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Globetrotter

Al-Ula International Airport Enters the Digital ATC Era – U.S Version

Airport Intelligence Series Al-Ula International Airport Enters the Digital ATC Era March 2026   Al-Ula International Airport in Saudi Arabia has become the first airport in the Middle East to operate fully remotely using advanced digital tower technology, marking a significant step in aviation operations and infrastructure innovation. The remote air traffic control system was developed collaboratively by Saudi Air Navigation Services (SANS) and global technology provider Indra, and went into service in February 2026. Controllers now manage aircraft movements at Al-Ula from a distant operations centre, using high-definition cameras, sensors and real-time data feeds to maintain situational awareness and oversee arrivals and departures. The implementation of a digital tower reduces reliance on traditional physical control towers and offers operational efficiency gains, while supporting broader strategic objectives, including enhanced safety, improved resource utilisation and the adoption of modern air navigation technologies. This development aligns with regional aviation goals to modernise air traffic infrastructure as demand grows and new mobility solutions emerge. Share Share Share

Globetrotter

Singapore Turns Policy into Climate Action with Aviation Fuel Levy

Airport Intelligence Series Singapore Turns Policy into Climate Action with Aviation Fuel Levy February 2026   Singapore has become the first country to introduce a nationwide Sustainable Aviation Fuel (SAF) levy, establishing a structured funding mechanism to accelerate aviation decarbonisation. Announced by the government and reported by Associated Press, the levy will apply to tickets sold from April 1, 2026, for flights departing Singapore on or after October 1, 2026. Passengers will pay between S$1 and S$41.60, depending on distance and cabin class, while air cargo shipments will be subject to a separate weight-based fee. Funds collected will be pooled to procure SAF – a lower-carbon alternative produced from renewable feedstocks such as waste oils and agricultural residues, helping airlines operating from Singapore Changi Airport increase cleaner fuel uptake. The move positions Singapore at the forefront of aviation climate policy. As Southeast Asia expands its SAF production capacity, the levy creates predictable demand and financial certainty for suppliers while spreading costs across the ecosystem. While the additional ticket cost is modest, the policy marks a significant structural shift signalling that sustainable aviation is transitioning from voluntary initiatives to regulated, system-wide climate action. Share Share Share

Airport Planning & Infrastructure

India’s First Dual Airport Case Study: Goa’s Dabolim/MOPA System – Redistribution or Real Growth?

Airport Intelligence Series India’s First Dual Airport Case Study: Goa’s Dabolim/MOPA System – Redistribution or Real Growth? February 2026 6 min read The story of Goa was that of a suppressed system for air travel – road taking the dominant share of domestic tourist activity – with seasonal activity driven by the charters from Europe. MOPA (GOX) opened in January 2023, and Dabolim (GOI) /MOPA (GOX) became the first dual-airport system in India. The two airports are about 60 km apart. Technically, being part of a state and not a city/metropolitan region creates distinct catchment preferences due to the geographical spread. However, due to lack of serious competition from any other airport in the neighbouring states – the dual airports represent a competitive scenario with the incumbent, state-owned Airports Authority of India (AAI) operating Dabolim International Airport (GOI), and the 2nd airport, Manohar International Airport (GOX), at MOPA, operating under a 40-year concession model with GMR Airports owning 100% of the equity. 90 mins catchment area With distinct catchments, the two airports appeal to a very different type of customer. South Goa generally attracts local domiciled population and high-end tourists who prefer luxury resorts and personalised hospitality experiences, while North Goa draws more tourists focused on entertainment and nightlife. This difference in tourist profile and location makes both airports important for the state’s connectivity and tourism economy. The success of a dual airport system (for both parties involved) hinges on the positioning of each airport and the scale that the airports can grow to. Unlike many other dual airport systems globally, the traffic allocation at Dabolim (GOI) /MOPA (GOX) is not a result of any government mandate but purely on market dynamics (and incentives). Through the lens of demand and supply, we look at how the overall pie has changed and the market share the two airports have been able to garner supported by the role some of the heavy-hitter airlines have played in the traffic distribution. System Demand – Has the overall pie grown? For the GOI/GOX system, one airport was never meant to be a replacement for the other. Since overall market size is not a zero-sum game, the expectation is that the new airport will create new customers and tap into latent demand. The overall pie should grow for the following reasons: With GOX helping ease congestion and representing an option for airlines and passengers who don’t want to be limited by the operational restrictions at GOI and sync up travel to coincide with hotel check-in and check-out times Improved access to North Goa (party place with serene beaches) The two-airport system creates more supply and provides room for future growth.   Prior to the opening of MOPA (GOX), there was a sharp recovery after the COVID-19 pandemic with total passenger demand rebounding to 7.8 million in CY 2022 (representing a year-on-year growth of 50.3% from 2021). International recovery lagged while domestic travel rebounded aggressively on the back of revenge travel. Post MOPA (GOX) commissioning, the dual system traffic increased sharply in 2023 due to post pandemic revenge travel surge and the new supply. The pace of growth slowed after 2023 as demand stabilised. The passenger demand for the dual airport system grew from 11.16 million to 11.62 million passengers from 2023 to 2025 – a relatively modest 2% CAGR largely concealing the redistribution beneath the headline number. This growth is lower than the overall growth seen in the Indian aviation market during the same period- India aviation market grew at 1 x multiplier of GDP (6.6% CAGR). Overall, there hasn’t been much growth system wide – the cumulative supply of seats at GOX and GOI has only grown 3.6% from 2023 to 2025.  What’s going on, Goa? Have you lost your MOJO? There could be several reasons for the insipid demand growth in recent times including the following considerations: Overtourism – Crowding and low value tourism eroding the cultural identity of Goa Choice – Are Indians opting for other destinations including reasonably priced scenic destinations in South-East Asia? Airlines are not complaining as they map the Eastward surge. Cost – Has the state become too expensive due to the lack of affordable accommodation and transportation? Room tariffs in Goa have increased with the average daily rate (ADR) of about 10,900 INR in 2024 (Source: horwathhtl 2024 report) Overtourism has been the bane of the state once known for its casual and easy-going lifestyle. The crowds thronging the beaches of Goa are not respectful of the beach surroundings. Choice was expected and as the numbers of Indians traveling internationally continue to grow exponentially, the Indian carriers are lapping up slots at places such as Bali, Vietnam, Cambodia to name a few. Scheduled seats from India to Southeast Asia in 2025 are projected to be 29% above 2019 levels. The third issue is a structural problem that is not just confined to Goa in the post pandemic world. Goa used to be known as the cheaper Maldives for our East European and Russian friends (who would come and stay for months sometimes). That’s not the case anymore. Goa’s overall average daily rate (ADR) has roughly doubled over the last decade — from around ₹7,000 in FY2016 to over ₹10,000 by FY2023, consistently making it among the highest-ADR hotel market in India. In 2024, Goa slowed but did not decline — its 2.4% RevPAR (revenue per available room) growth remained positive but was very modest compared to the high growth rates of the previous two years. Foreign Tourist Arrivals (FTAs) into Goa by air are currently about 71% lower than 2019 levels on the back of fewer charter flights. In 2019, there were around 800 international charter ATMs. By 2025, this number had fallen to around 190 ATMs, representing an 81% traffic decline compared to 2019. For Goa to get its MOJO back, there needs to be a recalibration of the price point and service offerings that competes with the Balis of the world. Consider removing this filler

Cargo and Logistics

The Smart Cargo Terminal: A Practical framework for Technology Integration

Airport Intelligence Series The Smart Cargo Terminal: A Practical Framework for Technology Integration February 2026 5 min read The Global Air Cargo sector currently navigates an environment where the challenges facing the industry are different from those of the past. On one hand, there are factors such as geopolitical tensions, trade policy shifts, and trade lane disruptions; while on the other, there are challenges arising from capacity constraints, expensive labour and sustainability commitments. For decades, the answer to cargo growth was simple: build more warehouses. When volumes rose, we expanded footprint and adjusted layout. With the rapid growth of traffic and the associated aeronautical infrastructure needs of airports, physical space constraints are plaguing all the major airports. Cargo facilities that require prime real estate at an airport, with airside access are impacted by this constraint too.  Technology provides a solution, enabling optimization of the cargo capacity. But it is easier said than done. The question facing cargo operators and handlers today is not whether to transform or not. It is about how to do it  without falling into the trap of fragmented, reactive technology adoption that creates new inefficiencies rather than eliminating old ones. In this article, we propose a framework to facilitate decision-making on technology integration for cargo terminals to function as an intelligent and ecosystem-connected facilities. The Core Strategic Shift The path to greater throughput is no longer paved with more square footage. It is built on smarter use of what already exists. Technology integration, when executed along with architectural design, allows stakeholders to extract significantly more output from current or future planned facilities. The evidence from airports that have made this transition demonstrates measurable gains in throughput, dwell time reduction, labour productivity, and service reliability. When we think about cargo facilities planning, technology solutions are often a layer on top, unaccounted for in the design stage resulting in sub-optimal outcomes. An integrated solution would mean drafting out a plan for technology adoption at different phases and working backwards to the design of the physical space, incorporating the requirements of future technology. In other words, the vision for a smart cargo terminal must dictate the design of the terminal, and it must be planned thoroughly. A Three-Layer Framework for Technology Integration in Air Cargo Facilities Technology integration is most effective when approached as a structured maturity pathway rather than a collection of isolated pilots. Hence, a three-layered approach, where each successive capability builds on the foundation established by the one before it. Each layer has standalone value and its potential is enhanced with combination of other layers. Decision makers can hence use the framework to craft a practical path of realizing the vision of a smart cargo terminal. Layer 1: Physical Automation Automation is the first and most tangible step. It addresses the highest-visibility pain points — manual handling inefficiencies, peak-period bottlenecks, ULD damage, and the safety risks inherent in labor intensive environments. Technologies in this layer include Autonomous Mobile Vehicles (AMVs), robotic pallet movers, and Automated Storage and Retrieval Systems (AS/RS) Shanghai Pudong International Airport deployed heavy-load AGVs in their cargo terminal to manage rising e-commerce volume and labour dependency. They deployed six 10-tonne-capacity AGVs integrated with China’s first lift-and-run system. Operating 24/7 with precision control, these systems reduced manual transfers and improved throughput stability. At FedEx South Pacific Regional Hub in Singapore, AI-enabled robotic sorting arms process up to 1,000 parcels per hour across 100 destinations with >98.5% accuracy, while allowing manpower redeployment to higher-value functions. Physical automation makes the strongest case in environments characterised by high volume, complex handling requirements, or significant space constraints. It delivers measurable gains when deployed correctly. Layer 2: Intelligence Integration While Layer 1 would standardize workflows and and increase throughputs, it does not adapt well to real time variability. Unexpected disruptions or fluctuating demand may restrict its efficiency.  When artificial intelligence is deployed as the intelligence layer above physical automation, it provides precisely this capability: adaptive decision-making and real-time optimisation across the entire terminal operation. Where automation delivers the execution backbone, AI delivers the decision-making intelligence. There are several cargo management system (CMS) products that provide an integrated platform covering sales, warehouse management, ULD management, mail handling, revenue management etc. Rather than allowing AGVs, storage systems, and handling equipment to operate as independent automated silos, the CMS integrates them into a unified terminal management platform. Real-time analytics, predictive task allocation, and system-wide visibility through mobile interfaces enable continuous performance monitoring and dynamic resource deployment. These platforms have been deployed in live cargo environments including Shanghai Pudong, Finnair Cargo Terminal, Istanbul’s Mega Hub amongst others. Layer 3: Ecosystem Integration While the cargo terminal may be highly automated and intelligently managed, if the broader ecosystem — landside, airside, and city processes operates without real-time visibility into asset location, and systemic inefficiencies persist. Ecosystem integration extends digital visibility to every asset and actor in the cargo supply chain. Smart labels, IoT-enabled tracking, and connected community platforms transform fragmented multi-stakeholder processes into coordinated operations. This is the larger vision. By equipping non-powered assets like ULD dollies, loose pallets, and ground support equipment, with battery-operated trackers, real-time visibility across both airside and cargo zones can be achieved. Hoopo, an Israel based company has deployed its tracking technology at several global airports and reported favourable outcomes. These include a 70% reduction in manual search time for assets and, a 50% faster GSE response times, with direct downstream benefits for aircraft turnaround performance. At Kempegowda International Airport, Bengaluru, the response was structural. Rather than addressing individual pain points in isolation, the airport built a single digital platform, the Airport Cargo Community System, that connected airlines, customs, freight forwarders, ground handlers, and trucking partners into a shared operational view. Landside congestion, often the most stubborn bottleneck at high-growth gateways, was tackled directly through an automated truck management facility. The results were measurable: average truck turnaround dropped from four hours to one, and 78% of vehicles now enter the terminal within 20 minutes. Export dwell time came down

Globetrotter

Hearing Every Call: Frankfurt Trials Auracast at the Gate

Airport Intelligence Series Hearing Every Call: Frankfurt Trials Auracast at the Gate February 2026   Frankfurt Airport has launched a world-first trial of Auracast broadcast audio – a new Bluetooth technology that sends gate announcements directly to passengers’ own devices (hearing aids, earbuds, headphones or smartphones). The pilot is live at Gates A16 and A17 in Terminal 1, where travellers can connect their compatible devices and receive personalised audio streams of boarding calls, gate changes, delays and other flight information. Why it matters for passengers: Busy airport terminals are often noisy, which can make traditional loudspeaker announcements difficult to hear, particularly for deaf and hard-of-hearing passengers. By streaming announcements straight to personal devices, Auracast provides clearer, more inclusive access to important travel information, reducing stress and enhancing confidence during the airport experience. This is a substantial step toward a more accessible travel environment for all passengers, especially the estimated 1.5 billion people globally living with some degree of hearing loss. How it works: Auracast turns public audio into a Bluetooth broadcast that multiple compatible devices can tune into without traditional pairing. Users can connect via compatible smartphones (e.g., Pixel, Samsung), earbuds, headphones or hearing aids to receive direct gate audio. The trial will run for about two months while feedback is collected to evaluate comfort, clarity and overall passenger experience. Industry impact: If successful, this technology could expand to other airports worldwide, enabling more inclusive and quieter terminal environments while significantly improving real-time communication for passengers with hearing impairments. Share Share Share

Globetrotter

Passenger 2.0: BIAL & Mu Sigma Elevate Customer-First Journeys

Airport Intelligence Series Passenger 2.0: BIAL & Mu Sigma Elevate Customer-First Journeys February 2026   Bangalore International Airport Limited (BIAL) is advancing its Customer-First philosophy by partnering with global decision sciences leader Mu Sigma to transform the airport into an “algorithmic airport.” This strategic collaboration integrates Mu Sigma’s proprietary Decision Intelligence Platform and advanced analytics tools across key operational and passenger service touchpoints to unify and analyse data in real time, enabling proactive decision-making and personalised service delivery. By consolidating insights from existing systems, BIAL aims to anticipate passenger needs, smooth terminal flow and enhance convenience, comfort and efficiency throughout the travel journey. Predictive analytics will be applied across functions such as retail and food service queue management, dynamic parking demand forecasting, and personalised passenger interactions via BLR’s mobile Pulse app and official website. These capabilities are designed to reduce congestion, provide timely recommendations and offers, and improve wayfinding and choice at every terminal touchpoint. Location-based promotions, tailored loyalty rewards and real-time notifications will make the digital experience more intuitive, while operations teams will leverage unified intelligence to optimise service delivery and respond faster to evolving traveller patterns. According to BIAL, the initiative will be rigorously tested; only enhancements that deliver measurable improvements to the passenger experience will be scaled more broadly, reinforcing BLR Airport’s evolution from a transit hub to a holistic, passenger-centric travel ecosystem. Share Share Share

Globetrotter

Breaking Ground in Aerial Cargo: ST Engineering’s DrN-600 Debut

Airport Intelligence Series Breaking Ground in Aerial Cargo: ST Engineering’s DrN-600 Debut February 2026   At the Singapore Airshow 2026, ST Engineering, in collaboration with U.S. partner AIR Inc., unveiled its most capable unmanned cargo aircraft to date – the DrN-600. Designed as a medium-lift cargo drone, the aircraft represents a leap forward in autonomous logistics and unmanned air systems. With a maximum take-off weight of up to 600 kg and an 8-metre wingspan, the DrN-600 can carry up to 100 kg of payload inside a front-loading compartment sized for standardised pallets, facilitating efficient loading for commercial operations. Powered by lithium-polymer batteries and featuring vertical take-off and landing (VTOL) capability, the drone combines multi-rotor lift with wing-borne forward flight to achieve a range of roughly 70–100 km, making it suitable for last-mile cargo missions in remote, island, or infrastructure-limited regions. Company representatives highlighted potential use cases that include delivery of critical supplies, spare parts, medical products, and logistics support where traditional transport is constrained. Development trackers say test flights are slated for the second quarter of 2026, with commercial operations anticipated by 2028, pending regulatory approvals. This timeline aligns with ST Engineering’s broader intention to overcome technical and economic barriers to routine unmanned cargo service and push beyond small delivery UAS into practical, scalable aerial logistics solutions. Share Share

Globetrotter

Al-Ula International Airport Enters the Digital ATC Era

Airport Intelligence Series Al-Ula International Airport Enters the Digital ATC Era February 2026   Al-Ula International Airport in Saudi Arabia has become the first airport in the Middle East to operate fully remotely using advanced digital tower technology, marking a significant step in aviation operations and infrastructure innovation. The remote air traffic control system was developed collaboratively by Saudi Air Navigation Services (SANS) and global technology provider Indra, and went into service in February 2026. Controllers now manage aircraft movements at Al-Ula from a distant operations centre, using high-definition cameras, sensors and real-time data feeds to maintain situational awareness and oversee arrivals and departures. The implementation of a digital tower reduces reliance on traditional physical control towers and offers operational efficiency gains, while supporting broader strategic objectives, including enhanced safety, improved resource utilisation and the adoption of modern air navigation technologies. This development aligns with regional aviation goals to modernise air traffic infrastructure as demand grows and new mobility solutions emerge. Share Share Share

Market Intelligence and Analytics

Top 10 U.S. Domestic Airport Pairs

Airport Intelligence Series Top 10 U.S. Domestic Airport Pairs September 2025 4 min read The U.S. domestic market continues to be shaped by hub dynamics and route specific supply decisions. Unsurprisingly, the airports that dominate the list are serving some of the most populated catchment areas. Drawing on supply data [1] of seats for three consecutive summers (June to August of 2023, 2024 and 2025, referred to as SYY from here on), the analysis identifies the dominant carriers by airport pair and highlights the trajectory of their dominance. In S25, the largest legacy carriers; United Airlines, Delta Airlines, American Airlines – carved out a market share of 66% across the top 10 domestic airport pairs with United Airlines far ahead of the pack with 28% market share of the top 10 US domestic airport pairs. The pecking order for the top 10 domestic pairs tell an interesting story. Largely, the pairs have held their ranking in S25 as compared to S24 with at most a drop or gain in ranking by one position for some airport pairs. A three-year comparison of summer schedule across top airport pairs reveals how carriers have fortified their dominance, how low-cost and ultra low-cost carriers (LCCs and ULCCs) are tactically adjusting, and route-specific supply decisions are tightly aligned with broader network planning objectives. The JFK>LAX corridor is the busiest U.S. domestic airport pair in S25 with a 10.3% YoY growth from S24, and represents a strategic battleground for transcontinental traffic. The entry of Frontier with a 4.9% share in S25 signals possible ULCC experimentation, though the pair remains highly concentrated among legacy and hybrid carriers – Delta ~ 44% and JetBlue 33% and American 19% market share. LGA>ORD has dropped 1 position to #2 ranking with a 4.4% YoY growth in S25 as compared to S24. The move up in the ranking from 7th position in S23 reinforces its status as a high-frequency business trunk pair. United Airlines has increased its market share (by 6 percentage points) to 48% as the carrier continues leveraging its stronghold at Chicago O’Hare. The casualty of the battle has been American and Delta – losing market share by 5.0 and 3.0 percentage points respectively. Spirit Airlines coming out of bankruptcy has filed for second bankruptcy within a year due to its inability to fix its cost structure. Operating expenses have continued to exceed revenue, forcing the airline to cut several loss-leading routes. Its market share has dropped from 9.8% in S24 to 3.0% in S25, and the company plans to further reduce its presence in the near future as part of additional cost-saving measures. On the West Coast, LAX>SFO route posted a 3.8% increase in seat supply in S25 as compared to S24, and retained its #3 rank in seat supply volumes. United and Delta are dominant with 33% and 25% market share respectively. Notably, American Airlines has ramped up service and increased market share from 2.6% to 6.6%, while Frontier and Horizon have emerged with ~5% shares respectively, reflecting diversification of supply. In contrast, JetBlue and Alaska have fully exited as part of the larger network restructuring to cut unprofitable routes. ORD>LAX, one of the fastest growing pair, increased seat supply by 12% and moved up one spot to #4 position in S25 – United (47.8%) and American (40.0%) dominating the pair. Frontier is the new kid on the block with a 3.4% market share. At #5 position, the seat supply for the East Coast corridor LGA>ATL fell sharply (-13.9% drop) with the exit of JetBlue and the reduced service from Spirit, illustrating the challenges of contesting in Delta’s fortress hubs. Delta increased its dominance to nearly 70% market share. Again, Frontier was the only other airline to grow seat volumes by 1.5%. Other competitors, including JetBlue and Spirit, exited. In the #6 position DEN>PHX corridor, not surprisingly dominated by Southwest, who remains the market leader (48.0%) but has ceded ground to United (23.6% market share, 2% seat supply growth in S25). While Frontier’s growth has plateaued, American has rebounded modestly. The market contracted by 7.0% in S25 compared to S24. At the #7 position EWR>LAX market contracted by 1.2% in S25. United was the dominant carrier (69.2%), with declining seat volumes for JetBlue, Alaska, and Spirit, reflecting incumbents’ advantage in long-haul markets. This dominance is expected to increase with United’s moving their transcontinental premium “PS” service from JFK to EWR from October. At the #8 position, JFK>SFO route is dominated by Delta and JetBlue controlling ~69% combined share, Alaska Airlines continued to retreat, cutting seat volumes by 5.5% in S25 and 8 percentage points compared to S23. This route grew 5.4% in seat supply in S25. Leisure markets – #9 EWR>MCO is stagnant with S25 volumes similar to S24 while #10 PHL>MCO volumes in S25 are down compared to the S24 by 4.0%. Overall, S25 trends illustrate a re-concentration of supply around high-demand transcontinental and business-focused corridors, led by legacy carriers strengthening their share amid selective ULCC entry and exit. The overall seat supply in S25 for the top 10 domestic markets increased by 1.2%. United, Delta, and American have garnered nearly two-thirds of the market share of the top 10 domestic markets, cementing their network advantages, while ULCC entries remain limited. [1] Source: Cirium SRS Analyzer Share Share Share

Market Intelligence and Analytics

Predictive Analytics for Airport Capacity Planning

Airport Intelligence Series Predictive Analytics for Airport Capacity Planning September 2025 3 min read Why Passenger Demand Forecasting at a granular level matters Traditional planning cycles, seasonal schedules, and monthly roll-ups can’t keep pace with real-world variability: shifting booking patterns, weather, special events, and disruptions. Passenger demand is the thread that ties it all together. If airport operators can predict inflows and outflows through curb, check-in, security, immigration, boarding, and arrivals, they can right-size resources and make targeted, timely interventions. That translates to shorter queues, more consistent dwell times, and smoother peaks and troughs that ripple less across the day. Variability of the demand from one day to another day is what keeps some of the capacity and operations planning folks up all night. Traditional ways of estimating passenger demand through historical load factor (% of seats filled by flight) and applying a show up profile (also known as the distribution of time that passengers arrive at an airport) by route/market are very static ways of estimating demand. The precision is indeed lacking to be able to have a high degree of confidence in the numbers. Airports are interested in predicting hourly and daily demand with a higher degree of confidence interval, and not just quarterly or annual demand to streamline resourcing allocation decisions. Use Case – Profile Estimation for a Typical Day at a Major Indian Airport Avinia Labs, using several years of tower data for a major Indian airport, has demonstrated the utility of machine learning (ML) models to forecast typical weekday and weekend patterns, as well as the busiest days of the year such as Diwali or Christmas Eve. In this use case SARIMA model was used, which is among the more popular time series forecasting techniques. 11 months (January to November) 2019 of tower data was used to train the model to produce daily and hourly profiles for the month of December. Specifically, the weekly seasonality was tested and separate daily profiles for a Friday and Sunday was tested against actuals. This also included testing the busiest travel day in the year, which fell on Christmas Eve. The comparison is shown in the graphic below. It shows a close match between the predicted values and actuals except for the busiest day of the year outlier. Busiest travel days require bespoke models instead of one-size-fits-all averages, improving accuracy when passenger experience is most sensitive. Modelling the busiest day would require training the model on a few years of the busiest day to enable it to predict with a higher precision going forward. However, there are some limitations as with any model. Larger datasets are required to improve accuracy. As models are exposed to larger, more diverse datasets, they learn from anomalies, become more robust across airport types, and improve reliability. Modeling extreme cases such as the busiest day of the year will require representative data to train the model for busiest days over several years. Forecasting is part science and part Art. Any application without a subjective context or interpretation can be misleading. Patterns tend to overestimate “causality”. Any constraints and other “temporal” factors need to be considered. Got a use case idea? Just hit reply and tell us what analysis you would find most useful— we can crunch the numbers at your beloved airport. Share Share Share

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