Abstract
Sensor networks are widely used nowadays. They can be used with various applications, such as monitoring, tracking, communication, and many more. The positioning of the sensors in the network is of great importance. It should enable full coverage, communication between sensors, and transmission of collected data. On the other hand, it is important to do this with as few sensors as possible. When the network is used for monitoring, it is important to consider the presence of impenetrable obstacles. They cover part of the coverage area of some of the sensors. This requires a different positioning of the sensors compared to the case without obstacles. For the solution, we propose an algorithm based on Ant Colony Optimization (ACO) methodology. We have shown how the algorithm works, when there are impenetrable obstacles in the observed space. Using the obstacles, areas of arbitrary shape can be modeled.