Abstract:
The incessant advancements in location tracking technologies have brought up spatiotemporal datasets being vital in real time usage (e.g., tracking, monitoring, and decision making etc.). In addition, spatiotemporal datasets can be used to extract certain patterns, configuration of routes and different scenarios depending upon different temporal behaviors found in the datasets. To fulfil the need of achieving spatiotemporal database management systems, several platforms like Hadoop, SECONDO and the most recent MobilityDB have been developed by researchers to resolve this challenge of information extraction. Apart from the rest, MobilityDB an extension of PostGIS, is the first ever commercially available moving objects’ database having the capability to incorporate mobility datasets and perform complex pattern extraction using spatiotemporal queries. Building trajectories is one of the important features of MobilityDB. This study has got its uniqueness on the basis that no research has yet been carried out on flights dataset, to the best of our knowledge. In this study, we have used Pakistan International Airlines (PIA) flights dataset to build aircraft trajectories using MobilityDB with the objective to explore the trajectories for optimizing air operations based upon different parameters including aircraft taxiing time, flight diversion, monitoring flight routes and distance among different flights in the air etc. The methodology used in the study is simple and adaptable for the new researchers for future enhancements in the research area. The results produced by the study have highlighted different areas of improvements in air operations. We found that minimizing taxiing time at Islamabad and Lahore International airports will have a good impact on air operations. The policy / decision maker would be getting more informed and well intime decisions based upon the statistics and facts to improve air operations of PIA and Pakistan.
