A good gas detection system is usually large and expensive because it requires specialized sensors or complex algorithms. In this study, we use easily obtained gas sensors and a single-chip microprocessor with statistical techniques and fuzzy algorithms to design a gas detection system. This system is easy to transport, less expensive, and possesses learning ability. In our system, we use eight different types of easily obtained gas sensors. They are ceramic and can detect different gases. While some sensors can only detect a certain gas, others can detect a variety of gases. In the latter case, one cannot determine the detected gas, because under certain output conditions, different gases may produce the same output signal. How then can one determine the type of gas detected through the use of a multigas sensor? This is the key aspect of a gas detection system. In this study, we use a fuzzy algorithm to analyze the detected signal to distinguish the gas type, and then combine the data to calculate the concentration of the gas. We used multisensors, a fuzzy algorithm, and a single-chip circuit to design a gas detection system. This system is based on a modular design; thus one can respond to the need to replace any module or sensor in the system if necessary. This sensing system can be used to detect different gases and form a gas sensor network.