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MobilitySquare

Sustainable Mobility Recommendation Engine for Tourism

COMPANY
iMpronta
DOMAIN
Sustainable Mobility, Tourism
COUNTRY
Italy
YEAR
2022
Mobility-Square

DESCRIPTION

The purpose of the experiment is the creation of a Reccomendation Enegine for e-bike rental which could do the following actions:
1) Forecast the number of reservation in a specific rental point depending on the weather forecast and so recommend other destinations in case of bad-weather or overbooking
2) Reccomend to the user interesting things to do based on the existing partners and points visited so far. Reccomend interchange with the train at local train stations in order to avoid car trips.

 

I-Space Coach

 

I-Spaces Involved

Main Objectives

Create a Reccomendation Enegine for e-bike rental which could do the following actions:

1) Forecast the number of reservation in a specific rental point depending on the weather forecast and so recommend other destinations in case of bad-weather or overbooking

2) Reccomend to the user interesting things to do based on the existing partners and points visited so far. Reccomend interchange with the train at local train stations in order to avoid car trips.

Main innovations

Using weather information and positions of the e-bikes in order to forecast and suggest solutions to the users, in order to reduce their impact on the environment

Impacts

We aim at using data to promote a zero-pollution choice for the tourists and increase the attractiveness of e-bikes+train instead of
cars.
The basic idea is to provide a solution to travel to rural areas with zero-pollution. The user who wants to visit a destination can get
the recommendation to get to a train station where he or she can pickup an e-bike and reach his/her final destination with no
impact.
The recommendation engine will use the historical data about reservations, anonymized routes of the users and weather forecasts to increase the probability to make in interesting proposal and so generate a green travel. 

Key Exploitable Results (KERS)

Define an algorithm which combines the weather information with the historical data about reservation and allow a reliable prediction in the e-bike market.

Create a reccomendation engine which will propose what to visit in a specific destinations

Technical KPIS

1) forcast number of correctly predicted cancellations (85% accuracy at the end of the experiment)
2) 25M of GPS data processed by the reccomendation engine

COMPANY INFO

iMpronta is a small company founded in 2003 with a focus on and main milestones Sustainability and Computer Engineering. At the moment counts 9 people, all with a master degree (4 computer engineers, 2 communication scientist, 1 environmental scientist, 1 architect, 1 accountant)
Starting in 2009 iMpronta has focussed in the field of cycling tourism and solutions for sustainable mobility.
Since 2014 we have run a small rental shop in the Langhe Region (north west of Italy), with the aim of creating a rental network,
which actually was born in 2016 with BikeSquare.
At the moment BikeSquare is the company running al the e-bike rental business, while iMpronta acts as the technology consultancy developing the innovative solutions for the Rental Business.