Airport security stakeholders have the desire to create a seamless passenger flow, to relieve passengers from perceived stress during security, and most importantly to maintain a high security level. To achieve this, factors like type of screening equipment, number of security lanes, a (dynamic) staffing model and a differing passenger type are of influence. One critical piece in the puzzle towards an improved screening process still is the operator and its performance in human-essential tasks like x-ray image analysis. But how to achieve and maintain high performance standards in screening for prohibited objects?
Whereas our previous articles on the transition to EDS CB with CT machines focused on the component of initial training, in this blog post we share our experience on how image analysis can increase in performance. We look at three factors – Human Perception, Checkpoint Environment and CONOP & legislation - that influence screener performance the most. Focus in this third blog on the influence of legislation and CONOP.
The way in which operators analyse images depends on several factors. Legislation and work instructions describe the requirements and guidelines for image analysis to a certain degree. These requirements and guidelines provide for a standardised way of working which is necessary in the dynamic environment of airport security. Also, standards are enablers for monitoring purposes, which is essential in airport security.
Airport security is evolving by implementing State-of-the-Art Technology. In relation to image analysis CONOP this brings change as well. By introducing CT technology in the security checkpoint, the operator is able to analyse a 3D image instead of a 2D image. When using an AI powered operator assist functionality for threat detection, the operator gets a trigger to search for a specific threat. It is this type of technology that requires new ways of working and a change in legislation and CONOP. It all leads back to the number one priority for image analysis: detecting threats and preventing them from entering security restricted areas.
In this blog we describe three factors that impact operator performance on image analysis. First, the 20/10 time on task legislation is described. Then, the influence of the threat list and types and the CONOP on image analysis are outlined.
Time on task legislation
Operators need to maintain a high awareness level at all times during their tasks. Specifically, for image analysis legislation describes a maximum time of 20 minutes image analysis when there is a continuous flow of images followed by a period of 10 minutes performing other tasks. This 20/10 rule impacts the operation a lot, because operators must rotate which impacts the individual work flow and the flow of the security checkpoint.
Threat list
Operators must search for several threats which can be categorized in sharp items, firearms, blunts, miscellaneous and Improvised Explosive Devices (IEDs).
Figure 1 - Sharp object on left of image
Figure 2 - Firearm in centre of image
This is an impressive list and therefore image analysis is considered an intense task. Specifically, the comprehensive visual inspection process of identifying an IED is sufficiently more complex than the other threat categories. This complexity is due to various reasons:
An IED consists of multiple components. The other threat categories mainly contain one component.
The IED components can manifest in multiple forms; explosives can resemble a chess piece, or the content of a soda-can, and the power source can be an iPad;
Numerous combinations are possible between the IED components;
An IED can be composed of everyday items that are frequently present in cabin baggage, such as laptops.
Figure 3 - Improvised Explosive Device with clutter (left) and without clutter (right).
With the introduction of Explosive Detection Systems (EDS), the operator is assisted by an explosive threat detection algorithm in the search for IEDs.
(Non-) OSR CONOP
Whether or not the primary operator is qualified to perform resolution of EDS alarms, depends on the airports’ Concept of Operations (CONOP). This can be either an OSR (On Screen Resolution) or non-OSR CONOP. Given that the human eye is not able to distinguish bare explosive material from harmless material, the On Screen Resolution (OSR) of alarms is not allowed in many countries. In a non-OSR CONOP, images with EDS alarms are rejected (by the system) for secondary alarm resolution with additional technology – such as Explosive Trace Detection (ETD) or Liquid Explosive Detection – regardless of the screening operator’s decision. Yet, the primary operator must still search for IEDs in such images. If an IED is detected, a High Threat situation occurs and different procedures follow up. But why do operators still search for IEDs in all available images? Why still search for IEDs in images of which the EDS algorithm indicates no potential explosive substances are detected? Why not have operators only search for full IED’s when the EDS algorithm indicates an alarm?
Figure 4 - Image with EDS alarm
Changing the threat list in relation to a non-OSR CONOP will benefit the operator performance. The extent to which, should result from a trial. Within such a trial, the current non-OSR situation would have to be compared to a non-OSR situation where operators only search for full IEDs when an EDS algorithm indicates an alarm, provided that the EDS algorithm operates at 100%. Insight on the effect of the threat list on the operators and their performance that will result from this trial, might provide reason to revise and change the legislation and CONOP. Not only will this improve operator performance, it could also contribute to an higher operator satisfaction.
By implementing the newest technology such as CT scanners and adapting the CONOP to the capabilities of the technology and the changing focus for the human factor – why still hold on to 20/10 time on task legislation, threat list and CONOP -is it time for change?
This blog post was the final blog post on the series on influence of operator performance on image analysis. Our next blog will be on operator satisfaction in relation to operator performance from the viewpoint of the field experts. In this blog we will discover the link between operator satisfaction and operator performance.
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