## 5 A Case Study on Reliable Pipeline Monitoring Using Cyber Physical Sensor Networks
### Sensing Techniques for Pipeline Monitoring  
One of the ways to detect leaks is by comparing the change in temperature profiles of the immediate surroundings of the pipeline due to the Joule Thompson Effect [37]. For compressed cases such as Liquefied Natural Gas (LNG), the difference is up to \(-190\)\({}^{\circ}\)C, but in case of underwater pipelines, there is only a subtle change in temperature. Temperature sensors for this purpose should be selected keeping the temperature gradient in mind. Distributed fiber optic sensors [38] provide a temperaturesignature and pinpoint the leak location. Optical fiber sensors need to be in close contact with the pipe so as to come in contact with a leaked fluid (Figure 10). Figure 10 illustrates an optical fiber-based leakage detection mechanism for gas pipelines using a distributed acoustic sensing technique that measure the backscatter that results due to disturbance caused in the fiber. The normal temperature profile and the temperature profile sensed from the fiber sensor in the presence of a leak are also illustrated. The fiber sensor is placed above the pipeline for gases and below the pipeline for liquids [13]. This sensor provides an effective solution for pipeline monitoring because of its low cost and easy installation. One attractive feature of optical fiber sensing is the fact that the optical fibers have already been installed and used for communication purposes along the pipelines [38]. Several techniques have been proposed for under-ground sensing of pipelines. Sensing soil properties can be useful to find abnormalities in soil [14]. Sensors can detect temperature variation in the soil due to leakage of hot liquids [36, 39]. Hydrocarbon vapor sensors can be used to detect the leakage of pipelines transporting liquefied natural gas [39]. Soil dielectric property sensors can be used to detect the leakage of crude oil pipelines [40, 41]. Acoustic sensors can be used to detect leaks in municipal water pipes, sewages, and oil and gas pipelines, respectively [29, 30, 31]. Since corrosion in pipelines makes the inner pipe surface vulnerable to leakages and any external or internal strike (like solid particles hitting the surface with high velocities) can result in leakages, it is also necessary to monitor pipes flowing fluid for the presence of solid particles. Using acoustic sensors to detect the presence of solid impurities such as sand in oil, the sensors are placed non-intrusively near the bends of the pipeline [42]. The solid particles collide with the surface of the pipeline at the bends which generate high frequency waves that are detected by the sensors. Mobile sensor robots move inside the pipeline to monitor pipeline conditions and to provide accurate measurements and readings about the defects appearing inside the pipeline at regular intervals. Industries are therefore interested in developing robots with ingenious designs so the whole pipeline can be scrutinized [43]. A recently developed Magnetostrictive Sensor (MsS) inspection system [44] is an intrusive sensor which detects corrosion in the pipelines. Research work in [45] describes Carnegie Mellon's robot Explorer II which is designed to be used in pipelines of different diameters as it has adjustable diameter and contains a number of inexpensive piezoelectric sensors to pinpoint leaks. In the research work described in [46], four different topologies of Multifunctional Robot for In-Pipe Inspection (MRINSPECT) are investigated. The research contribution in [47] identifies construction equipment to be one of the major causes of breakages of pipelines and proposes efficient acoustic sensing with noise cancellation that can detect the presence of such equipment and generate an alarm at the base station. Figure 10: Optical fiber-based leakage detection mechanism. PipeSense [48] has provided an alternate sensing method to acoustic sensing by incorporating induction based _ad hoc_ RFID wireless sensor networks for water pipelines.