Energy Efficient Data Acquisition Techniques Using Context Aware Sensing for Landslide Monitoring Systems

Prabha, R.; Ramesh, Maneesha Vinodini; Rangan, Venkat; Ushakumari, P. V.; Hemalatha, T.

doi:10.1109/jsen.2017.2730225

Cited by 39 publications

(22 citation statements)

References 14 publications

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“…The work carried out by Liu et al [19] have discussed about usage of non-convex optimization problem for solving allocation of power issues in body area network while performing energy harvesting. Usage of context-based sensing mechanism was also proven to affect energy saving as reported in the work of Prabha et al [20].…”

Section: Introductionmentioning

confidence: 90%

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A novel predictive optimization scheme for energy-efficient reliable operation of a sensor in dynamic scenarios

Jayasri¹,

Rao²

2020

IJECE

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Wireless Sensor Network (WSN) has been studied for more than a decades that resulted in evolution of the significant applications towards assisting in sensing physical information from human inaccesible area. It was also observed from existing sysem that energy attribute is the root cause of majority of the problems associated with WSN that also gives rise to various operational reliability issue. Therefore, the prime goal of the proposed study is to present a novel predictive optimization approach of data fusion in order to jointly address the problems associated with energy efficiency and reliable operation of sensor nodes in WSN. An analytical research approach is carried out in order to ensure that a time-based synchronization scheme contributes to offer an evolutionary approach towards significant energy optimization. A simulation-based benchmarking analysis is carried out to find that proposed system offers good energy-efficient performance in comparison to existing approaches.

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Section: Introductionmentioning

confidence: 90%

“…The system is modelling in a way where prior to fusion process when each sensor node wants to transmit data to its neighbor at that point it can adjust its transmission power to optimize the energy consumpsion. 20.  (A pkt-delay , E /bit )…”

Section: Endmentioning

confidence: 99%

A novel predictive optimization scheme for energy-efficient reliable operation of a sensor in dynamic scenarios

Jayasri¹,

Rao²

2020

IJECE

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“…Prabha et al [ 17 ], on the other hand, proposed a context aware sensing technique which could be utilized for landslide monitoring. According to their approach, given a set of data, a discrete wavelet transformation is performed to find out the lowest sampling rate, which meanwhile should be able to guarantee the reliability of data.…”

Section: Related Workmentioning

confidence: 99%

An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring

Shu

Xia

Chen

et al. 2017

Sensors

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Power management is crucial in the monitoring of a remote environment, especially when long-term monitoring is needed. Renewable energy sources such as solar and wind may be harvested to sustain a monitoring system. However, without proper power management, equipment within the monitoring system may become nonfunctional and, as a consequence, the data or events captured during the monitoring process will become inaccurate as well. This paper develops and applies a novel adaptive sampling algorithm for power management in the automated monitoring of the quality of water in an extensive and remote aquatic environment. Based on the data collected on line using sensor nodes, a data-driven adaptive sampling algorithm (DDASA) is developed for improving the power efficiency while ensuring the accuracy of sampled data. The developed algorithm is evaluated using two distinct key parameters, which are dissolved oxygen (DO) and turbidity. It is found that by dynamically changing the sampling frequency, the battery lifetime can be effectively prolonged while maintaining a required level of sampling accuracy. According to the simulation results, compared to a fixed sampling rate, approximately 30.66% of the battery energy can be saved for three months of continuous water quality monitoring. Using the same dataset to compare with a traditional adaptive sampling algorithm (ASA), while achieving around the same Normalized Mean Error (NME), DDASA is superior in saving 5.31% more battery energy.

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“…Qadori et al [22] have used fuzzy-approach along with consideration of mobile agents in order to conserve energy consumption. Usage of context-based sensing mechanism was also proven to affect energy saving as reported in the work of Prabha et al [23]. Han et al [24] have investigated coverage problems and its relationship with the energy attribute in WSN.…”

Section: Introductionmentioning

confidence: 96%

Analytical Modelling of Power Efficient Reliable Operation of Data Fusion in Wireless Sensor Network

Jayasri¹,

Rao²

2018

IJECE

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Irrespective of inclusion of Wireless Sensor Network (WSN) in majority of the research proposition for smart city planning, it is still shrouded with some significant issues. A closer look into problems in WSN shows that energy parameter is the origination point of majority of the other problems in resource-constrained sensors as well as it significant minimizes the reliability in standard sensory operation in adverse environment. Therefore, this manuscript presents a novel analytical model that is meant for establishing a well balance between energy efficiency over multi-path data forwarding and reliable operation with improved network performance. The complete process is emphasized during data fusion stage to ensure data quality too. A simulation study has been carried out using benchmarked test-bed of MEMSIC nodes to find that proposed system offers good energy conservation process during data fusion operation as well as it also ensure good reliable operation in comparison to existing system.

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Energy Efficient Data Acquisition Techniques Using Context Aware Sensing for Landslide Monitoring Systems

Cited by 39 publications

References 14 publications

A novel predictive optimization scheme for energy-efficient reliable operation of a sensor in dynamic scenarios

A novel predictive optimization scheme for energy-efficient reliable operation of a sensor in dynamic scenarios

An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring

Analytical Modelling of Power Efficient Reliable Operation of Data Fusion in Wireless Sensor Network

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