# Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion
###### Abstract  
With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor. os 2021 6 January 2021 9 January 2  
and carelessness in disposing of wastes generate unnecessary fumes, are the significant reasons of fume leakages. An article presented in the media revealed that burning wood, biomass, and dung led to 326,000 of the estimated 645,000 premature deaths from outdoor air pollution, which constitutes about 50% of the total deaths due to outdoor pollution [3]. Harmful gases such as Liquid Petroleum Gas (LPG), Compressed Natural Gas (CNG), Methane, Propane, and other flammable and toxic gases, if not used carefully and adequately, may lead to accidents and, in some cases, disastrous consequences. A gas leak is an unintended crack, hole, or porosity in a joint or machinery, which excludes different fluids and gases, allowing the escape of a closed medium. In any plant or industrial setup, a gas leak test is a quality control step that must be performed before a device is set up. As a precautionary measure, gas sensors are set up near the leakage prone equipment. However, the sensors are not able to detect gas in a mixed gas environment. Sensors are also prone to and limited to their operating characteristics. Human intervention is not always possible in leakage situations, primarily due to the hazardous nature of gases. Smoke emissions during leakages give rise to unclear vision problems, fire and smoke leakages demand the immediate evacuation of persons with mobile disability. Breathing these dangerous fumes may lead to dizziness, unconsciousness, and mass disaster if not treated properly. In the case of gas leakage in chemical factories, it can cause explosions. Therefore, detecting gas leakages and explosions within a short period is of utmost importance. Early detection of gas leakage with higher accuracy and reliability using the state-of-art techniques is an essentially required assistive technology solution. Detecting a particular gas or different gases in the mixture of gases is also challenging and requires technological attention. Existing methods of mixed gas detection methods include a way of using a Colorimetric Tape [4]. In this method, a dry material of tape reacts with the gas being emitted and leaves a special stain for different gases under consideration. The more the gas concentration, the darker the stain on the tape [5]. Gas Chromatography is another methodology that separates mixtures of gases based on differences in boiling points, polarity, and vapor pressure [6]. This method has high separation efficiency but requires a large apparatus and workforce to operate [7].