Link Quality Analysis of Wireless Sensor Networks for Underground Infrastructure Monitoring: A Non-backfilled scenario

In this work, the combination of capabilities provided by Wireless Sensor Networks (WSN) with parameter observation in a school garden is employed in order to provide an environment for school garden integration as a complementary educational activity in primary schools. Wireless transceivers with energy harvesting capabilities are employed in order to provide autonomous system operation, combined with an ad-hoc implemented application called MySchoolGardenApp, based on a modular software architecture. The system enables direct parameter observation, data analysis and processing capabilities, which can be employed by students in a cloud based platform. Providing remote data access allows the adaptation of content to specific classroom/homework needs. The proposed monitoring WSN has been deployed in an orchard located in the schoolyard of a primary school, which has been built with EnOcean’s energy harvesting modules, providing an optimized node device as well network layout. For the assessment of the wireless link quality and the deployment of the modules, especially the central module which needs to receive directly the signals of all the sensor modules, simulation results obtained by an in-house developed 3D Ray Launching deterministic method have been used, providing coverage/capacity estimations applicable to the specific school environment case. Preliminary trials with MySchoolGardenApp have been performed, showing the feasibility of the proposed platform as an educational resource in schools, with application in specific natural science course content, development of technological skills and the extension of monitoring capabilities to new context-aware applications.

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Magnetic Induction Technology-Based Wireless Sensor Network for Underground Infrastructure, Monitoring Soil Conditions, and Environmental Observation Applications: Challenges and Future Aspects

Journal of Sensors ◽

10.1155/2022/9332917 ◽

2022 ◽

Vol 2022 ◽

pp. 1-18

Author(s):

Pratap Singh ◽

Rishi Pal Singh ◽

Yudhvir Singh ◽

Jasgurpreet Singh Chohan ◽

Shubham Sharma ◽

...

Keyword(s):

Sensor Networks ◽

Magnetic Induction ◽

Sensor Nodes ◽

Wireless Sensor ◽

Soil Conditions ◽

Long Distance ◽

Infrastructure Monitoring ◽

Research Areas ◽

Underground Infrastructure ◽

Type Water

Wireless sensor networks (WSNs) especially with sensor nodes communicating with each other in medium other than air have been naive area of research since the last few years. In comparison to underwater communication, wireless underground sensor networks (WUSNs) are now being used in a large number of applications ranging from environmental observation, estimating chances of earthquake, communicating in underground tunnels or mines, and infrastructure monitoring to soil monitoring for agricultural purposes. In spite of all such promising applications, due to harsh and dynamically changing soil characteristics including soil type, water content in soil, and soil temperature, underground communication with conventional electromagnetic (EM) wave-based technology could not prove to be feasible for long-distance communication. Alternatively, due to magnetic permeability of soil being similar to air, magnetic induction- (MI-) based approach was adopted using magnetic coils as antenna for sensor nodes. Subsequently, MI waveguide and 3D coil mechanisms were considered to improve the system efficiency. Attributing to different characteristics of underlying transmission channels, communication protocols as well as architecture of MI-based WUSNS (MI-WUSNs) have been developed with different approaches. In this review paper, in addition to the latest advancements made for MI-WUSNs, closely associated areas of MI-WUSNs have also been explored. Additionally, research areas which are still open to be worked upon have been detailed out.

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Recurrent Neural Network Based Link Quality Prediction for Wireless Sensor Networks

2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) ◽

10.1109/icccs52626.2021.9449134 ◽

2021 ◽

Author(s):

Ming Xu ◽

Jinwei Xu ◽

Yu Xia ◽

Jian Xie ◽

Wei Liu ◽

...

Keyword(s):

Neural Network ◽

Wireless Sensor Networks ◽

Sensor Networks ◽

Recurrent Neural Network ◽

Link Quality ◽

Wireless Sensor ◽

Quality Prediction ◽

Link Quality Prediction

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Swarm-Intelligence-Centric Routing Algorithm for Wireless Sensor Networks

Sensors ◽

10.3390/s20185164 ◽

2020 ◽

Vol 20 (18) ◽

pp. 5164

Author(s):

Changsun Shin ◽

Meonghun Lee

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Swarm Intelligence ◽

Network Performance ◽

Ad Hoc ◽

Routing Algorithm ◽

Optimal Solution ◽

Link Quality ◽

Wireless Sensor ◽

Control Message

The swarm intelligence (SI)-based bio-inspired algorithm demonstrates features of heterogeneous individual agents, such as stability, scalability, and adaptability, in distributed and autonomous environments. The said algorithm will be applied to the communication network environment to overcome the limitations of wireless sensor networks (WSNs). Herein, the swarm-intelligence-centric routing algorithm (SICROA) is presented for use in WSNs that aim to leverage the advantages of the ant colony optimization (ACO) algorithm. The proposed routing protocol addresses the problems of the ad hoc on-demand distance vector (AODV) and improves routing performance via collision avoidance, link-quality prediction, and maintenance methods. The proposed method was found to improve network performance by replacing the periodic “Hello” message with an interrupt that facilitates the prediction and detection of link disconnections. Consequently, the overall network performance can be further improved by prescribing appropriate procedures for processing each control message. Therefore, it is inferred that the proposed SI-based approach provides an optimal solution to problems encountered in a complex environment, while operating in a distributed manner and adhering to simple rules of behavior.

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