We present an optimization problem for automatic irrigation systems. The solution approach, based on the generalized set covering problem, considers a specific urbanization with factors such as risk assessments and associated costs, which contribute to scalability and long-term sustainability. A mathematical model is proposed to minimize the number of sensors and sprinklers, where the aim is to maximize the irrigation efficiency of a public square. The preliminary results allow us to analyze different morphologies of public spaces. The methodology used considers two phases: the first phase optimizes the number of sensors and their placement, maintaining a high percentage of coverage; Then, the second phase optimizes the number of sprinklers and their placement, achieving full coverage. It is concluded that the module has the ability to be extensible and scalable, with minimum computational time. The model can be integrated into a web app with a TRL4 maturity level.