Vol: 1 Issue: 1
Development of an SMS-based accurate notification system for improved pipeline leakages
Gertrude A. Fischer, F. I. Anyasi, Sunday A. Ojomu
INTRODUCTION
The effective management and maintenance of pipelines are crucial for ensuring the safe and reliable transportation of fluids such as oil, gas, and water. Pipeline systems are subject to various risks and potential failures, including leaks, corrosion, and mechanical damage, which can lead to environmental hazards, disruptions in supply, and significant economic losses. To mitigate these risks and enhance the efficiency of pipeline maintenance, the development of an improved and accurate notification system is essential. Traditionally, pipeline maintenance has relied on periodic inspections and manual monitoring, which can be time-consuming, costly, and prone to human error. These conventional approaches often result in delays in identifying and responding to maintenance issues, increasing the chances of accidents or breakdowns. To overcome these limitations, there is a growing need for a more advanced and automated notification system that leverages cutting-edge technologies to detect, analyses, and to communicate pipeline maintenance requirements promptly. [1] Using wireless sensor networks, a data collection system for irrigation and gas pipelines is described. The design outcomes from the experimental prototype of a wireless sensor-based network for gathering pressure data for watering systems and gas pipelines were reported by the authors in this paper. The system's foundation consists of Telos B motes arranged in a WSN with an appropriate network protocol that also offers data control and aggregation.
The [2] research was presented. A study titled "Smart Pipes: Smart wireless sensor networks for leak detection in water pipelines" examined wireless smart sensor networks, which the authors claimed to be a practical method for keeping track of subterranean water pipes' pressure and, consequently, leaks. Their advantage over other widely used leak detection techniques is that they have some degree of redundancy, allowing for continuous monitoring without human involvement and preventing individual bad nodes from making the entire system obsolete. Smart wireless sensor networks with ultra-low power consumption can operate without maintenance for long periods of time. They can now be used with both traditional and cutting-edge power sources as a result [3] "Oil and Gas Pipeline Monitoring during COVID-19 Pandemic via Unmanned Aerial Vehicle" research was presented. He discussed the idea of using drones to conduct inspections and recording video and pictures in order to find potential hazards before they become serious. He also provided details of a survey that professionals in the oil and gas sector had undertaken to determine the functional and non-functional requirements of the suggested system. In [4], reliable solution was developed in the study titled "Remote Pipeline Monitoring Security System" for the wireless monitoring of the pipelines for various parameters that were embedded together. Remote monitoring was used to wirelessly monitor the pipelines in real time and report to the control center whenever a value was found that was higher than the threshold value. These pipelines underwent remote monitoring, which meant watching them from a distance. Temperature, relative humidity, dew point, liquefied petroleum gas leakage, liquefied petroleum gas leakage rate, liquefied petroleum gas leak rate, movement of persons around the facility, fire, and smoke are the variables that are tracked. A monitoring device was created and built to keep track of these parameters. To provide a reliable method of remotely monitoring the pipelines, a monitoring device for these parameters was designed, built, and software in the C programming language was created to communicate with the hardware.[5] [6] The principles and approaches are in "Recent Advances in Pipelines Monitoring and Oil Leakage Detection Technologies: Approaches". analyzed the state-of-the-art accomplishments of various leak detection and localization systems and conducted research on pipeline leak detection technology. The best leak detection technique for a given operating environment was chosen using comparative performance studies as a guide. The location of sensors in pipeline monitoring is then brought to the attention of additional study. Before a complete real-time leakage detection in the pipeline can be realized, research gaps must be filled.
Radio Frequency Identification (RFID) and mobile sensors based on MICA were combined in the study published in "Remote pipeline monitoring using wireless sensor networks" [7, 11] to enable effective remote pipeline monitoring. A prototype model was developed that enables actuators to react to detected anomalies while allowing a topology-aware robot agent to sense desired parameters. The system's cost and scalability were shown through thorough testing, but additional study is required to track the effects of fluid on mobile sensors. [8] developed a wireless sensor network of mobile sensors that may be employed inside the water pipelines in their study titled "Mobile sensor networks for optimal leak and backflow detection and localization in municipal water networks." A mixed integer nonlinear optimization problem is used to solve the placement of sensors and beacons in a single joint formulation. It was determined that the disjoint method was an effective and reliable solution for solving the sensor and beacon placement problem in WDSs due to the joint formulation's time complexity. In a later project, algorithms will be extended to WDSs with dynamic pipe flow rates.
In their article "Operation of remote mobile sensors for security of drinking water distribution systems [9] examined a mobile water sensor that can wirelessly capture and send data as it is being constructed and manufactured. Several test results showed that adding inline observatory systems to online monitoring systems was an effective strategy to boost security and reduce the mean time of threat detection.