Periodic Reporting for period 1 - SOM (Statistical modeling for Optimization Mobility)
Okres sprawozdawczy: 2016-10-01 do 2018-03-31
The objective of this project was to bring to practice better software and internet services related to mobility in the general sense such as ride sharing, navigation systems, crowdsourcing and the use of GPS-enabled mobile devices.
Three key competitive advantages of our approach are (1) the privacy one gets in contrast with most cloud-based platforms where all data is centrally collected, (2) the saving of computational costs by distributing computations to devices having much more detailed information than what one can centrally collect, and (3) the fact that most services work with current traffic information, while we work with future travel intentions, allowing for planning better ahead.
We have improved our network, and had in-depth discussions with industrial partners, including car OEMs, data brokers, service providers and developers of new technology such as autonomous cars. In general, we found a very important development increasing the need for technology such as ours, is the rapidly increasing volume of data generated by cars and mobile devices, making local computation and distributed analysis more desirable. Together with a selected set of industrial partners we have developed concrete use cases, and pilot studies to demonstrate the feasibility of our technology for these use cases.
The project has lead to several follow-up initiatives where the technology will be further tested, improved, and embedded in existing services and business models.
Three key competitive advantages of our approach are (1) the privacy one gets in contrast with most cloud-based platforms where all data is centrally collected, (2) the saving of computational costs by distributing computations to devices having much more detailed information than what one can centrally collect, and (3) the fact that most services work with current traffic information, while we work with future travel intentions, allowing for planning better ahead.
We have improved our network, and had in-depth discussions with industrial partners, including car OEMs, data brokers, service providers and developers of new technology such as autonomous cars. In general, we found a very important development increasing the need for technology such as ours, is the rapidly increasing volume of data generated by cars and mobile devices, making local computation and distributed analysis more desirable. Together with a selected set of industrial partners we have developed concrete use cases, and pilot studies to demonstrate the feasibility of our technology for these use cases.
The project has lead to several follow-up initiatives where the technology will be further tested, improved, and embedded in existing services and business models.