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SMAT - F1 and SMAT - F2

The SMAT Project: an Advanced Environment Monitoring System

SMAT main objective is to define, design and develop an Advanced Environment Monitoring System, based on Unmanned Air Systems (UAS). SMAT is a research project funded by the RegionePiemonte (Italy), managed by Finpiemonte and promoted through the Comitato Promotore del Distretto Aerospaziale Piemonte. It is also cofunded by Fondo europeo di sviluppo regionale (F.E.S.R.).

The first phase of SMAT denoted as SMAT F1 lasted 30 months and ended in September 2011.

SMAT F1 was leaded by Alenia Aermarcchi, other industrial partners were Selex Galileo (now Selex ES) and ALTEC supported by 11 SMEs. Research partners were Politecnico di Torino, Università di Torino and Istituto Mario Boella.

The goals and the overall organizations of the project are described in

while the results are summarized in

From a scientific point of view Dipartimento di Informatica was involved in the activities on Mission Planning and Mission Management, Data Modelling and Meta Data Retrieval. Meta Data Retrieval had the purpose to produce a enrichment and characterization of the cartography by selection of the features that are peculiar of the territory if compared to the neighborhood. The mainresults are reported in:

  • R. Meo, E. Roglia, A. Bottino, The Exploitation of Data from Remote and Human Sensors for Environment Monitoring in the SMAT Project, in Sensors Journal, MDPI, 2012, 12(12), 17504-17535. doi: 10.3390/s121217504.
  • R.Meo, E.Roglia, E.Ponassi, MetaData Retrieval: A Software Prototype for the Annotation of Maps
    with Social Metadata, in Proceedings of 26th ECML/PKDD (ECML/PKDD 2011), LNCS vol. 6913,
    pp. 642-645, Athens, Greece, 5-9 September, 2011.
  • R.Meo, E.Roglia, E.Ponassi, MetaData Retrieval: Annotation of Geo-Referenced Maps with Social
    Metadata in Support to Unmanned Aircraft Vehicles Missions, in Proceedings of 2011 NASA
    Conference on Intelligent Data Understanding (CIDU 2011), extended abstract, pp.2,
    Moutain View, CA, 19-21 October, 2011.

As concerns Mission Planning and management the main goal was to develop an intelligent support system for the Human operator responsible for mission planning. In particular,the system is able to check the validity of the mission plan with respect to the requests of target observation, by taking into account the temporal and resource constraints. The support system is also able in some case to suggest how to revise the mission plan in case some of the constraints are violated. The main results are reported in:

The second phase of SMAT (denoted as SMAT F2) is funded by the RegionePiemonte (Italy) and Fondo Europeo di Sviluppo Regionale (F.E.S.R.). The project lasts from January 2013 to September 2015 and is led by Alenia Aermacchi. The project involves Selex ES, ALTEC, 13 SMEs, Politecnico di Torino, Università di Torino, CNR-IRPI and ISMB.

The SMAT-F2 project is designed to address a number of technological and procedural macro-themes: Development of autonomous capabilities to support the Remote Pilot, which will allow the system to perform certain tasks autonomously,

  • Sensor & Payload Management Development and Integration of sensors and related management logic, to carry out the monitoring mission.
  • Extension of the functionalities of the Station of Supervision and Coordination (SSC) both as concerns the capabilities of mission planning (starting from end-user requirements) and Data Exploitation Development (processing capabilities of the acquired data.

For more information look at

Within SMAT F2, the Dipartimento di Informatica isinvolved in:

  • Design and development of the Planning component of the SSC which has to take into consideration End-user requests, availability of the RPAs in the fleet, sensor suite configuration on board of the RPAs, temporal and resource constraints for singling out an hypothesis of mission plan possibly involving multiple RPAs.
  • Retrieval of metadata on geographic entities from crowdsourcing and open data sources for the generation and publication of geo-summaries. The project involves crawling, cleaning and preparation of metadata, mapping of ontologies of metadata sources for the fusion of metadata from multiple sources (OpenStreetMap and Foursquare), clustering in a multidimensional model of the georeferred metadata, optimization ) of the clusters by Pareto optimization strategy (Pareto front), evaluation of the geo-summaries with crowdsourcing strategies.

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