Flight Schedule Research Articles

Intelligent algorithms applied to the prediction of air freight transportation delays

PurposeThe objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.Design/methodology/approachThe research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).FindingsShipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.Originality/valueThese findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

Integrating Flight Scheduling, Fleet Assignment, and Aircraft Routing Problems with Codesharing Agreements under Stochastic Environment

Airlines face the imperative of resource management to curtail costs, necessitating the solution of several optimization problems such as flight planning, fleet assignment, aircraft routing, and crew scheduling. These problems present some challenges. The first pertains to the common practice of addressing these problems independently, potentially leading to locally optimal outcomes due to their interconnected nature. The second challenge lies in the inherent uncertainty associated with parameters like demand and non-cruise time. On the other hand, airlines can employ a strategy known as codesharing, wherein they operate shared flights, in order to minimize these challenges. In this study, we introduce a novel mathematical model designed to optimize flight planning, fleet assignment, and aircraft routing decisions concurrently, while accommodating for codesharing. This model is formulated as a three-stage non-linear mixed-integer problem, with stochastic parameters representing the demand and non-cruise time. For smaller-scale problems, optimization software can effectively solve the model. However, as the number of flights increases, conventional software becomes inadequate. Moreover, considering a wide array of scenarios for stochastic parameters leads to more robust results; however, it is not enabled because of the limitations of optimization software. In this work, we introduce two new simulation-based metaheuristic algorithms for solving large-dimensional problems, collectively called “simheuristic.” These algorithms integrate the Monte Carlo simulation technique into Simulated Annealing and Cuckoo Search. We have applied these simheuristic algorithms to various problem samples of different flight sizes and scenarios. The results demonstrate the efficacy of our proposed modeling and solution approaches in efficiently addressing flight scheduling, fleet assignment, and aircraft routing problems within acceptable timeframes.

Issues facing Osaka International Airport and its dialogues with the surrounding communities

Osaka International Airport is an urban airport located close to the city center, and its operating hours are set at 14 hours, from 7:00 to 21:00. In the past, the airport had conflicts with local residents over aircraft noise. Even today, the airport needs to pay careful attention to the communities to ensure smooth operation of the noise-generating airport. The flight schedule is set to allow enough time for takeoffs and landings in order not to exceed 21:00 based on the agreements with the surrounding communities; however, recently there have been many delayed flights, takeoffs and landings outside of the operating hours, due to weather conditions or for other unavoidable reasons. We have gained a certain level of understanding of the surrounding communities for delayed flights by sharing appropriate information and holding regular dialogues with them. In addition, Osaka International Airport has set specific flight paths called noise preferential routes to minimize the impact of aircraft noise around the airport and is using a system to monitor deviations from NPRs. This presentation is to introduce the current status of these activities and methods for properly analyzing the information to provide to the community.

Towards a resilience assessment framework for the airport passenger terminal operations

Airport terminals can generate and intensify the undesired phenomena that take place on transportation networks in the wake of disruptive events. The more resilient a terminal is, the more easily it will bounce back to the desired state, causing less nuisance to the users. In this study, we expand the state-of-the-art airport terminal resilience assessment through fast-time simulation and tailored resilience metrics. From the point of view of simulation, we establish delay management strategies based on flight schedule alterations as a response to a disruptive event. In the baseline scenario, no disruption is set, whereas passenger arrival to the airport is blocked for 1 or 2 h in the disrupted scenarios. A previously verified and validated simulation model of a Brazilian domestic airport was used to represent the passenger departing flow, encompassing check-in and security screening. From the resilience perspective, a systematic assessment procedure for new resilience metrics is unveiled, providing means for exploring the metrics’ formulations and their relationship to the operational strategies. Following the simulation runs, resilience metrics for individual passenger and aircraft delays were investigated, something yet scarcely explored in the literature. The results show that the proposed metrics deliver significantly different outcomes from those associated with the current literature. Consequently, we can conclude that a resilience assessment concerning the airport terminal that disregards individual delays may be missing important information. The systematic approach we propose is a contribution in that sense, even though this topic requires more research, considering the vast nature of the possible disruptive events and their subsequent operational impacts.

SINGLE CROSS-BORDER FREE ROUTE AIRSPACE CONCEPT IN THE ASEAN REGION

Single Cross-Border Free Route Airspace (FRA) represents the ultimate long-term idealistic routing rules allowing airspace users freely plan a route in en-route airspace, which is not immediately possible from the administrative and technological point of view. In Single Cross-Border FRA, the whole ASEAN airspace is treated as a single-large FRA where all 12 Flight Information Regions (FIRs) implement FRA, with direct routing between the entry (horizontal entry into FIR or end of Standard Instrument Departure Route, SID) and the exit (horizontal exit from FIR or beginning of Standard Arrival Route, STAR). Single Cross-Border FRA is the most fuel-efficient reference that we could ever reach in the future.All otherhypothetical routing rules fall between the Single Cross-Border FRA and those hypo-thetical routing rules in terms of fuel efficiency. In this paper, we described the potential in fuel efficiency (or benefit achievement scaling) with refer-ence to this ultimate basic fuel requirement and scaled the excess fuel with different routings. We evaluated the fuel burn with a fast-time simulation (FTS) in 12 different scenarios (3 traffic volume levels × 4 routing scenarios). As for the traffic volume scenarios, we simulated 1-day of commercial ASEAN flight schedule data of 3 traffic volume levels (100%, 150%, and 200% of pre-COVID19 traffic volume). As for four routing scenarios with increasing levels of directness: conventional Air Traffic Service route network (ATS) (R1), hypothetical Several-Small FRA route network (R2), Single Cross-Border FRA route network with Danger Areas (R3) and Single Cross-Border FRA network without Danger Areas (R4). Results showed that flight time, fuel burn, and distance travelled were less in R2, R3, and R4 than in R1. There was an average difference of 2.2% in flight time, 1.9% in fuel burn, and 2.2% in distance travelled from R1 to R4.

The Chinese Aviation Network: An Empirical Temporal Analysis on Its Structural Properties and Robustness

Complex networks have encouraged scholars to develop an effective method for abstracting and optimizing aviation networks. However, researchers often overlook the aviation network’s temporal attribute and treat it as a static network. Aviation networks have strong temporal characteristics and the dynamic connection cannot be realistically described by a static network. It is necessary to more accurately and realistically represent these connections during the operation of an aviation network. This study explored temporal structures of the Chinese aviation temporal network (CATN) based on flight schedules and actual operational time data. Temporal networks based on time windows were represented to analyze the temporal topology features and robustness of the CATN. The results demonstrated the following: (1) based on the spatial-temporal aviation network, there is a morning departure peak (7:00–8:00) and an evening arrival peak at the airline hub (20:00–21:00); (2) examining the centrality of each airport in the CATN at various time intervals exposed fluctuations in their rankings, which could not be identified by a static network, and (3) the robustness of the CATN was found to be unaffected by time windows, but it displayed poor resilience against deliberate attacks, particularly when subjected to betweenness and closeness attacks, which target the network’s shortest paths. For obtaining a greater understanding of the operating situation of civil aviation, displaying the topological features and robustness of the temporal network is of great importance.

Competitive integrated airline schedule design and fleet assignment

Airline profits are significantly influenced by competitive timetables that match passenger demand to fleet resources. In this research, we develop an integrated, mixed-integer optimization model to derive a comprehensive flight schedule, fleet assignment, and average airfares jointly. Passenger choice behavior is incorporated through a prospect theory-adjusted, nested, multinomial logit model which estimates market share. The competitive fleet assignment and schedule design (CFSD) formulation is embedded in a differentiated Bertrand game, such that each transport operator optimizes their best response function connected through the market share model. To solve the integrated optimization problem efficiently, a hybrid algorithm is developed that combines stabilized column generation with a large neighborhood search algorithm.The game-theoretic framework is applied to a case study in China involving legacy airlines, a low-cost carrier, and a high-speed rail (HSR) operator. The equilibrium outcomes suggest that the low-cost carrier is likely to stimulate demand and improve the level of service through secondary airports. The further development of high-speed rail service is expected to intensify competition among airlines and reduce the overall fare level. The low-cost carriers and HSR are able to significantly increase overall consumer surplus, providing insights into the potential for low-cost service in the Chinese aviation markets and the entrance of the public service obligation program at minimum cost.

Flight Path and Scheduling Effects on Perceived Jet Lag, Fatigue, and Sleep in Footballers Traveling to and From National Teams.

This study examined posttravel perceptual responses of national-team footballers (soccer) following different flight paths, arrival/departure times, and trip contexts. Details of 396 flights from national-team players (N = 68) were obtained and verified via an online flight database. Each player provided ratings of perceptual fatigue, sleep, soreness, stress, and jet lag for 2days before and after each trip. The flight path (continents of departure and arrival), travel context (into vs out of national team), and arrival and departure times were obtained for each trip. Linear mixed models compared the pretravel with posttravel change in perceptual responses based on flight path, context, and schedule. Perceived jet-lag ratings were more responsive to travel variables (R2 = .48) than other perceptual ratings (R2 < .26). Travel from Asia to Europe (P < .05) and Europe to Australia (P < .001) had significantly higher jet-lag ratings than all other paths. Fatigue scores were worst following Asia to Europe (P < .05) and Europe to Australia (P < .05) travel, while sleep scores were worst following Europe to Australiatravel (P < .01). Perceptual responses were poorer following travel from national team to club compared with all other travel contexts (P < .05). Arrival during the daytime (11 AM to 5 PM) resulted in better perceptual responses than early-morning or late-night arrivals (P < .05). Perceived jet-lag ratings are more responsive to travel demands than perceptual wellness scales in national-team football athletes. Poorer perceptual responses may be expected when travel is longer in nature, ends later in the day, or involves travel out of the national team back to club.

Correlations among Fatigue Indicators, Subjective Perception of Fatigue, and Workload Settings in Flight Operations

Conducting flight operations at the pace of air traffic relies on shift work, overtime work, work at night, work in different and numerous time zones, and unbalanced flight crew schedules. Such working hours and workload settings can cause disturbances of the circadian rhythm and sleep disorders among flight crew members; this can result in fatigue and can have an impact on the safety of flight operations. Fatigue impacts many cognitive abilities such as vigilance, memory, spatial orientation, learning, problem solving, and decision making. In aviation, fatigue has been identified as a hazard to the safety of flight operations. This paper describes objectivation methods for data collecting processes regarding flight crew fatigue, using an electronic system of standardized chronometric cognitive tests and subjective self-assessment surveys on the subjective perception of fatigue. The data collected were analyzed using statistical methods to identify and quantify elements that affect the appearance of fatigue. Finally, causal modeling methods were used to determine correlations among the measured flight crew fatigue indicators, the subjective perception of fatigue, and the defined workload settings. The results of this research reveal which elements strongly impact flight crew fatigue. The detected correlations can help define improved measures for the mitigation of fatigue risk in future flight operations.

A multi-objective memetic algorithm with adaptive local search for airspace complexity mitigation

Airspace complexity is a paramount safety metric to measure the difficulty and effort required to safely manage air traffic. The continuing growth in air traffic demand results in increasing airspace complexity and unprecedented safety concerns. Most existing methods treat the minimization of airspace complexity as the sole objective, ignoring the path deviation cost induced by the re-scheduled aircraft. In this paper, regarding reduction of airspace complexity and path deviation cost as two conflicting objectives, a multi-objective airspace complexity mitigation model is proposed to simultaneously ensure the safety and efficiency of air transport by optimizing flight trajectories. To effectively solve this multi-objective and non-linear optimization problem, a novel Memetic Algorithm with Adaptive Local Search (called MA-ALS) is developed. Specifically, we design a new crossover and three new local search operators under the flight trajectory representation. MA-ALS conducts exploration by crossover, and exploitation by a hill-climbing local search process. Moreover, we proposed an adaptive local search selection mechanism which facilitates the dynamic collaboration of different local search operators during evolution. A comprehensive comparison with the most recently developed algorithms on Chinese air traffic dataset is conducted. The Pareto front generated by the proposed algorithm dominates that of the compared baselines. Moreover, compared with a real flight schedule, the flight plan obtained by the proposed algorithm can significantly reduce the airspace complexity.

The Influence of Visibility on the Opportunity to Perform Flight Operations with Various Categories of the Instrument Landing System.

Meteorological conditions significantly affect air traffic safety and can also affect a pre-planned flight plan. Difficult meteorological conditions are particularly hazardous during take-off and landing procedures. Still, they can also cause disruptions to air traffic by causing, for example, delays to air traffic or diversion of aircraft to other airports. From the airlines' point of view, such situations are not beneficial if flights are diverted to other airports due to reduced visibility at the airport caused by fog and haze. For flight operations, a popular navigation system with a precision approach is the ILS, which has several categories enabling an approach even in adverse meteorological conditions. However, not every airport has a high-category ILS, and setting up such navigation equipment is lengthy and costly. The main objective of this article is to analyze the impact of meteorological conditions, particularly visibility, on the possibility of performing flight procedures with different ILS categories. The study was designed to quantify the limitations associated with meteorological conditions with specific ILS equipment at a given airport. The research questions for this study include the following: What were the meteorological conditions in terms of visibility? What impact did the visibility parameter have on the performance of landing operations at the airport under study? Can an indication of the probability of stopping landing operations be important in recommendations for scheduling airline flights to avoid delays? Three airports were selected for the analysis: Warsaw Chopin Airport, Warsaw Modlin Mazowiecki Airport, and Krakow John Paul II Airport. The analysis was based on approximately 52,000 METAR dispatches in 2019 and 2022. The research indicated during which periods landing procedures were most frequently halted and calculated such a change with a different category of ILS. For the Kraków Airport, the probability of stopping landing procedures in any month was calculated, along with recommendations for flight schedule planning for this airport. The research results can be used to better plan airline flight schedules, avoiding hours with a high probability of reduced visibility, which may result in rerouting flights to another airport. Long-term low clouds and reduced visibility affect the safety of operations but also cause delays.

Unlocking ventilation flexibility of large airport terminals through an optimal CO2-based demand-controlled ventilation strategy

Large airport terminals consume significant energy due to their extensive ventilation demands. Optimizing the operation of ventilation systems is a crucial aspect of achieving greater energy flexibility and efficiency. In this study, we proposed an optimal CO2-based demand-controlled ventilation (DCV) strategy that utilizes the large indoor space of airport terminals to shift ventilation loads, reduce operating cost, and enable demand response (DR) programs. The effect of air infiltration on ventilation demand is considered in the DCV strategy through on-site CO2 measurement. A passenger dwell model is integrated to estimate the occupancy of airport terminal based on flight schedules for dynamic ventilation control. Considering the DR signal and time-of-use tariff, an advanced evolutionary algorithm is employed to locate optimal ventilation solutions that deliver better economic performance and energy flexibility while meeting indoor air quality constraints. Using an airport terminal in Beijing, China, as a testbed, the superior performance of the proposed DCV strategy was demonstrated against a baseline strategy with a fixed outdoor air supply rate under three scenarios. Simulation results showed that the proposed DCV strategy can reduce peak energy consumption by up to 60.9% and operating costs by up to 48.6% in different scenarios. Moreover, the DCV strategy can provide a flexible trade-off between the overall energy efficiency and DR capability in the adjustable DR scenario. This study revealed great opportunities for improving the flexibility of ventilation in large-space buildings and provided an instructive case study.

Reshaping China's urban networks and their determinants: High-speed rail vs. air networks

As high-speed rail (HSR) and air transportation developed rapidly in the last decade, their coopetition and interactional relationship has reshaped China's urban networks. Based on HSR and flight schedule data from 2009 to 2019, this paper constructs a weighted network to compare China's urban networks and their evolution, and employs machine learning to investigate the potential determinants. The results indicated that both networks tend toward polarization in the overall distribution and that the structure of urban networks under HSR networks is more hierarchical. That of HSR networks gradually forms a corridor structure along the trunk lines, while that of airline networks mainly shows a diamond spatial structure with Beijing, Shanghai, Guangzhou, and Chengdu as the cores. As for the evolution of urban networks, geographical factors, per capita GDP, and the tourism function of cities have more important impacts on that of HSR networks, while the network's topological structure and education resources have a greater impact on that of airline networks. Some socioeconomic attributes, such as urban administrative level, population, and the proportion of tertiary industry, have similar and limited influences on the two networks.

Airport traffic optimisation and airdrome analysis using mathematical modelling

An airport is considered to be a complex system, so managers nowadays are looking for verifiable solutions that could be tested and virtually simulated, in order to optimize safety, improve regularity, and reduce delays and risks of collision. To respond to this dilemma, many solutions were tested using safe simulation methods. The specific problem tackled in this paper refers to aerodrome capacity optimization, and specialy arcrafts mouvements. For this purpose, we introduce a mathematical model that was applied to Mohamed V Casablanca Airport, and the corresponding event actualization and graph was constructed taking into account uncertainty in flight schedules, aircraft types and their stand. Finally, the airdrome model was simulated using a special parameter in Arena tool.

Analysis of the Readiness of the Apron Movement Control Unit in the Embarkation and Debarkation Phases of Hajj Flights in 2022 at Adi Soemarmo Boyolali International Airport

In the service of flight activities on the air side, it requires the role and supervision and regulation of air traffic from the Apron Movement Control (AMC) unit. Adi Soemarmo International Airport is one of the hajj embarkation airports in Indonesia, especially in Central Java and Yogyakarta. When there are Hajj flight activities, the airport operation hour will be 24 hours while still dividing work time. In handling haj flights, the AMC unit oversees the movement of haj transport buses from or to planes so that researchers aim to analyze the readiness of the AMC unit in the embarkation and debarkation phases of hajj flights at Adi Soemarmo International Airport in 2022.This research is descriptive using qualitative methods with data collection methods in the form of interviews and documentation. The data obtained were in the form of observations, interviews with AMC unit personnel at Adi Soemarmo International Airport as well as documents used to carry out the pilgrimage activities.The results of this study indicate that from secondary data that analyzes AMC unit documents are follow me car services, aircraft parking placements, special terminals for Hajj flights and Hajj flight schedules, based on standard operation procedure (SOP) data, namely follow me car services placing aircraft parking . hajj flight special terminal and haj flight schedule. The results of the interview with AMC at Adi Soemarmo International Airport will increase the number of human resources due to the division of work time due to the lack of AMC unit workers. During the hajj flights, the operation of Adi Soemarmo International Airport became 24 hours, the airport operating hours changed from 07.00 WIB to 20.00 WIB/last night to 24 hours with the number of AMC unit personnel only 2 to 3 people per shift, both regular flights and during flights pilgrimage. However, this is not a workload for the AMC unit in dealing with haj flights.

Impact Analysis of VVIP and VIP Flight Activities on the Smoothness of Commercial Flights at Bali's I Gusti Ngurah Rai International Airport

I Gusti Ngurah Rai International Airport is an airport for several purposes, from the needs of VVIP and VIP guests to commercial needs. Some of these types of flights certainly have differences, VVIP and VIP flights are a priority at the airport. Disruption to the smooth operation of commercial flights, which was partly caused by VVIP and VIP guests coming and going to the island of Bali through I Gusti Ngurah Rai airport. This study uses inductive/qualitative data analysis. The method used for this research is the method of documentation, observation, and interviews with Airport Operation Landside and Terminal officers. This research was conducted for 2 months, starting from 01 November 2022 to 31 December 2022 at the Airport Operation Landside and Terminal unit. The results of the research conducted can be concluded that VVIP (Very Very Important Person) and VIP (Very Important Person) flight activities at I Gusti Ngurah Rai International Airport in Bali greatly affect commercial flight activities, causing commercial flights to be temporarily stopped or flight schedules changed. , and the airport has prepared for handling in such a way as to reduce the impact caused by VVIP flights on commercial flights.

MODELLING FOR FUEL POLICY IN LOW VISIBILITY OPERATIONS IN AIRLINE OPERATIONS MANAGEMENT

Purpose- It can be said that fuel costs have the highest share in airline operation costs. Therefore, fuel efficiency is important for cost optimization in airline operation management. Fuel efficiency has been studied in many ways in airline operation management in the literature. It can be reported that the cost optimization due to additional fuel transportation caused by meteorological conditions is also an important field. This study aims to provide data for making a decision to form a fuel policy for a flight schedule by determining the divert risk rate by analyzing previous meteorology reports when there is a risk of divert due to low visibility in meteorology reports. Methodology- Thus, by providing data for airline operation managers to make decisions that will provide fuel optimization, cost-effectiveness will also be contributed. Data for the study were taken from OGIMET (the Spanish meteorology website). A simulated flight was created for the study, and the past period forecast efficiency was calculated from previous meteorological data to determine the divert risk rate. Then, it was revealed how much the divert risk rate was reduced if additional fuel was carried for the flight according to the past period meteorological data to ensure that the aircraft waited for suitable conditions in the air at the landing aerodrome. Findings- The above results reveal the divert risk rate for the airline39 flights when additional fuel is loaded and without loading additional fuel in low visibility forecast operations for the three months of the year when low visibility is more common, based on past meteorological data. Conclusion- As a result of the study, it can be reported that a model has been created relating to how to determine the divert risk rate to make a fuel policy decision for a flight schedule when there is a risk of diverting due to low visibility in airline operation management. Keywords: Airline operation management, low visibility, fuel policy, airline fuel efficieny, divert risk ratio, JEL Codes: L93, M21, C44

Kajian Pengawasan Unit Apron Movement Control (AMC) terhadap Kelayakan Ground Support Equipment (GSE) di Sisi Udara Bandar Udara Internasional Hang Nadim Batam

&#x0D; Supervision conducted by Apron Movement Control (AMC) on the feasibility of Ground Support Equipment (GSE) vehicles is still frequently found in incidents and violations on the airside. Violations found such as damage to the vehicle engine, vehicle facilities that do not comply with regulations, and oil/fuel spills. This study aims to find out the causes of the lack of supervision of the Apron Movement Control (AMC) unit on the feasibility of the Ground Support Equipment (GSE) on the airside and to find out the reasons why Ground Support Equipment (GSE) vehicles that are not operationally feasible are still used on the air side at International Aiports Hang Nadim Batam. This study uses a qualitative method. Data collection techniques through interviews, observation and documentation. Then data analysis was carried out, namely data reduction, data presentation, and drawing conclusions. The results of this study indicate that direct supervision by Apron Movement Control (AMC) of GSE vehicles has not been carried out properly because AMC officers are more focused on garbarata services and Human Resources (HR) are limited, so violations are still found on the airside such us GSE vehicles that are not properly operational. Unfit GSE vehicles are still used for operational activities on the airside due to very busy flight schedules.&#x0D; Keywords: Supervision, Apron Movement Control (AMC), Feasibility, and Ground Support Equipment (GSE)

Optimizing the battery charging and swapping infrastructure for electric short-haul aircraft—The case of electric flight in Norway

Recent advances in battery technology have opened the possibility for short-haul electric flight. This is particularly attractive for commuter airlines that operate in remote regions such as archipelagos or Nordic fjords where the geography impedes other means of transportation. In this paper we address the question of how to optimize the charging infrastructure (charging power, spare batteries) for an airline when considering a battery swapping system. Our analysis considers the expenditures needed for (i) the significant charging power requirements, (ii) spare aircraft batteries, (iii) the used electricity, and (iv) delay costs, should the infrastructure not be sufficient to accommodate the flight schedule. The main result of this paper is the formulation of this problem as a two-phase recourse model. This is required to account for the variation of the flight schedule throughout a year of operations. With this, both the strategic (infrastructure sizing) and tactical (battery recharge scheduling) planning are addressed The model is applied for Widerøe Airlines, with a network of 7 hub airports and 36 regional airports in Norway. The results show that a total investment of 4412 kW in electricity power supply and 25 spare batteries is needed for the considered network, resulting in a daily investment of €11700. We also quantify the benefits of considering an entire year of operations for our analysis, instead of just one congested day (7% cost reduction) or one average day of operations (31% reduction) at the most congested airport.

Suitcase Pro

Suitcase Pro introduces a QR-based flight inventory management solution, aiming to optimize the efficiency and precision of flight inventory control procedures. This innovative system revolves around a digital approach to travel bookings, eliminating the need for paper and embracing mobile connectivity, all facilitated through QR codes. Through a browser-accessible web page, users gain access to comprehensive flight schedules and an online reservation platform. This platform empowers customers to securely purchase flight tickets with their debit/credit cards, accompanied by web connectivity. Notably, the implementation employs QR codes to oversee and keep luggage records up to date. These QR codes enable the airport department to effortlessly access passenger details. Concurrently, distinct QR codes are assigned to merchandise within the airport, underscoring the versatility of QR codes in effectively tracing product location and ownership information