROSDS brings together different skills and addresses the problem from the different points of view mentioned and with different methodologies. The goal is to gain a broad overview of the space of possible solutions and the best way to address them. After formalizing the problem, possible solution methods will be addressed, including artificial intelligence and machine learning techniques, to finally move on to both analytical and simulation evaluation of the proposed methodologies and the resulting solutions.

Partners

The project is part of RESTART Structural Project SUPER) coordinated by Prof. Carla-Fabiana Chiasserini. PROSDS will cooperate with researchers involved in SUPER and contribute to its goals and deliverables.

EMBRACE provides smart solutions that reduce energy consumption via adaptive communication techniques, more effective hardware (including batteryless devices), novel communication systems, and novel antenna/sensor technology tailored to extreme environments, including intra-body and underwater sensors. EMBRACE’s consortium brings together all the expertise required to design and optimize hardware, coalesce component systems into more complex laboratory prototypes, design communication systems from antennas up to the networking protocols and related applications, access relevant environments for the technology at hand, and evaluate its performance. EMBRACE promotes a flexible approach, where the evaluation of the proposed solutions takes place through simulations until the system is ready for deployment on site. A selection of systems is then evaluated via field measurements in challenging environments, according to the requirements of the cascade call. UniBS with the ANS group is active in the design of algorithms to provide PHY- and MAC-layer protection in extreme channels and in privacy protection for standalone networks in adversarial environments.

Partners

The project is part of RESTART Structural Project SEXTET) coordinated by Prof. Michele Zorzi. EMBRACE is a consortium proposal coordinated by Prof. Paolo Casari at the University of Trento.

The project proposes a new system architecture for future 6G Smart Networks, characterised by high performance and energy efficiency, facilitating advanced internet applications. Key goals include driving an industry revolution, fostering digital transformation, and building smart societies with improved quality of life through features, like autonomous systems, haptic communication, and smart healthcare.

ANS participate in 6G-INTENSE as CNIT research unit together with Politecnico di Torino. ANS role is in the development of Joint Communciation and Sensing techniques and their integration in the 6G-INTENSE Intent-driven orchestration framework.

Project Website

Visit 6g-intense.eu website for more information on the whole project and goals.

Analysis and modeling the transmission channel is a foundation of transmission theory with the key goal of enabling channel equalization and optimal information decoding. Modern wireless communications, based on OFDM modulations and (massive) MIMO technologies, achieve unprecedented transmission speed and efficiency exploiting the description of the channel through the CSI, enabling the receiver to greatly improve the performance.

Transmission theory focuses on short term channel modeling, within the so-called coherence time, which is the essential descriptor that enables optimal decoding. In the past decade, however, the research community has discovered that the long term behavior of the channel, which is normally not useful for transmission performance, yields useful information on the propagation environment leading to the idea of joint communication and sensing (JCS).

Sensing includes people localization and tracking, object recognition, but also e-health and emotional computing applications. We stress that this is very different from standard device localization as nobody is asked to carry a device and the ambient is sensed as if communications signals were a radar, but without the need of ‘pulse-and-reflect’ operation.

The potential of JCS is enormous, and all future telecommunication systems, from 5G to emerging Wi-Fi standards foresee JCS in their evolution path. At the same time this potential entails also enormous privacy and security/safety concerns, as JCS is a pervasive tracking system that cannot be countered with any cryptographic means, as the information is embedded within the signal at the physical level.

CSI-Future focuses on JCS based solely on the interpretation of the CSI with AI/ML techniques, coupled with appropriate protocols to operate it and preserve safety and privacy of users.

CSI-based JCS has been tackled through AI/ML, yielding very promising results, but without completely uncovering how the information from the environment is embedded in the signal, nor proposing interpretative or predictive models for the shaping of CSI by the environment. Studies on privacy and security are still in their infancy.

The goal of CSI-Future is to push the state of the art one step further offering models that increase the insight in the problem and possible solutions to the privacy and security issues. CSI-Future starts from an extensive measurement campaign to collect a very large dataset to analyze, a feat that, strangely enough, has not yet been tackled by the community. The dataset will be published as Open Data, and fundamental stochastic analysis and modeling will be carried out. Further, the project will investigate different learning techniques to identify what are those that yield the best results in ambient sensing. Finally CSI-Future will propose protocols to exploit the results obtained in real communication systems as well as techniques to enable only authorized sensing and prevent attacks.

Partners

Politecnico di Torino (Prof. Carla Fabiana Chiasserini)

University of Verona (Prof. Damiano Carra)

Nei prossimi mesi sarà messo a punto un modello digitale di infrastruttura di trasporto innovativa, in grado di integrare una gestione sempre più automatizzata del traffico, supportare la guida autonoma, realizzare reti di ricarica elettrica e rifornimento di idrogeno intelligenti e prevedere e salvaguardare la sicurezza e resilienza delle infrastrutture di trasporto. Un gemello digitale sarà messo a punto e utilizzato per il testing e la validazione di soluzioni tecnologiche all’avanguardia, affiancandolo con un Living Lab in scala reale che sarà proposto a completamento della rete di laboratori previsti per lo Spoke 7. Il living lab permetterebbe di trasferire immediatamente le soluzioni innovative prodotte dal mondo del testing virtuale al mondo reale. L’ecosistema fisico e digitale realizzato permetterà la crescita di una nuova filiera industriale di settore, con notevole slancio ed opportunità per il settore produttivo, lo sviluppo e diffusione delle Smart Infrastructures, con grande miglioramento della fruibilità e sostenibilità dei sistemi di trasporto, e la formazione di una nuova generazione di tecnici di alta formazione per la realizzazione e gestione della mobilità di domani.

DI-P2SL is a long-term project devoted to protecting people’s location privacy from unauthorized intrusion and surveillance based on 802.11 signal analysis. Recent works have shown that the Channel State Information (CSI) of 802.11 signals can be used to localize people with sub-meter precision in indoor environments, and this even if they do not carry any 802.11 device, but just based on how their presence modifies the electromagnetic environment. The goal of DI-P2SL is to implement, within the openwifi environment, appropriate CSI manipulation techniques that can counter unauthorized localizations. We have recently proved the feasibility of such a manipulation technique with an experimental approach and Matlab-based CSI processing that obfuscate the information carried by the CSI allowing position inference. We are currently devising more sophisticated obfuscation techniques that aim at making the manipulated signal indistinguishable from a non-manipulated one, and we plan to implement this solution in openwifi allowing its use, and further improvement, by anyone willing to protect his/her own privacy.

CSI-MURDER investigates how the proper manipulation of Wi-Fi frames’ preamble interfere with algorithms that use channel-state-information (CSI) for sensing the physical environment. Recent work demonstrated that it is possible to use CSI data for controlling people movement and activity. This project studies how to re-establish victims’ privacy by deploying techniques at the physical layer that can circumvent sensing algorithms.

CSI-MURDER is an Experiment of the ORCA Project. Please visit the web page of the project to see the related publications, the availability of code through github and much more.

netCommons is a Horizon2020 research project that has been coordinated by Renato Lo Cigno at the University of Trento.

NetCommons introduced in the scenario of telecommunication networks a novel transdisciplinary methodology on treating network infrastructure as commons, for resiliency, sustainability, self-determination, and social integration. Project partners have expertise in engineering, computer science, economics, law, political science, urban, media, and social studies; and close links with successful Community Networks like guifi.net, ninux.org, and sarantaporo.gr.

Activities around netCommons ideas are still going on in ANS group in Brescia in collaboration with Leonardo Maccari, now at the University Ca’Foscari in Venice and other netCommons partners.