A time-effective coverage path can be decisive in catastrophic and war scenarios for saving countless lives where UAVs are used to scan an area looking for an objective. Given an area shaped as a polygon, a quadratic decomposition method is used to discretize the area into nodes. A model of the optimization problem constraint is created and solved using mixed-integer linear programming, taking into consideration simple dynamics and coverage path planning definitions. Simulations in different scenarios are presented, showing that the presence of no-fly zones can negatively affect the coverage time. The relationship between coverage time and the number of UAVs employed is nonlinear and converges to a constant value. The result has a direct impact on the evaluation of benefits and the cost of adding UAVs to a search mission.