AEGIS App: Wildfire Information Management for Windows Phone Devices

AbstractNovel technological advances in mobile devices and applications can be exploited in wildfire confrontation, enabling end-users to easily conduct several everyday tasks, such as access to data and information, sharing of intelligence and coordination of personnel and vehicles. This work describes an innovative mobile application for wildfire information management that operates on Windows Phone devices and acts as a complementary tool to the web-based version of the AEGIS platform for wildfire prevention and management. Several tasks can be accomplished from the AEGIS App, such as routing, spatial search for closest facilities and firefighting support infrastructures, access to weather data and visualization of fire management data (water sources, gas refill stations, evacuation sites etc.). An innovative feature of AEGIS App is the support of these tasks by a digital assistant for artificial intelligence named Cortana (developed by Microsoft for Windows Phone devices), that allows information utilization through voice commands. The application is to be used by firefighting personnel in Greece and is potentially expected to contribute towards a more sophisticated transferring of information and knowledge between wildfire confrontation operation centers and firefighting units in the field

Taking SPARQL 1.1 extensions into account in the SWIP system

International audienceThe SWIP system aims at hiding the complexity of expressing a query in a graph query language such as SPARQL. We propose a mechanism by which a query expressed in natural language is translated into a SPARQL query. Our system analyses the sentence in order to exhibit concepts, instances and relations. Then it generates a query in an internal format called the pivot language. Finally, it selects pre-written query patterns and instantiates them with regard to the keywords of the initial query. These queries are presented by means of explicative natural language sentences among which the user can select the query he/she is actually interested in. We are currently focusing on new kinds of queries which are handled by the new version of our system, which is now based on the 1.1 version of SPARQL

The usability of semantic search tools: a review

The goal of semantic search is to improve on traditional search methods by exploiting the semantic metadata. In this paper, we argue that supporting iterative and exploratory search modes is important to the usability of all search systems. We also identify the types of semantic queries the users need to make, the issues concerning the search environment and the problems that are intrinsic to semantic search in particular. We then review the four modes of user interaction in existing semantic search systems, namely keyword-based, form-based, view-based and natural language-based systems. Future development should focus on multimodal search systems, which exploit the advantages of more than one mode of interaction, and on developing the search systems that can search heterogeneous semantic metadata on the open semantic Web

Geospatial Semantics

Geospatial semantics is a broad field that involves a variety of research areas. The term semantics refers to the meaning of things, and is in contrast with the term syntactics. Accordingly, studies on geospatial semantics usually focus on understanding the meaning of geographic entities as well as their counterparts in the cognitive and digital world, such as cognitive geographic concepts and digital gazetteers. Geospatial semantics can also facilitate the design of geographic information systems (GIS) by enhancing the interoperability of distributed systems and developing more intelligent interfaces for user interactions. During the past years, a lot of research has been conducted, approaching geospatial semantics from different perspectives, using a variety of methods, and targeting different problems. Meanwhile, the arrival of big geo data, especially the large amount of unstructured text data on the Web, and the fast development of natural language processing methods enable new research directions in geospatial semantics. This chapter, therefore, provides a systematic review on the existing geospatial semantic research. Six major research areas are identified and discussed, including semantic interoperability, digital gazetteers, geographic information retrieval, geospatial Semantic Web, place semantics, and cognitive geographic concepts.Comment: Yingjie Hu (2017). Geospatial Semantics. In Bo Huang, Thomas J. Cova, and Ming-Hsiang Tsou et al. (Eds): Comprehensive Geographic Information Systems, Elsevier. Oxford, U

EUropean Heliospheric FORecasting Information Asset 2.0

Aims: This paper presents a H2020 project aimed at developing an advanced space weather forecasting tool, combining the MagnetoHydroDynamic (MHD) solar wind and coronal mass ejection (CME) evolution modelling with solar energetic particle (SEP) transport and acceleration model(s). The EUHFORIA 2.0 project will address the geoeffectiveness of impacts and mitigation to avoid (part of the) damage, including that of extreme events, related to solar eruptions, solar wind streams, and SEPs, with particular emphasis on its application to forecast geomagnetically induced currents (GICs) and radiation on geospace. Methods: We will apply innovative methods and state-of-the-art numerical techniques to extend the recent heliospheric solar wind and CME propagation model EUHFORIA with two integrated key facilities that are crucial for improving its predictive power and reliability, namely (1) data-driven flux-rope CME models, and (2) physics-based, self-consistent SEP models for the acceleration and transport of particles along and across the magnetic field lines. This involves the novel coupling of advanced space weather models. In addition, after validating the upgraded EUHFORIA/SEP model, it will be coupled to existing models for GICs and atmospheric radiation transport models. This will result in a reliable prediction tool for radiation hazards from SEP events, affecting astronauts, passengers and crew in high-flying aircraft, and the impact of space weather events on power grid infrastructure, telecommunication, and navigation satellites. Finally, this innovative tool will be integrated into both the Virtual Space Weather Modeling Centre (VSWMC, ESA) and the space weather forecasting procedures at the ESA SSCC in Ukkel (Belgium), so that it will be available to the space weather community and effectively used for improved predictions and forecasts of the evolution of CME magnetic structures and their impact on Earth. Results: The results of the first six months of the EU H2020 project are presented here. These concern alternative coronal models, the application of adaptive mesh refinement techniques in the heliospheric part of EUHFORIA, alternative flux-rope CME models, evaluation of data-assimilation based on Karman filtering for the solar wind modelling, and a feasibility study of the integration of SEP models.</p