Tra il 2015 ed il 2018, presso ICAR-CNR, ho collaborato alle attività del progetto:
finanziato dal Governo Italiano, PON Ricerca e Competitività 2007-2013.
In questo progetto, ho coordinato l’unità ICAR-CNR per l’attività A1.3 “Piattaforma social-pervasive per applicazioni adattative context aware”.
I miei contributi principali hanno in particolare riguardato:
- Progettazione ed implementazione piattaforma software ad agenti distribuita “isapiens“, per lo sviluppo di cyber-physical systems e smart environments.
- Progettazione algoritmi e soluzioni per ambient assisted living.
- Progettazione algoritmi e soluzioni per monitaraggio strutture.
Alcune pubblicazioni scientifiche correlate sono riportate di seguito:
1.
Cicirelli, F.; Guerrieri, A.; Mercuri, A.; Spezzano, G.; Vinci, A.
ITEMa: A methodological approach for cognitive edge computing IoT ecosystems Journal Article
In: Future Generation Computer Systems, vol. 92, 2019, ISSN: 0167739X.
@article{Cicirelli2019c,
title = {ITEMa: A methodological approach for cognitive edge computing IoT ecosystems},
author = {F. Cicirelli and A. Guerrieri and A. Mercuri and G. Spezzano and A. Vinci},
doi = {10.1016/j.future.2018.10.003},
issn = {0167739X},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
journal = {Future Generation Computer Systems},
volume = {92},
abstract = {The ever-increasing spread of Internet of Things (IoT)-based technologies paired with the diffusion of the edge-based computing boosts the development of pervasive cyber ecosystems having the goal of improving the life quality of people and assisting them in daily activities. In this context, cognitive behaviors are purposely required to make such ecosystems able to adapt to people needs and to envisage their behaviors. Despite the growing interest in cognitive ecosystems, still there is a lack of methodological approaches devoted to supporting the design and implementation of such complex systems. This paper proposes ITEMa, an Iot-based smarT Ecosystem Modeling Approach based on a three-layered architecture offering some well-suited abstractions tailored to the development of IoT-based ecosystems which exhibit cognitive behaviors and are able to exploit computational resources located either at the edge of the network or in the Cloud. The effectiveness of the approach is demonstrated through a case study concerning the development of a Smart Office devoted to forecast some usual office activities and to properly adapt the office environmental conditions to them.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ever-increasing spread of Internet of Things (IoT)-based technologies paired with the diffusion of the edge-based computing boosts the development of pervasive cyber ecosystems having the goal of improving the life quality of people and assisting them in daily activities. In this context, cognitive behaviors are purposely required to make such ecosystems able to adapt to people needs and to envisage their behaviors. Despite the growing interest in cognitive ecosystems, still there is a lack of methodological approaches devoted to supporting the design and implementation of such complex systems. This paper proposes ITEMa, an Iot-based smarT Ecosystem Modeling Approach based on a three-layered architecture offering some well-suited abstractions tailored to the development of IoT-based ecosystems which exhibit cognitive behaviors and are able to exploit computational resources located either at the edge of the network or in the Cloud. The effectiveness of the approach is demonstrated through a case study concerning the development of a Smart Office devoted to forecast some usual office activities and to properly adapt the office environmental conditions to them.
2.
Cicirelli, Franco; Guerrieri, Antonio; Mastroianni, Carlo; Spezzano, Giandomenico; Vinci, Andrea (Ed.)
The Internet of Things for Smart Urban Ecosystems Book
Springer, 2019, ISBN: 978-3-319-96549-9.
@book{bookCGMSV2019,
title = {The Internet of Things for Smart Urban Ecosystems},
editor = {Franco Cicirelli and Antonio Guerrieri and Carlo Mastroianni and Giandomenico Spezzano and Andrea Vinci},
url = {https://doi.org/10.1007/978-3-319-96550-5},
doi = {10.1007/978-3-319-96550-5},
isbn = {978-3-319-96549-9},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
3.
Cicirelli, Franco; Fortino, Giancarlo; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea
Metamodeling of Smart Environments: from Design to Implementation Journal Article
In: Advanced engineering informatics, 2017, ISSN: 1474-0346.
@article{cic:advei:2017,
title = {Metamodeling of Smart Environments: from Design to Implementation},
author = {Franco Cicirelli and Giancarlo Fortino and Antonio Guerrieri and Giandomenico Spezzano and Andrea Vinci},
url = {www.sciencedirect.com/science/article/pii/S1474034616302063},
doi = {10.1016/j.aei.2016.11.005},
issn = {1474-0346},
year = {2017},
date = {2017-08-01},
urldate = {2017-08-01},
journal = {Advanced engineering informatics},
abstract = {A smart environment is a physical environment enriched with sensing, actuation, communication and computation capabilities aiming at acquiring and exploiting knowledge about the environment so as to adapt itself to its inhabitants' preferences and requirements. In this domain, there is the need of tools supporting the design and analysis of applications. In this paper, the Smart Environment Metamodel (SEM) framework is proposed. The framework allows to model applications by exploiting concepts specific to the smart environment domain. SEM approaches the modeling from two different points of view, namely the functional and data perspectives. The application of the framework is supported by a set of general guidelines to drive the analysis, the design and the implementation of smart environments. The effectiveness of the framework is shown by applying it to the modeling of a real smart office scenario that has been developed, deployed and analyzed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A smart environment is a physical environment enriched with sensing, actuation, communication and computation capabilities aiming at acquiring and exploiting knowledge about the environment so as to adapt itself to its inhabitants' preferences and requirements. In this domain, there is the need of tools supporting the design and analysis of applications. In this paper, the Smart Environment Metamodel (SEM) framework is proposed. The framework allows to model applications by exploiting concepts specific to the smart environment domain. SEM approaches the modeling from two different points of view, namely the functional and data perspectives. The application of the framework is supported by a set of general guidelines to drive the analysis, the design and the implementation of smart environments. The effectiveness of the framework is shown by applying it to the modeling of a real smart office scenario that has been developed, deployed and analyzed.
4.
Cicirelli, Franco; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea; Briante, Orazio; Iera, Antonio; Ruggeri, Giuseppe
Edge Computing and Social Internet of Things for large-scale smart environments development Journal Article
In: IEEE Internet of Things Journal, vol. PP, no 99, pp. 1-1, 2017, ISSN: 2327-4662.
@article{iotj2017,
title = {Edge Computing and Social Internet of Things for large-scale smart environments development},
author = {Franco Cicirelli and Antonio Guerrieri and Giandomenico Spezzano and Andrea Vinci and Orazio Briante and Antonio Iera and Giuseppe Ruggeri},
doi = {10.1109/JIOT.2017.2775739},
issn = {2327-4662},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {IEEE Internet of Things Journal},
volume = {PP},
number = {99},
pages = {1-1},
abstract = {Large-scale Smart Environments (LSEs) are open and dynamic systems typically extending over a wide area and including a huge number of interacting devices with a heterogeneous nature. Thus, during their deployment scalability and interoperability are key requirements to be definitely taken into account. To these, discovery and reputation assessment of services and objects have to be added, given that new devices and functionalities continuously join LSEs. In spite of the increasing interest in this topic, effective approaches to develop LSEs are still missing. This paper proposes an agent-based approach that leverages Edge Computing and Social Internet of Things paradigms in order to address the above mentioned issues. The effectiveness of such an approach is assessed through a sample case study involving a commercial road environment.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Large-scale Smart Environments (LSEs) are open and dynamic systems typically extending over a wide area and including a huge number of interacting devices with a heterogeneous nature. Thus, during their deployment scalability and interoperability are key requirements to be definitely taken into account. To these, discovery and reputation assessment of services and objects have to be added, given that new devices and functionalities continuously join LSEs. In spite of the increasing interest in this topic, effective approaches to develop LSEs are still missing. This paper proposes an agent-based approach that leverages Edge Computing and Social Internet of Things paradigms in order to address the above mentioned issues. The effectiveness of such an approach is assessed through a sample case study involving a commercial road environment.
5.
Cicirelli, Franco; Fortino, Giancarlo; Giordano, Andrea; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea
On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment Journal Article
In: Journal of medical systems, vol. 40, no 9, pp. 200, 2016, ISSN: 0148-5598.
@article{cicirelli2016design,
title = {On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment},
author = {Franco Cicirelli and Giancarlo Fortino and Andrea Giordano and Antonio Guerrieri and Giandomenico Spezzano and Andrea Vinci},
doi = {doi:10.1007/s10916-016-0549-7},
issn = {0148-5598},
year = {2016},
date = {2016-07-28},
urldate = {2016-07-28},
journal = {Journal of medical systems},
volume = {40},
number = {9},
pages = {200},
publisher = {Springer US},
abstract = {A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.