Publications

@article{augelloDisasterPreventionVirtual2016,

title = {Disaster Prevention Virtual Advisors through Soft Sensor Paradigm},

author = { Agnese Augello and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},

editor = { Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},

doi = {10.1007/978-3-319-39345-2_55},

issn = {21903018},

year  = {2016},

date = {2016-01-01},

journal = {Smart Innovation, Systems and Technologies},

volume = {55},

pages = {619--627},

abstract = {In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. textcopyright Springer International Publishing Switzerland 2016.},

keywords = {Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems},

pubstate = {published},

tppubtype = {article}

}

@article{augello_disaster_2016,

title = {Disaster prevention virtual advisors through soft sensor paradigm},

author = {Agnese Augello and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},

editor = {Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977119923&doi=10.1007%2f978-3-319-39345-2_55&partnerID=40&md5=a54a699ddea48ce7e9ab353ef5ce4ba0},

doi = {10.1007/978-3-319-39345-2_55},

issn = {21903018},

year  = {2016},

date = {2016-01-01},

journal = {Smart Innovation, Systems and Technologies},

volume = {55},

pages = {619–627},

abstract = {In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. © Springer International Publishing Switzerland 2016.},

keywords = {Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems},

pubstate = {published},

tppubtype = {article}

}