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Designing AI-based platforms that provide personalized recommendations for eco-friendly travel options. An AI considers factors such as climate-friendly transportation, eco-friendly accommodations, and responsible tourism practices. Helps travelers minimize their environmental impact before and/or during travel. 

Example 1

I'm seeking a hotel suitable for a two-week family holiday in May, accommodating two adults and two children. The ideal establishment would offer child-friendly amenities, including a swimming pool and an entertainment team. Our preferred travel duration is no more than six hours. We anticipate a location with minimum temperatures of 20 degrees and predominantly sunny weather. 

Example 2

Kids have school holiday in a month and our family of 4 wants to go on a week holiday with no more than combined 5h travel one way. Something warm like Mallorca but, if possible, no flying. Separate rooms for kids, preferably one apartment or big suite. If an electric car is possible, I’d like to rent one for us, big enough for all of us and a load station at the hotel. 

Example 3

Flights are too expensive to go to Paris and I’d like to take my partner there. What's the best way to go there when ist not too hot and crowded without flying? I’d like to make it into a trip with sightseeing but also eating in restaurants in local areas and staying a bit outside the main tourist areas. Budget per night is 150 CHF for hotel.  

All data is provided in JSON format, with a supporting schema containing detailed field descriptions for data interpretation and manipulation. You can find this in the zip file 'hotelplancase.zip'.

Data export contains all geographical and hotel data available to be booked on hotelplan.ch. The export is a directed acyclic graph that has the following structure:

You will have access to a wealth of structured and unstructured data relating to geographical entities and associated products.

Since exporting graph is not easily done using a simple json document without duplicating tons of data, the export is provided in a tree form with optional relationships only listing node ids:

continents
  all attributes of continents
  countryGroups
    all attributes of countryGroups
    countries
      id
  countries
    all attributes of countries
    regions
      destionations
        id
    destionations
      all attributes of destinations
      resorts
       all attributes of resorts
         hotels
           all attributes of hotels

Each node within this tree structure holds a set of structured attributes, including: 

• Boolean Flags: Binary attributes indicating specific resort features, such as the presence of a "sandy-beach" or a "cobble-stone-beach", and others. 
• Numerical Values: Quantifiable metrics such as the average number of sunny hours per day in a given month, and others. 

The unstructured attributes: 

• Text: Free-form "LeadText" descriptions providing detailed insights about geographical nodes and related products. 
• Images: Visual content showcasing geographical objects and products. 

Field descriptions and types

GraphQL schema with field descriptions is in the enclosed file `schema.graphql`. You can use this schema for reference only or feed it to a code generator (e.g.https://the-guild.dev/graphql/codegen) so that it's easier to parse.

The root type is `FdrGeoResponse`.
 

Generating links to hotelplan.ch

You can use `https://www.hotelplan.ch/<publicId>` URL to navigate users to a specific object on our website.

For example, a hotel with `publicId` of `h-826` can be accessed via a URL of https://www.hotelplan.ch/h-826.

In addition to the provided data, participants are encouraged to incorporate relevant external data sources to enrich their solutions. This open-data approach will enable the creation of more comprehensive and accurate AI-driven recommendations. These external data sources may include carbon dioxide emissions data, sustainable route information from mapping APIs, data on local sustainable practices, climate data, and sustainability ratings from trusted third-party sources. 

Some API examples:  

• Carbon Interface | Docs: Generate accurate emissions estimates from flights, vehicles, shipping, electricity consumption and fuel combustion.  
• Introduction (openaq.org): Access air quality data on the OpenAQ Platform. Data on the OpenAQ platform are available free and open source. 
• NREL: Developer Network: Access and use energy data via Web services, including renewable energy and alternative fuel data. 
• AirVisual API | Trusted Live and Forecast Air Pollution Data (iqair.com): Accurate local air quality and weather data. 
• Dark Sky API Documentation (darkskyapis) | RapidAPI: Observed in the past or forecasted in the future hour-by-hour weather and daily weather conditions for a particular date.