The UnderSec consortium has successfully completed its first demonstration phase at Lavrion Port, Greece, held from 16 to 20 March 2026. This on-site activity brought together project partners to rehearse, deploy, and demonstrate the developed technologies in realistic port conditions.
To validate the method, the authors implemented an experiment with four sensors deployed along the north coast of Crete, from the Rethymno to the Lasithi districts. The Area of Interest was defined over central Crete, and multiple transmitters were activated within this region to test how well the algorithm could estimate their positions. Real sensor data, including bearing measurements and divergence, were used to feed the triangulation and centroid steps.
The study does not stop at theory: it presents a full algorithmic pipeline, from reading sensor data to delivering positions on a map. The algorithm is divided into clear stages, including reading and storing the input, computing bearing paths and quadrilaterals, filtering out unhelpful cases, reducing information to triads of sensors, and finally producing outputs that can be used for centroid-based position estimation. Each step is designed to keep the computation efficient and avoid unnecessary calculations in areas that are not relevant.
The paper explains triangulation in simple geometric terms: sensors measure angles, not distances, and their bearing lines intersect to form small polygons where a transmitter might be. When more than one transmitter is present, this becomes more complex, and traditional two-sensor approaches no longer suffice. The authors show that by using at least three sensors and carefully analysing how their bearing paths intersect, it is possible to separate the different triangulation areas and link them to individual transmitters.
In many security and monitoring scenarios, it is not enough to detect that “something is there” – we also need to know where several transmitters are, often at the same time. The new study by Staridas et al. proposes a triangulation-based method that can estimate the position of multiple transmitters using a fixed network of sensors spread over a large area. Instead of relying on expensive hardware that measures distance, the method uses “range-free” sensors, which only need to know the direction of the signal and not how far away it is.
Although the scientific article that inspired these news items focuses on wireless spectrum monitoring and security-related use cases, the methods developed are broadly applicable. Any situation where sensors are used to observe an area—on land, at sea or underwater—can benefit from a clear picture of where coverage is strong and where it is weak. This includes environmental monitoring, disaster response, wildlife tracking and the protection of critical infrastructure, all of which are relevant to UnderSec’s mission.
No monitoring system is perfect, and real-life situations often involve unexpected changes, such as sensor malfunctions, maintenance needs or environmental shifts. The UnderSec study includes scenarios that explore what happens when a sensor fails within the network and how this affects the overall ability to detect new transmitters. These examples show that some failures can have a strong impact on coverage, especially in areas where the network is already under pressure.
Installing or upgrading a sensor network in the real world is expensive and time-consuming, especially when it involves critical areas such as ports, coastal zones or other sensitive infrastructures. UnderSec’s research demonstrates how planning can be significantly improved by simulating different sensor configurations on screen before any physical changes are made in the field. This reduces the risk of trial-and-error deployments and helps make better use of public resources.
Behind the user-friendly maps developed in UnderSec lies a rigorous scientific method that uses geometry, signal behaviour and advanced algorithms. Traditionally, analysing wireless sensor coverage requires dealing with many variables: sensor locations, detection ranges, angles, obstacles and signal interferences. This is often described in mathematical language that can be difficult to access for non-specialists, even though the decisions based on these analyses affect many people.
The UnderSec project is working to make complex sensor networks easier to understand and manage for everyone involved, from engineers to public authorities and citizens. In many monitoring systems, such as those used to protect critical infrastructures or coastal areas, sensors can be affected by other transmitters in their surroundings, creating “blind spots” where detection becomes weaker. These blind spots are usually hidden behind technical details and are difficult to see without advanced expertise.
