Classification of Malodor Gases in Greenhouse Environment Using Artificial Intelligence Technique

Malodor gases are the presence of unwanted gases that can be harmful to our health. It can also affect the condition of plants, especially in a greenhouse environment. These gasses can be considered an important environmental pollution issue that needs to be monitored. To overcome this problem, the development of an instrumentation technology system is needed to detect and classify the presence of malodor gases. In this paper, an intelligent technique is proposed based on the concept of electronic nose and environmental monitoring technology. The proposed system employs several chemical gas sensors mounted with an Arduino microcontroller to detect the presence of malodor gases. Then, various artificial intelligence methods such as Support Vector Machine (SVM), Artificial Neural Networks (ANN) and Decision Tree Algorithms (DTA) are used to classify the types of gasses and compared their performance with each other. Our proposed system can enhance the reproducibility, reliability, and selectivity of the odour sensor output. This system utilizes the function of artificial intelligence technique in environmental monitoring, its applications in a greenhouse and detecting the smell of particular volatile organic compounds like ammonia, carbon dioxide and methane at different concentrations.