One of the approaches to mimic the remarkable abilities of the human olfactory system is by the design of computer-controlled sensor arrays that are capable of detecting and distinguishing a different range of smells and odors with consistent monitoring, referred to as electronic noses. This chapter introduces the opportunity of integrating smell sense in robots by the use of artificial neural networks. The study proposes a structure for integrating electronic noses in robots to add the capabilities of smell-related assignments, typically to recognize hazardous substances such as sampling the air and decide its actions based on this information. Utilizing the proposed algorithm allows experts in this field to be aware of gas leakage areas and thus reduce unexpected incidences. The effectiveness of the algorithm is demonstrated using real-world samples, and the performance is examined via quantitative metrics and analysis. The results show that the proposed algorithmic framework outperforms state-of-the-art methods with an error rate of only 0.0999%. © 2018, IGI Global.

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