Dynamic resource management of civil protection department for Smart and Safe Tourism Destination

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Summary of the entity:

The Data Cycle Hub (DCH) is the one-stop reference shop DIH in the Valencia region to foster data-driven and artificial intelligence-based innovation. The objective is to bridge the gap between research and industry, specifically SMEs, providing innovative solutions and services that require advanced data analytics, automatic learning, and artificial intelligence.

The DCH is a member of several DIH networks, such as EUHubs4Data (coordinator), AI DIH Network, DIH4CPS, INNDIH (E-DIH of the Valencia region, coordinator), and was one of the 5 finalists to the DIHNET DIH Champions Challenge 2019 and 2020. The DCH is coordinated by ITI – Instituto Tecnológico de Informática, a Research & Technology center specializing in ICT, located in Valencia, Spain. ITI provides a Big Data Space offering infrastructure, tools, and data for research and experimentation with Big Data Technologies, which has been awarded the BDVA i-Space Silver label and is a crucial infrastructure for the Data Cycle Hub.

This challenge has been defined together INVAT·TUR (Institute of Tourism Technologies of Region of the Valencia), a center conceived as a meeting platform for all agents in the tourism sector and represented one of the main axes in improving the competitiveness and sustainability of the tourism model of the Region of Valencia. The goals are to develop lines of action in R+D+i adapted to the needs of the tourism sector, as well as transfer knowledge to tourism companies and organizations, giving the tourism sector access to the most advanced knowledge, services, and technologies.

Summary of the challenge:

The aim is to develop a predictive tool that provides support to civil protection departments’ managers when sizing, allocating, and planning the emergency teams in order to contribute to the creation of Smart and Safe Tourism Destinations.

Description:

Smart Tourism Destinations is a concept that seeks to improve tourism services and experiences through innovative digital solutions. But a Smart Destination is also one that provides safe experiences. And, in a climate change situation in which more frequent adverse weather events will happen, it is necessary to optimize the resources associated with civil protection and emergencies.

Natural disasters pose serious threats too large urban areas, therefore understanding and predicting human movements is critical for evaluating a population’s vulnerability and resilience and developing plans for disaster evacuation, response, and relief. On the one hand, having a good knowledge of the mobility patterns associated with public transport systems, such as having both daily and real-time forecasts of the occupancy levels of the different modes of transport, can be very useful. On the other hand, tourism can significantly modify the amount and distribution of people over time and space in a city or a region, with the power of transforming a low-risk situation into a real emergency. Therefore, public transport mobility patterns and tourism information are features to be considered in the civil protection strategy.

Based on historical data on mobilizations, interventions, and emergencies in the area of civil protection, weather alerts, public transport information, tourism information, and events in a city or region, the aim is to obtain a predictive geospatial model of the probability of an increase or decrease in the different types of emergency situations in a 15-day time frame, with the aim of providing support to managers when sizing emergency teams.

Data:

REACH Data Providers

• Bilbao City Council – Security department: dataset with Firefighter interventions, events in Bilbao, and weather alerts in Bilbao area.

• Bilbao City Council – Mobility department: dataset with real-time information of public transport system.

• JOT Internet Media: Keyword lists and statistics for mobile and laptop campaigns

• PLAY&GO: Fallas (objectives & ratings). Two datasets providing mobility and user experience data related to the Fallas, one of the most relevant regional touristic festivities in Valencia city, brought from a dedicated outdoor gamified sightseeing guide from Play&Go. Data includes points of interest, ratings, geoposition, objectives achieved (as attractive).

• Turisme Comunitat Valenciana – INVAT.TUR: Tourism Dataset Region of Valencia. Different datasets could be provided, under a private agreement with the applicants. Datasets dealing with: source of tourism flows to Valencia region and some of the factors influencing them (source countries, age, language, climate, safety, satisfaction), tourism products (main products, product satisfaction, sentiment analysis, gender and age distribution, language per product, …), attractiveness factors, accommodations (prices, customer reviews, satisfaction, flights (capacity, prices).

Open source datasets:

• Open Source: Valencia City open data portal, with transport and tourism datasets http://gobiernoabierto.valencia.es/en/data/

• Open Source: Valencia City public transport mobility data (EMT http://transitfeeds.com/p/emt-valencia/719 MetroValencia http://transitfeeds.com/p/ferrocarriles-de-la-generalidad-valenciana/1039

• Open Source: Valencia Region data portal, including tourism data and others http://www.dadesobertes.gva.es/es/dataset

• Open Source: Spain open data portal, including tourism data and others https://datos.gob.es/en/catalogo?theme_id=turismo

• Open Source: Basque weather open data portal 

https://www.euskalmet.euskadi.eus/servicios/open-data/ 

Other datasets could be used if needed, such as end-users bringing their daily data on which to train and test the solution developed.

Expected outcomes:

Predictive geospatial model of the increase or decrease of probability of the different types of interventions.