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The main problems in wireless sensor technologies are the constrained energy resources (e. g., battery capacity, processing consumption), and their long-lasting operational capacity in the environment while collecting and sending data to the central station. So, in the design and development of wireless sensor networks, one of the main challenges is to achieve maximal battery life. Real time monitoring by implementation of wireless sensor networks contributes to minimization of potential production risks, emerging mainly from environmental influences and human actions. The main goal in this paper is to obtain minimal energy consumption of wireless sensor nodes while collecting distributed data in environmental parameters monitoring. The communication module and the controller should be in idle state as long as possible when they are not active. Energy consumption changes with the frequency of the transmitted measurement data by the sensors and send/receive configuration of the radio frequency modules. Therefore, all of these parameters should be chosen carefully in order to create an optimal environmental monitoring system. In this contribution the stochastic optimization method-genetic algorithm is used to minimize the energy consumption of the wireless sensor nodes depending on the frequency of the transmitted data and the period of the transmission process. The optimization method is implemented for different scenarios while the frequency of the transmitted data is increasing and the period of transmission of all the active components in a sensor node is increasing.