Directional mobile charging method for mine Internet of things

Hu, Qingsong; Cheng, Yunhai; Li, Binghao; Wang, Yajun; Li, Shiyin

doi:10.1049/iet-com.2018.6008

Cited by 5 publications

(8 citation statements)

References 20 publications

(24 reference statements)

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“…KMEC‐Charging adopts a cluster‐first route‐second strategy to charge the sensor nodes efficiently under the constraint of MC capacity; the cluster‐first strategy shares common features with SCTD‐Charging of choose candidate charging nodes. The simulation parameters and their default settings are listed in Table 1 [27–29]. Event distortion : Figure 10 shows the effect of the number of active nodes on the distortion under different values of distance parameter of 10, 50, 100, 500, 1000, 5000 and 10,000.…”

Section: Performance Analysismentioning

confidence: 99%

Space‐correlation‐based joint data transmission and on‐demand charging for rechargeable wireless sensor networks

Yang

et al. 2020

IET Communications

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It is of great importance to power the nodes of the rechargeable wireless sensor network to detect events continuously in the area of interest. This paper proposes a joint data transmission and on‐demand charging algorithm based on the space correlation. The new algorithm optimises the event detection, data forwarding and node charging jointly to improve the charging efficiency. First, the active nodes participating in the event detection are selected using an improved iterative node selection method to reduce the number of nodes working concurrently. Then, the greedy data transmission scheme based on grid partition is proposed to transmit the observed data to the sink node. Finally, the nodes in the networks are charged using the on‐demand charging method based on grid partition, which greatly decreases the charging frequency and energy loss of the mobile charger. The simulation results demonstrate that the proposed method has superior performance in the distance travelled by the mobile charger, the energy utilisation, the average energy consumption of the mobile charger and the node charging latency.

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Section: Performance Analysismentioning

confidence: 99%

Space‐correlation‐based joint data transmission and on‐demand charging for rechargeable wireless sensor networks

Yang

et al. 2020

IET Communications

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“…Taking Fig. 4 as an example [9],

S_{k}

represents

Nod e_{k}

. Assuming that the MC moves in the middle line of the roadway, and O is the projection of

S_{k}

on the vertical plane of the MC (the plane perpendicular to the middle line of the roadway),

(||, O S_{i}) = w / 2

, where w is the width of the roadway.…”

Section: Hybrid Charging Of Controlled MC and Opportunistic Mcmentioning

confidence: 99%

“…The default settings of the parameters are as follows [7, 9]:

G_{MC} = 8 dBi

G_{r false(i false)} = 2 dBi

η = 0.125

P_{MC} = 5 normalW

λ = 0.158

v = 0.5 normalm / normals

L_{p} = 2 dB

β = 0.2316

. Since it is the charging service provided by the opportunistic MC that lays the basis for C&O charging, we first evaluate the charging ability of opportunistic MC.…”

Section: Performance Simulationsmentioning

confidence: 99%

“…To charge the Mine IoT nodes wirelessly, a certain number of stationary chargers (SCs) need to be deployed in the coal mine roadway, which are directly connected to the underground power grid, and have a stable power supply [8, 9]. Each SC also needs to be equipped with several mobile chargers (MCs).…”

Section: Introductionmentioning

confidence: 99%

“…Considering the crowding problem of MCs in existing wireless charging methods for one‐dimensional space, a distributed cooperative wireless charging method was suggested in [8]. Furthermore, a method of directional mobile charging for the Mine IoT based on smart antenna was proposed to increase the charging efficiency [9]. These methods can further be optimised through cross‐layer optimisation [10], so that the charging time is decreased [11].…”

Section: Introductionmentioning

confidence: 99%

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