# A Drone-Enabled Approach for Gas Leak Detection Using Optical Flow Analysis +
## 2 Literature Review  
Gas leak detection techniques can be classified into various categories based on the level of human involvement and employed technologies. The level of human involvement is one of the factors that would be important especially for the detection of possible hazardous gas leaks. The gas leak detection techniques can be classified into three main categories based on the level of human intervention, (a) automatic detection, (b) semiautomatic detection, and (c) manual detection. The automatic detection methods mostly include installed sensors and monitoring systems that can detect the leaks completely automated. Semiautomatic detection approaches require certain human inputs or assistance to perform the task and manual detection techniques involving the sensors that need to be directed by operators [6]. Gas leak detection techniques can also be categorized based on the employed technology. Some studies classify the detection approaches into optical and nonoptical due to the wide range of optical methods used for leak finding purposes [9; 10]. Moreover, they can be considered based on their detection approaches and grouped into direct and indirect approaches. The direct approach involves the use of systems and sensors like a thermal camera to find the possible gas emanations while in the indirect approach, the leaks are detected by measuring the variation in some of the parameters such as flow rate or pressure in the targeted system like pipeline [11]. One of the most used ways to categorize the gas leak detection methods is based on their technical nature [6; 12], (a) hardware-based techniques, and (b) software-based techniques. Hardware-based techniques basically use a sensing system to detect possible gas emanation. These methods can further be classified based on the type of sensors that they employ for detection. On the other hand, software-based techniques continuously monitor and analysis the parameters of a system like a pipeline to detect possible signs of gas leaks. The categories and the subcategories are demonstrated in Figure 1.  
Acoustic methods determine the existence of gas leaks based on the fact that escaping gas generates an acoustic signal as it flows through a crack in the pipe. The inspection can be carried out with handheld detection devices used by operators moving alongside the pipeline [13]. Moreover, continuous monitoring is possible using installed sensors on the pipeline's outerior with fixed distance [14]. Cable sensors are another type of sensor for gas leak detection. The cables are made of specific materials reacting when in contact with a certain medium. The changes in parameters can be monitored and utilized for leak detection purposes. Cable sensors are fast in responding and more sensitive than many other approaches. However, the cost of implementation is high and the difficulty of retrofitting the sensors to the existing pipelines are the main disadvantages of cable sensors. Additionally, cable sensors are not able to provide leak size estimation. Soil monitoring is another type of gas leak detection involving the use of tracer compounds on pipelines [15]. In this method, high sensitivity and low false alarm rates are the advantages and the high cost of applying this method is the main disadvantage. Optical methods for the purpose of leak detection can be categorized into passive and active techniques. In active methods, the targeted area is excited by an external radiation source. On the other hand, passive methods do not require excitation source [16]. The optical methods have many advantages including portability, contactless detection, and locating the origin of the leakage. In many scenarios, the optical sensor is installed on an aircraft or ground vehicle for detecting a long pipeline. One of the passive methods for gas leak detection is to employ a thermal imaging system. Thermal imaging systems visualize the temperature difference between leaked gas and the surrounding environment to detect leaks.