Routing with Renewable Energy Management in Wireless Sensor Networks

João, D. P.; Lima, Moysés M.; Balico, Leandro N.; Pazzi, Richard W.; Oliveira, Horácio A. B. F.

doi:10.3390/s21134376

Cited by 5 publications

(3 citation statements)

References 38 publications

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“…In addition, Llaria et al [103] apply wireless actuators [104] for intelligent management techniques in a microgrid environment. Junior et al [105] describe sensors used for management of energy generated by distributed renewable plants.…”

Section: Important Performance Parameters Of Actuators and Evolutionmentioning

confidence: 99%

Functionality Analysis of Electric Actuators in Renewable Energy Systems—A Review

Redekar

Deb

Ožana

2022

Sensors

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Various mechanical, hydraulic, pneumatic, electrical, and hybrid actuators can alter motion per the requirements of particular applications. However, except for electrical ones, all actuators are restricted due to their size, complex auxiliary equipment, frequent need for maintenance, and sluggish environment in renewable applications. This brief review paper highlights some unique and significant research works on applying electrical actuators to renewable applications. Four renewable energy resources, i.e., solar, wind, bio-energy, and geothermal energy, are considered to review electric actuators applicable to renewable energy systems. This review analyses the types of actuators associated with the mentioned renewable application, their functioning, their motion type, present use, advantages, disadvantages, and operational problems. The information gathered in this paper may open up new ways of optimization opportunities and control challenges in electrical actuators, thereby making more efficient systems. Furthermore, some energy-efficient and cost-effective replacements of convectional actuators with new innovative ones are suggested. This work aims to benefit scientists and new entrants working on actuators in renewable energy systems.

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Section: Important Performance Parameters Of Actuators and Evolutionmentioning

confidence: 99%

Functionality Analysis of Electric Actuators in Renewable Energy Systems—A Review

Redekar

Deb

Ožana

2022

Sensors

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“…In the context of the smart city river monitoring project, a water quality monitoring system [ 25 ] based on the Internet of Things was proposed, which offered an affordable and efficient online monitoring scheme. To minimize the power consumption [ 26 ] of wireless sensor transmission, an energy-aware geographic routing algorithm was implemented. In addition, a microcontroller-based water contamination monitoring automation system [ 27 ] was introduced, which principally focused on monitoring indicators such as PH, temperature, turbidity, and dissolved oxygen.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of a Li River water quality monitoring and analysis system based on outlier data analysis

Lu,

Zou,

et al. 2024

PLoS ONE

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The detection of water quality indicators such as Temperature, pH, Turbidity, Conductivity, and TDS involves five national standard methods. Chemically based measurement techniques may generate liquid residue, causing secondary pollution. The water quality monitoring and data analysis system can effectively address the issues that conventional methods require multiple pieces of equipment and repeated measurements. This paper analyzes the distribution characteristics of the historical data from five sensors at a specific time, displays them graphically in real time, and provides an early warning of exceeding the standard; It selects four water samples from different sections of the Li River, based on the national standard method, the average measurement errors of Temperature, PH, TDS, Conductivity and Turbidity are 0.98%, 2.23%, 2.92%, 3.05% and 3.98%.;It further uses the quartile method to analyze the outlier data over 100,000 records and five historical periods are selected. Experiment results show the system is relatively stable in measuring Temperature, PH and TDS, and the proportion of outlier is 0.42%, 0.84% and 1.24%. When Turbidity and Conductivity are measured, the proportion is 3.11% and 2.92%. In the experiment of using 7 methods to fill outlier, K nearest neighbor algorithm is better than others. The analysis of data trends, outliers, means, and extreme values assists in making decisions, such as updating and maintaining equipment, addressing extreme water quality situations, and enhancing regional water quality oversight.

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“…Saini and Sharma [17] provided a three-tier approach heterogeneity to enhance network lifetime using an enhanced threshold approach. Junior et al [18] provided a method to use residual energy and solar energy to increase the lifetime of the network. In [19], the method and usefulness of using MATLAB to carry out the simulations for wireless sensor networks were discussed.…”

Section: Introductionmentioning

confidence: 99%

Lifetime enhanced energy efficient wireless sensor networks using renewable energy

Tagare

Narendra

2023

IJECE

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In this paper, we consider a remote environment with randomly deployed sensor nodes, with an initial energy of E0 (J) and a solar panel. A hierarchical clustering technique is implemented. At each round, the normal nodes send the sensed data to the nearest cluster head (CH) which is chosen on the probability value. Data after aggregation at CHs is sent to the base station (BS). CH requires more energy than normal nodes. Here, we energize only CHs if their energy is less than 5% of its initial value with the use of solar energy. We evaluate parameters like energy consumption, the lifetime of the network, and data packets sent to CH and BS. The obtained results are compared with existing techniques. The proposed protocol provides better energy efficiency and network lifetime. The results show increased stability with delayed death of the first node. The network lifetime of the proposed protocol is compared to the multi-level hybrid energy efficient distributed (MLHEED) technique and low-energy adaptive clustering hierarchy (LEACH) variants. Network lifetime is enhanced by 13.35%. Energy consumption is reduced with respect to MLHEED-4, 5, and 6 by 7.15%, 12.10%, and 14.975% respectively. The no. of packets transferred to the BS is greater than the MLHEED protocol by 39.03%.

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Routing with Renewable Energy Management in Wireless Sensor Networks

Cited by 5 publications

References 38 publications

Functionality Analysis of Electric Actuators in Renewable Energy Systems—A Review

Functionality Analysis of Electric Actuators in Renewable Energy Systems—A Review

Design and implementation of a Li River water quality monitoring and analysis system based on outlier data analysis

Lifetime enhanced energy efficient wireless sensor networks using renewable energy

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