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Why Open Architecture and third-party algorithms will accelerate the arrival of automated cabin baggage screening

Guest Author by Guest Author | Sep 29, 2022

By Ha McNeill, Executive Vice President, Commercial, Pangiam and Alexis Long, Project Director, Dartmouth, Pangiam

Requiring open architecture (OA) in baggage screening is a powerful action airport operators can take today to address the operational and staffing challenges that have affected post-pandemic travel at major airports.

In any hardware procurement, OA must be considered in relation to future integrations or data use. Systems, which produce open and standardized data, ensure that current hardware will not be rendered obsolete and will not have to be replaced or significantly upgraded with future developments in software or technology—some of which we may not even know about today.

OA is therefore a critical tool for airports and screening authorities seeking to enable the greatest flexibility in designing new security checkpoints. It prevents vendor lock-in, allows integration and interoperability with any security technology—irrespective of manufacturer or other third-party algorithms—and creates an environment where innovation can come from the entire ecosystem rather than relying on a single provider for 100% of that innovation.

At the same time, it creates incentives and encourages a larger ecosystem of providers by reducing barriers to entry and making it easier to deploy solutions, sometimes developed for other use cases, to transport security.

In 2020, ACI got behind OA in force. Over 20 of the world’s Regulators and airport operators from across Europe, North America, Asia Pacific and the Middle East joined forces to promote the introduction of OA in airport security systems by publishing common requirements, which could be used in future tenders and provide clarity for original equipment manufacturers (OEM) on industry needs: ACI’s Open Architecture for Aviation Security Systems.

The role of Computed Tomography scanners for cabin baggage

The international roll out of Computed Tomography (CT) scanners provides a once in a decade opportunity to reinvent how security is delivered and to embed OA.

These powerful scanners are data rich and enable third party software developers to build solutions to unlock this data and ultimately automate the screening of baggage. One of the key aspects of third-party algorithm software is making sure decisions on threats through CT scanning images are automated and free up valuable security resources to focus on only those bags that pose the greatest risk. By harnessing the power and potential of software, the aviation industry will benefit from this specialized skill set, increased competition, and therefore ultimately raise standards and options.

When procuring CT scanners, it is therefore vital that airport buyers use their contractual and market power to ensure that the entire ecosystem of aviation security vendors proactively commit and deliver a roadmap to OA.

Doing so will help rebalance that business case for deploying CT scanners by disrupting traditional thinking, enhancing existing capability, and transforming historic ways of working.

Key takeaways for procurement

Anyone buying or thinking of buying new checkpoint technologies and CT scanners should ensure that vendors participating in a tender can fully comply with ACI’s Open Architecture for Aviation Security Systems document.

The objective is to ensure that the airport or screening provider has access to the data generated at the checkpoint:

  • In a format that is usable
  • In real time so that it is operational viable
  • With the ownership rights so that the data can be utilized to advance the mission objectives

The desired structure around access to images and data at the checkpoint will supercharge the software industry and lead to a breadth of analytic capabilities being developed in a competitive market.  

The structure in place today for checkpoint screening equipment puts tremendous limitations on current and future operational effectiveness and efficiency.

The details matter

A principle of OA is the use of common open-source image formats. In aviation CT technology, this is widely accepted through ACI’s Open Architecture for Aviation Security Systems agreement to be the use of the DICOS image format. This is due to its similarities with the DICOM format, used successfully today as the common format in the medical imagery sector, an area with similar data quality requirements. In any procurement exercise, attention should be paid to the speed at which DICOS images can be retrieved from scanners, how that data is transferred, and the ownership structure of those images.

To offer the full benefits of automated cabin screening and wider digital transformation, images and other data produced by checkpoint equipment and screening technologies must be made available in real time. Any solutions that result in an increase in the time taken to provide images from scanners, severely impedes the processing time, and in practice, would prevent airports and screening authorities from being able to realize the full benefits of third-party software and would be de-facto locked into OEM specific systems and algorithms.

Finally, just like any appliance or tool, data generated from OEMs such as images produced must have ownership rights vesting with the airport or screening authority so that innovation born from that data can come from the entire ecosystem rather than relying on a single provider for 100% of that innovation.

For more information on technical specifications to include in procurement and how third-party software can transform airport security and operations, please contact Pangiam at info@pangiam.com.

ACI Smart Security White Paper: The Implementation of Artificial Intelligence and Machine Learning in the Security Checkpoint

Pangiam is pleased to have contributed to and supported the ACI Smart Security White Paper on Artificial Intelligence (AI) and Machine Learning (ML) in the Security Checkpoint. Among many topics, the resource covers what OA is, how AI/ML can offer benefits in the OA space, as well as its risks.

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Implementation of AI and ML in the Security Checkpoint
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Ms. Ha McNeill is Executive Vice President for Pangiam Commercial. As EVP of Pangiam Commercial, Ha leverages Pangiam’s commercial and government mission-driven experience to deliver innovative solutions for a diverse range of clients. Ha is a seasoned national and homeland security professional who has spent over a decade at the Department of Homeland Security and the White House, driving whole-of-government policies on topics including trade, supply chain and transportation security, and commercial unmanned aerial systems. Previously, Ha was Chief Operating Officer for BSA | The Software Alliance where she helped design the organization’s strategic direction and oversaw revenue-generating licensing and compliance programs for the organization, driving $40-50 million in annual sales to BSA members. Ha also served as Chief of Staff at the Transportation Security Administration (TSA). There, she led the offices responsible for strategy, policy coordination, innovation, public affairs, and legislative affairs. In that role, she worked with Congress and stakeholders to secure public-private partnership authorities for TSA, allowing for innovative approaches to addressing year-over-year growth in travel volume.


Mr. Alexis Long is Senior Vice President of Trade and Goods and Project Director for Dartmouth at Pangiam. Project Dartmouth utilizes AI and pattern analysis technologies to digest and analyze vast amounts of data in real-time and identify potential threat items in carry-on baggage, checked baggage, airline cargo, and shipments. After an early career in the UK government, Alexis was Chief Innovation Officer at the Department of Homeland Security’s Transportation Security Administration (TSA) and Director at London Heathrow, Europe’s busiest privately operated airport where he was responsible for Security Strategy and Cyber Defense.

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