Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Aircraft tyre

The algorithm detects anomalies in the radio spectrum used for civil aviation communications and sends them as notifications to inspectors. In doing so, the algorithm supports the daily work of these inspectors.

Last change on 24th of March 2026, at 14:32 (CET) | Publication Standard 1.0
Publication category
Impactful algorithms
Impact assessment
Field not filled in.
Status
In use

General information

Theme

Space and Infrastructure

Begin date

03-2025

Contact information

www.rdi.nl/contact

Link to publication website

https://www.rijksoverheid.nl/onderwerpen/telecommunicatie/nationaal-frequentiebeleid

Responsible use

Goal and impact

The algorithm supports inspectors in surveillance by analysing large amounts of data and detecting possible disruptions. Disturbances in the civil aviation band can occur day and night, with some disturbances having higher priority than others. The algorithm is set up to detect important disruptions immediately and make them visible to inspectors, enabling timely follow-up. This also makes it easier to detect disruptions that occur outside office hours. This gives inspectors more scope to use their expertise in other parts of the process.

Considerations

It is not possible to manually monitor the civil aviation band day and night because of the large amount of frequencies and data. The inspectors are therefore supported by interference reports from organisations. By deploying the algorithm watching along with the inspectors, the chances of disturbances being missed are reduced. Ultimately, the inspector himself always decides whether the outcome of the algorithm is actually a disruption and whether action should be taken accordingly.

Human intervention

There is always human intervention, so there is no automatic action based on the algorithm. The outcome of the algorithm is a list of possible disturbances and a frequency graph per measurement location in the Netherlands. This list is presented to the inspector every morning. Based on experience, the inspector decides whether there are actual disturbances in the list and whether action should be taken.

Risk management

There is a chance that the algorithm may make mistakes. For example, it may detect disturbances that are not actual disturbances but belong to legitimate aeronautical communications. Also, the algorithm may miss disturbances when there is an actual disturbance. This risk is mitigated by the fact that there is always human intervention by an inspector assessing whether and how the results are followed up. In addition, the algorithm is re-trained monthly to make the outcomes as reliable as possible.

Legal basis

The Telecommunications Act is a Dutch law that sets rules for (providers of) communication networks and services. Among other things, it regulates user protection, providers' duty of care for safety and security and sets obligations for network operators.

Links to legal bases

Telecommunications Act: https://wetten.overheid.nl/BWBR0009950/2025-09-01

Elaboration on impact assessments

The radio spectrum is public data and available to anyone with a suitable receiver and antenna. No personal data is recorded, stored or processed for this algorithm.

Operations

Data

The algorithm uses the Landelijk Meetnet Telecom (LMT). The LMT consists of 15 measurement stations in the Netherlands that make a "scan" of the entire radio spectrum every minute. This scan consists of amplitude measurements of all frequencies within the measuring range. Only the civil aviation band (108-137 MHz) is used by the algorithm.

Technical design

The algorithm works on the basis of statistical analysis. It analyses on the basis of 2 years of historical measurement data what is, on average, the normal situation per frequency. It looks at signal amplitude, occupancy and signal width. Based on that analysis, cut-off values are defined. The daily measurements are then compared with the cut-off values and the outliers are marked as disturbances. Every month, the algorithm is re-trained.

External provider

Internally developed

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