ORIGINAL Design of a correlated validated CFD and genetic algorithm model for optimized sensors placement for indoor air quality monitoring Monireh Sadat Mousavi 1 & Khosro Ashrafi 2 & Majid Shafie Pour Motlagh 2 & Mohhamad Hosein Niksokhan 2 & HamidReza Vosoughifar 3,4 Received: 12 March 2017 /Accepted: 21 August 2017 # Springer-Verlag GmbH Germany 2017 Abstract In this study, coupled method for simulation of flow pattern based on computational methods for fluid dynamics with optimization technique using genetic algorithms is pre- sented to determine the optimal location and number of sen- sors in an enclosed residential complex parking in Tehran. The main objective of this research is costs reduction and maxi- mum coverage with regard to distribution of existing concen- trations in different scenarios. In this study, considering all the different scenarios for simulation of pollution distribution using CFD simulations has been challenging due to extent of parking and number of cars available. To solve this prob- lem, some scenarios have been selected based on random method. Then, maximum concentrations of scenarios are cho- sen for performing optimization. CFD simulation outputs are inserted as input in the optimization model using genetic al- gorithm. The obtained results stated optimal number and lo- cation of sensors. 1 Introduction Because of sensors technology developments, wide applica- tion of wireless communications and sensor network has been considered in industry and daily life [1]. These technological advances have created new opportunities for monitoring, collecting and processing environmental information that have not already been available [2]. Designing sensor network to monitor environmental plays a significant role in protecting the environment and will play a sig- nificant role in the future [1]. Given significant progress in the field of environmental sensors, there has been limited progress in the development of environmental monitoring pollutants, determination of ex- posure rate and appropriate response in such events [3]. In modern societies, urbanization and industrialization have a great impact on public health and the environment; and one of the critical needs associated with the control of environmental pollution is continuous air pollution monitoring. Prediction of locating sensors for monitoring distribution of pollutants in indoor environment and providing control methods is one of the most complex issues in management of air quality due to the impact of various factors that are out of control. Providing a more economical model with the desired accuracy is of special importance. The main focus of this study is indoor sensor system. It should be mentioned that scope of application of sensors may be wider than indoors, an example of outdoor sensor system is intelligent transportation systems and in issues re- lated to agricultural science it can include groundwater pollut- ants, etc. [4]. The major problem in accurately predicting flow behavior is the effect of various factors on air circulation. In order to determine the air flow pattern in enclosed areas, several methods such as experimental methods, analytical methods and Computational Fluid Dynamics (CFD) have been used. Experimental methods are mostly difficult, costly and time consuming. In contrast, analytical methods provide a simple and quick solution but they are generally used for simple * Monireh Sadat Mousavi msmousavi@ut.ac.ir 1 Faculty of Environment, University of Tehran, Tehran, Iran 2 Department of Engineering, Faculty of Environment, University of Tehran, Tehran, Iran 3 Department of Civil Engineering of Hawaii University at Manoa, Honolulu, HI, USA 4 Islamic Azad University of Tehran South Unit, Tehran, Iran Heat Mass Transfer DOI 10.1007/s00231-017-2138-9