Tags RICE.Edu
“Rice University computer scientists are mapping a new solution for interior navigational location detection by linking it to existing sensors in mobile devices. Their results were presented in a paper at last month’s 2017 Design, Automation and Test in Europe (DATE) Conference in Lausanne, Switzerland. Six months ago, the same researchers published a paper on their first technology for a new indoor mobile positioning system called CaPSuLe. The navigational location detection system began as a solution for mobile device users inside large indoor spaces like office complexes or shopping malls where GPS navigation falters under poor signals that quickly deplete battery life. Both CaPSuLe and the DATE paper technology rely on machine learning for location detection. Both increase the speed of calculations and decrease energy expenditure in comparison with existing location technologies. But CaPSuLe depends on image matching techniques and uploaded data, while the new technology taps into sensors that already exist in most mobile devices. Chen Luo, a graduate student working with assistant professor of computer science Anshumali Shrivastava, said the team was not satisfied with the initial performance metrics of its sensor-driven technology.”