Catalyst Project: Indoor Moving Objects Trajectory Generation and Query Evaluation

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Catalyst Projects provide support for Historically Black Colleges and Universities to work towards establishing research capacity of faculty to strengthen science, technology, engineering and mathematics undergraduate education and research. It is expected that the award will further the faculty member's research capability, improve research and teaching at the institution, and involve undergraduate students in research experiences. This project at Tuskegee University seeks to develop an indoor data-based tracking framework designed to understand the mathematical and technological foundations of indoor data management. The project provides an opportunity for undergraduate students to enhance their education through research experiences in computer modeling and data management techniques. The researcher has established a strong collaboration with faculty at Auburn University. This project will result in the development of a number of indoor query evaluation mechanisms and the techniques to derive the accurate locations of indoor moving items from raw erroneous indoor tracking data. This will improve the accuracy of indoor spatial queries, which can support many indoor high-level applications, including indoor location-based service and hotspot finding. Novel indoor tracking data management techniques will be devised. The goals of the project are to: 1) implement a simulation toolkit and a prototype system, where many indoor environments and deployment settings will be simulated for performance evaluation; 2) develop and compare a number of machine learning-based location inference methods for accurate trajectory generation in indoor environments; 3) design novel indoor query evaluation algorithms for various types of queries, in particular spatial query types such as range query and nearest neighbor query; and 4) invent an error model-based approach for indoor object trajectory tracking which is a non-machine learning approach. The results of this research will improve the performance of number of indoor location-based application which will make it easy to locate people and help to guide people to safety during emergency situations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.