With the spread of COVID-19, occupancy estimation wason the rise to regulatepeople’smovement in public areasto further decrease the spreadof the diseaseand prepare for future pandemics.Much theory existson the problem of sensor placement, but this theory is mainly treated as a mathematical problem and often not applicable to real-life situationsdue to important real-life factors not being considered. Placing sensors is adifficult task,and it is hard knowingwhere to beginplacing themand what type of sensors to use. The purpose of thisthesis was to help with the problem onplacing sensors by investigatingmethods in a simulated environmentto create guidelines for placing sensors in public areasand evaluatethese placements through a formula.The results are compared to previous researchto prove that it is important to cover different types of hotspots within a building,and where these hotspots canbe foundin general buildings.To truly achieve good sensor placement involves several different things but what is most importantis to be able to track the movement of people, with the number of sensors being as low as possiblewhile still having good coverage.The formula proved to have both benefits and drawbacks, such asthe drawback ofnot consideringwhat kind of sensor is being evaluated. The results should be validatedin a more truthful simulation orin real-lifeto be able to be fully dependent on.