UnderSec relies on networks of sensors to detect and localise unknown transmitters around areas of interest, including critical and underwater infrastructures. In many cases, not all installed sensors can be active at the same time, due to energy, cost or operational limits, so it becomes crucial to decide which sensors to switch on and how to orient them to maximise coverage.

The article “A Constrained-Aware Genetic Algorithm for Coverage Optimization in Range-Free Sensor Networks” tackles exactly this challenge. The authors formulate a problem where a fixed number of sensors must be chosen from a larger pool and each active sensor must be assigned one of several possible angular sectors, taking into account blind zones caused by previously detected transmitters. They then propose a constraint‑aware genetic algorithm that automatically searches for near‑optimal activation and orientation patterns while always respecting the requirement that exactly K sensors are active.

For UnderSec, this work offers a practical optimisation engine that can support rapid reconfiguration of sensor networks when threats or environmental conditions change, helping to maintain strong triangulation coverage without the need for exhaustive search.