Analysis of Gas Leakage and Diffusion Model

He, Hong; Chen, Wenhaor; Liu, Mei; Xu, Xin

doi:10.2991/iccahe-16.2016.18

Cited by 1 publication

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“…The Gaussian model is divided into Gaussian plume model and Gaussian puff model. The former applies to the continuous diffusion of gases, the latter applies to the instantaneous diffusion of gases [19], [20]. There is no need to set leakage diffusion time t in the Gaussian plume model, and the calculation result is the concentration distribution of toxic and harmful gases in the steady state.…”

Section: Gas Dynamic Diffusion Modelmentioning

confidence: 99%

Energy-Efficient Boundary Detection of Continuous Objects in Internet of Things Sensing Networks

et al. 2020

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Internet of Things (IoT) has been widely used to facilitate environmental perception, where detecting the boundary regions for continuous objects with energy-efficient manner is a challenge to be explored to support domain applications. This paper proposes a novel approach for continuous objects boundary prediction and detection in IoT sensing network, which is called Cloud Model-IoT Sensing Network Collaborative (CM-IoTSNC). Specifically, when an event is potentially occurred, the atmospheric dynamic diffusion model deployed on the cloud is adopted to predict gas diffusion trend in ideal and complex environments, moreover prediction results are transmitted to the IoT devices in the real-time fashion for scheduling security plans in advance. One-hop neighbor nodes are activated by abnormal nodes to determine a more accurate boundary region. Compared our technique with two traditional methods, namely Wireless Sensor Monitoring and Activating One-hop Neighbor Nodes, experimental results show that our method has a good performance in reducing the energy consumption and prolonging the lifetime of the network. INDEX TERMS Boundary detection, continuous objects, IoT sensing networks, energy efficiency, gas dynamic diffusion model.

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Section: Gas Dynamic Diffusion Modelmentioning

confidence: 99%