A state-of-the-art survey on wireless rechargeable sensor networks: perspectives and challenges

Qureshi, Bushra; Aziz, Sammah Abdel; Wang, Xingfu; Hawbani, Ammar; Alsamhi, Saeed Hamood; Qureshi, Taiyaba; Naji, Abdulbary

doi:10.1007/s11276-022-03004-x

Cited by 9 publications

(5 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This mechanism can be called as Wireless rechargeable sensor network (WRSN). (Qureshi et al, 2022) (Chaudhri et al, 2022) 4: Challenges and Solutions:…”

Section: : Algorithms For Discriminationmentioning

confidence: 99%

“…As discussed by (Chaudhri et al, 2022) the Fig. 6 Schematic representation of currently employed charging schemes (Qureshi et al, 2022) circuitry of a gas sensor can be reduced and we can save almost 40-50 % of power consumption. By using these novel techniques a smart gas sensor can be developed.…”

Section: : Algorithms For Discriminationmentioning

confidence: 99%

“…So by using Multiphysics software's the power consumption should be calculated first and the sensor arrays should be fabricated. By using the approach of (Qureshi et al, 2022) the charging of sensor circuitry can be done properly. If it is followed then the power consumption will also get reduced and the life of the sensor circuit can be increased.…”

Section: : Algorithms For Discriminationmentioning

confidence: 99%

“…The smart gas sensor requirement is based on three main factors first is the sensing element, the sensing circuit, power consumption. These three aspects can be taken care of if we adopt the approach of (Qureshi et al, 2022) (Chaudhri et al, 2022) (Almagrabi et al2020. From these approaches the power consumption and the area of a sensor circuitry can be reduced making it portable and fixable in IOT based devices.…”

Section: : Conclusionmentioning

confidence: 99%

See 3 more Smart Citations

Review on Discrimination of Hazardous Gases by Smart Sensing Technology

Bandewad

Datta

Gawali

et al. 2023

AIA

View full text Add to dashboard Cite

Real-time detection of hazardous gases in the ambient and indoors has become the prime motive for curbing the problem of air pollution. Keeping the concentration of hazardous gases in control is the main task before human society so as to keep environmental balance. Smart sensors are attracting researchers to focus on fabricating devices that could detect and predict the presence of gas in real-time, give accurate results about the gas concentration, detection of a target gas from the mixture of gases. This smart gas sensor system can have applications in the field of military, space, underwater, indoor, outdoors, factories, vehicles, and wearable smart devices. This study reviews recent advances in smart sensor technology with respect to the material structure, sensing technique, and discrimination algorithm. Focus is given on reducing the power consumption and area of a sensor circuitry with the help of different techniques.

show abstract

“…This mechanism can be called as Wireless rechargeable sensor network (WRSN). (Qureshi et al, 2022) (Chaudhri et al, 2022) 4: Challenges and Solutions:…”

Section: : Algorithms For Discriminationmentioning

confidence: 99%

Section: : Algorithms For Discriminationmentioning

confidence: 99%

Section: : Algorithms For Discriminationmentioning

confidence: 99%

Section: : Conclusionmentioning

confidence: 99%

See 2 more Smart Citations

Review on Discrimination of Hazardous Gases by Smart Sensing Technology

Bandewad

Datta

Gawali

et al. 2023

AIA

View full text Add to dashboard Cite

show abstract

“…The most important activity of wireless rechargeable sensor network (WRSN) 1 is data gathering 2,3 . To perform this activity, the battery limited sensors spend huge energy and as a result die early.…”

Section: Introductionmentioning

confidence: 99%

Collaborative data gathering and recharging using multiple mobile vehicles in wireless rechargeable sensor network

Das

Dash

2023

Int J Communication

View full text Add to dashboard Cite

SummaryMany cutting‐edge studies on collaborative data gathering and charging (CDAC) assume that the mobile vehicle (MV) has enough energy to charge the sensors as well as collect data from them. The current studies also took into account that the sensors always receive full charge from the MV, resulting in a wireless rechargeable sensor network (WRSN) with very little dead period and very little data gathering latency. It is also believed that the energy consumption rates of the sensors are constant. However, in large‐scale WRSN, the aforementioned considerations are not always practical. In addition, the utilization of single base station (BS) in a large‐scale WRSN cannot guarantee improved network scalability, expedite charging decisions by minimizing the substantial overhead of the BS, and enhance the traveling distance for MV. In order to overcome the aforementioned problems, we present an effective on‐demand partial CDAC scheme using battery‐limited multiple MVs. The proposed scheme implements the CDAC process in such a way that the total dead periods of the sensors and the energy consumption of MVs are reduced. We use a multi‐objective‐based genetic algorithm (GA) to optimize the entire CDAC process. The simulation is carried out to demonstrate the usefulness and competitiveness of the proposed scheme. In comparison with existing works, the proposed work improves CDAC performance by reducing sensor dead time and energy consumption of MV.

show abstract