Research Article
Developing Data Model Managing Residents by Space and Time in Three-Dimensional Geographic Space
@INPROCEEDINGS{10.1007/978-3-030-67101-3_7, author={Dang Van Pham}, title={Developing Data Model Managing Residents by Space and Time in Three-Dimensional Geographic Space}, proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 9th EAI International Conference, ICCASA 2020, and 6th EAI International Conference, ICTCC 2020, Thai Nguyen, Vietnam, November 26--27, 2020, Proceedings}, proceedings_a={ICCASA \& ICTCC}, year={2021}, month={1}, keywords={Relations Spatial - temporal - residential data model STRDM Queries Geographic location Managing residents}, doi={10.1007/978-3-030-67101-3_7} }- Dang Van Pham
Year: 2021
Developing Data Model Managing Residents by Space and Time in Three-Dimensional Geographic Space
ICCASA & ICTCC
Springer
DOI: 10.1007/978-3-030-67101-3_7
Abstract
A major challenge currently of levels of government and construction contractors is how to manage population growth by geographic location and over time. The population increases by geographic location and over time leading to the increase of positive and negative aspects in the community. Managing people living and working on the territory by space and time is a very important and urgent job. The levels of government must regularly manage the people living and working on their localities, which are always associated with the management of permanent populations, temporary populations, blood relations, social relations, previous conviction relations, previous offence relations and birth or death relations that all of this management takes place at a specific geographic location and time. The paper proposes to develop a spatial - temporal - residential data model that is capable of managing human activities at the place of residence, at the workplace and at the location of the relations by geographic location and over time, this model is called STRDM. The paper illustrates empirical results with visual forms through the use of queries by space, time, resident, and search for ancestor and descendant. These empirical results show that it can be applied to residential data management systems in new urban areas.
