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Gas leaking in gas production industry is a serious issue which could cause explosion or pose a high risk to human life. The searching of leaking gas can be performed by robots. It is better than using human beings because searching of leaking gas is a high risk task. Most of the gas sensors used in industries is semiconductor metal-oxide (MOX) type due to its low cost, ease of use, high sensitivity and fast response time in gas sensing, and ability to detect large number of gases. However, there is a fatal limitation i. e. long recovery time after the exposure of the target gas. It definitely causes robots to fail in gas/odour plume searching tasks due to delay of responses during the absent of gas plume. This paper proposes a sensing algorithm based on evidential theory which is using certainty factors and evidential reasoning to overcome the long recovery problem. Based on the conducted experiments, the proposed algorithm has improved the accuracy and reliability while maintaining its performance in recovery time. It performs better than other algorithms such as simple threshold methods, transient response algorithm and system modelling approach. Keywords-Gas detection, Certainty Factor Sensing, Odour plume tracking, MOX Gas Sensor.

Overcoming Long Recovery Time of Metal-Oxide Gas Sensor With Certainty Factor Sensing Algorithm