Wireless sensor networks are a new generation of networks that usually consist of a large number of low power sensors, deployed randomly in an area and each node is wirelessly connected with all other nodes in its vicinity. These sensors can monitor different parameters such as temperature, humidity, pressure, vibration intensity and sound intensity. Due to wireless sensor network’s reliability, self-organization, flexibility and ease of deployment, their existing and potential applications vary widely. As well, they can be applied to almost any environment, especially those in which conventional wired sensor systems are impossible or unavailable, such as in inhospitable terrains, battle?elds, outer space, or deep oceans. The main purpose of wireless sensor networks is to collect information about the surrounding environment of network’s sensors. In wireless sensor networks, reduction in sensor’s energy consumption is one of the important issues that have drawn researcher’s attention to it. Artificial immune systems are a number of algorithms iired by the human immune system. Many properties of the immune system are of great interest for computer scientists and engineers. The cells of the system are distributed all over the body and, most importantly, are not subject to any centralized control. The system can learn the structures of pathogens, so that future responses to the same pathogens are faster and stronger. The natural immune system mostly consists of lymphocytes and lymphoid organs. There are two types of lymphocytes: the T-Cell and B-Cell both created in the bone marrow. The T-Cell first becomes mature in the thymus; whereas the B-Cell is already mature after creation in the bone marrow. This research proposed the using of artificial immune systems in designing wireless sensor networks with low energy consumption. One of the advantages of the algorithms which are based on the pattern of artificial immune system is that they use memory cells. These cells preserve and produce the suitable antigen after identifying the routes with the most attenuation. Memory cells are used to choose the sensor cells to which the data will be sent. Therefore the process of identifying the node with the most energy is done quicker. Also, danger theory is used to prevent sending the packet to the nodes with the least neighboring. Each time that routes with more consumed energy and attenuation are detected, using the crossover operator a new generation is created that is added to memory cells. In other word, routes that have the most attenuation and energy consumption are found and this procedure increases the network’s accuracy. The results show that our algorithm is effective and it is working better than flooding and GEAR algorithms. In the other hand, our algorithm has maximum lifetime and minimum of attenuation compared with others. Keywords: Wireless sensor network, energy consumption reduction, artificial immune system, danger theory