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A proposed scalable design and simulation of wireless sensor network-based long-distance water pipeline leakage monitoring system.

Almazyad AS, Seddiq YM, Alotaibi AM, Al-Nasheri AY, BenSaleh MS, Obeid AM, Qasim SM - Sensors (Basel) (2014)

Bottom Line: To ensure the reliability of water pipelines, they must be monitored effectively.Wireless Sensor Networks (WSNs) have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines.The proposed equations are analyzed and the results are validated using simulation.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Engineering, King Saud University, Riyadh 11421, Saudi Arabia. al_nasheri@yahoo.com.

ABSTRACT
Anomalies such as leakage and bursts in water pipelines have severe consequences for the environment and the economy. To ensure the reliability of water pipelines, they must be monitored effectively. Wireless Sensor Networks (WSNs) have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines. In this paper, we present a scalable design and simulation of a water pipeline leakage monitoring system using Radio Frequency IDentification (RFID) and WSN technology. The proposed design targets long-distance aboveground water pipelines that have special considerations for maintenance, energy consumption and cost. The design is based on deploying a group of mobile wireless sensor nodes inside the pipeline and allowing them to work cooperatively according to a prescheduled order. Under this mechanism, only one node is active at a time, while the other nodes are sleeping. The node whose turn is next wakes up according to one of three wakeup techniques: location-based, time-based and interrupt-driven. In this paper, mathematical models are derived for each technique to estimate the corresponding energy consumption and memory size requirements. The proposed equations are analyzed and the results are validated using simulation.

No MeSH data available.


Related in: MedlinePlus

Energy consumption analysis results for (a) Location-based wakeup (1st node); (b) Time-based wakeup (1st node); (c) Interrupt-driven wakeup (1st node); (d) Location-based wakeup (5th node); (e) Time-based wakeup (5th node); (f) Interrupt-driven wakeup (5th node); (g) Location-based wakeup (25th node); (h) Time-based wakeup (25th node); (i) Interrupt-driven wakeup (25th node); (j) Location-based wakeup (50th node); (k) Time-based wakeup (50th node); (l) Interrupt-driven wakeup (50th node).
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f4-sensors-14-03557: Energy consumption analysis results for (a) Location-based wakeup (1st node); (b) Time-based wakeup (1st node); (c) Interrupt-driven wakeup (1st node); (d) Location-based wakeup (5th node); (e) Time-based wakeup (5th node); (f) Interrupt-driven wakeup (5th node); (g) Location-based wakeup (25th node); (h) Time-based wakeup (25th node); (i) Interrupt-driven wakeup (25th node); (j) Location-based wakeup (50th node); (k) Time-based wakeup (50th node); (l) Interrupt-driven wakeup (50th node).

Mentions: The analysis results for energy consumption are plotted in Figure 4. The x-axis represents the different values of N, which is the number of member nodes in a group, e.g., when n = 15, that refers to a 15-node group deployed in the pipeline. The y-axis refers to the energy consumed by a single node that is a member of an N-node group. On each plot, there are two types of curves: solid line and dashed line curves that correspond to the minimum and the maximum distances of separation between the RFID tags respectively. That is, the solid line is associated with Δd = 10 m while the dashed line is associated with Δd = 500 m. Moreover, each plot contains four curves that represent total trip times of 10, 30, 50 and 70 h. Figure 4 also consists of twelve plots, from (a) to (l), arranged in a matrix of four rows and three columns. The first, second and third columns of the matrix depicts the results of analyzing the location-based, the time-based and the interrupt-driven wakeup methods respectively. In other words, the first, the second and the third columns of the matrix depicts the results of analyzing Equations (8), (10) and (12) respectively. Each row of the matrix focuses on analyzing a specific node within the group using the three wakeup methods. That is, the first, second, third and fourth rows refer to the 1st, the 5th, the 25th and the 50th nodes of the group being analyzed respectively.


A proposed scalable design and simulation of wireless sensor network-based long-distance water pipeline leakage monitoring system.

Almazyad AS, Seddiq YM, Alotaibi AM, Al-Nasheri AY, BenSaleh MS, Obeid AM, Qasim SM - Sensors (Basel) (2014)

Energy consumption analysis results for (a) Location-based wakeup (1st node); (b) Time-based wakeup (1st node); (c) Interrupt-driven wakeup (1st node); (d) Location-based wakeup (5th node); (e) Time-based wakeup (5th node); (f) Interrupt-driven wakeup (5th node); (g) Location-based wakeup (25th node); (h) Time-based wakeup (25th node); (i) Interrupt-driven wakeup (25th node); (j) Location-based wakeup (50th node); (k) Time-based wakeup (50th node); (l) Interrupt-driven wakeup (50th node).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3958258&req=5

f4-sensors-14-03557: Energy consumption analysis results for (a) Location-based wakeup (1st node); (b) Time-based wakeup (1st node); (c) Interrupt-driven wakeup (1st node); (d) Location-based wakeup (5th node); (e) Time-based wakeup (5th node); (f) Interrupt-driven wakeup (5th node); (g) Location-based wakeup (25th node); (h) Time-based wakeup (25th node); (i) Interrupt-driven wakeup (25th node); (j) Location-based wakeup (50th node); (k) Time-based wakeup (50th node); (l) Interrupt-driven wakeup (50th node).
Mentions: The analysis results for energy consumption are plotted in Figure 4. The x-axis represents the different values of N, which is the number of member nodes in a group, e.g., when n = 15, that refers to a 15-node group deployed in the pipeline. The y-axis refers to the energy consumed by a single node that is a member of an N-node group. On each plot, there are two types of curves: solid line and dashed line curves that correspond to the minimum and the maximum distances of separation between the RFID tags respectively. That is, the solid line is associated with Δd = 10 m while the dashed line is associated with Δd = 500 m. Moreover, each plot contains four curves that represent total trip times of 10, 30, 50 and 70 h. Figure 4 also consists of twelve plots, from (a) to (l), arranged in a matrix of four rows and three columns. The first, second and third columns of the matrix depicts the results of analyzing the location-based, the time-based and the interrupt-driven wakeup methods respectively. In other words, the first, the second and the third columns of the matrix depicts the results of analyzing Equations (8), (10) and (12) respectively. Each row of the matrix focuses on analyzing a specific node within the group using the three wakeup methods. That is, the first, second, third and fourth rows refer to the 1st, the 5th, the 25th and the 50th nodes of the group being analyzed respectively.

Bottom Line: To ensure the reliability of water pipelines, they must be monitored effectively.Wireless Sensor Networks (WSNs) have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines.The proposed equations are analyzed and the results are validated using simulation.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Engineering, King Saud University, Riyadh 11421, Saudi Arabia. al_nasheri@yahoo.com.

ABSTRACT
Anomalies such as leakage and bursts in water pipelines have severe consequences for the environment and the economy. To ensure the reliability of water pipelines, they must be monitored effectively. Wireless Sensor Networks (WSNs) have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines. In this paper, we present a scalable design and simulation of a water pipeline leakage monitoring system using Radio Frequency IDentification (RFID) and WSN technology. The proposed design targets long-distance aboveground water pipelines that have special considerations for maintenance, energy consumption and cost. The design is based on deploying a group of mobile wireless sensor nodes inside the pipeline and allowing them to work cooperatively according to a prescheduled order. Under this mechanism, only one node is active at a time, while the other nodes are sleeping. The node whose turn is next wakes up according to one of three wakeup techniques: location-based, time-based and interrupt-driven. In this paper, mathematical models are derived for each technique to estimate the corresponding energy consumption and memory size requirements. The proposed equations are analyzed and the results are validated using simulation.

No MeSH data available.


Related in: MedlinePlus