Designing Airport Terminal New Facilities by Exploiting Parallel Intelligence and Level of Service Framework

Terminal planning is an iterative cycle that tends to add new facilities based on operational challenges, forecasts, demand analysis, capacity assessment, technology requirements and strategic business objectives. The cornerstone of terminal design management is sustained capacity, which correlates to sizing of subsystems thereby enhancing operational efficiency. The International Air Transport Association (IATA) redefined guidelines not only to reflect an optimum level of service (LoS) but also addressed capacity constraints for advanced concourse systems. On the other hand, parallel intelligence (PI) has gained popularity in terms of shifting the focus from digital twinning towards a highly adaptive tool, which can incorporate real time control function viz. decision making. This capability works on the principle of cognitive intelligence for computing big data via an orchestrated network of field sensors and edge devices. The purpose of this exploratory research is to propose a pragmatic approach that can perform data aggregation of PI nodes and the IATA LoS analytics. With this arrangement, the results will be more accurate, bespoke to a specific terminal and befitting the desired LoS criteria. The exploitation focussed on sample peak hour passenger forecasts for planning facilities and subsystems. The hypothesis is substantiated by means of numerical analysis, an illustrative configuration of PI architecture, and a histogram. The architecture proposed herein is scalable and promises a cost effective roadmap for ensuring optimal LoS while designing new facilities and subsystems. PI-based LoS framework is agile, and can be used for adaptive operations of airport terminal facilities for the future of aviation.