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ACTIONABLE BUSINESS INTELLIGENCE UPON POPULATION MOBILITY PATTERNS ANALYSIS

Project description

Forecasting mobility patterns of the general population

Big Data can be used by stakeholders for planning and managing effective actions. Striving to make this a reality, the EU-funded DEMOGRAPHICA project envisions an algorithm that could analyse collective human behaviour and produce per-location, per-time-frame, actionable and reliable predictions fully customised to a client’s market needs. To forecast mobility patterns of the general population, the project makes use of socio-thermodynamics to analyse the complex, massive and anonymised data provided by mobile network operators. This will benefit vertical markets where an understanding of mobility patterns guides decision-making and can improve various key performance indicators for smart cities and a wide range of sectors.

Objective

What if an algorithm could analyse collective human behaviour and produce per-location, per-time-frame, actionable and reliable predictions fully customised as per each clients’ market needs? This would benefit all those verticals that depend on mobility patterns to plan effective actions. Marketers would count with tools to design efficient and viral advertising, awareness or fundraising campaigns. Smart- cities/Municipalities’ mobility and tourism responsibles would count with scientific tools to effectively put into practice their politics. Toll-roads planners/managers would count with reliable tools to manage actions.
DEMOGRAPHICA makes use of socio-thermodynamics to analyse the complex, massive and anonymised data (i.e. Call Detail Records -CDR-) provided by Mobile Network Operators (MNOs) to forecast mobility patterns of general population. This allows us to understand and reliably forecast citizens’ mobility patterns without violating their privacy. This is useful in many verticals where understanding these mobility patterns is essential to drive informed decisions and improve different KPIs (key performance indicators), from profitability to service level, especially in the whole world of smartcities, and particularly in some niches of this big market such as Transportation, Tourism and Out-of-Home Marketing, but it also has application in other sectors such as Health (epidemics evolution prediction), energy or cybersecurity, to mention a few.

Call for proposal

H2020-EIC-SMEInst-2018-2020

See other projects for this call

Sub call

H2020-SMEInst-2018-2020-2

Coordinator

KIDO DYNAMICS SA
Net EU contribution
€ 1 024 884,00
Address
AVENUE DE SEVELIN 46
1004 LAUSANNE
Switzerland

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Schweiz/Suisse/Svizzera Région lémanique Vaud
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
€ 2 039 120,00

Participants (1)