In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.
Among diverse wearable techniques, insole‐based plantar pressure monitoring systems have surged as a leading technology to monitor patient's chronic disease progression. Such technological feat has been made possible due to the strong correlation between gait and disease status. Hence, insole‐based plantar pressure monitoring techniques are growing rapidly worldwide; with several research institutions and enterprises showing an increased interest in the field. This review intends to first explain the working principles of mainstream insole plantar sensing techniques and design considerations such as sensing material selection and electronics design requirements, and then the state‐of‐the‐art algorithms for plantar pressure distribution reconstruction. Following, this article will discuss disease monitoring applications and the extraction of disease features. Finally, insight regarding common challenges and their potential solutions within the field would be elucidated.
Nodes in wireless sensor networks (WSNs) have the potential to be selfish without transmitting packets in routing. This study mainly focuses on the problem of reliable delivery mechanism in WSNs, and the authors' objective is to ensure stable cooperation among nodes for packets delivery and minimum routing cost at the same time. Based on the performance metrics in terms of the rate of packets forwarding, correctly reporting event, and energy remain, the authors present a coalitional game model with a characteristic function to be shared among coalition members. Then an efficient and fast convergence coalition formation algorithm is proposed to obtain the stable coalition partition in the game. Finally, on the basis of the coalitional game model, the authors design a reliable coalition formation routing (RCFR) protocol, which selects route according to the principle of lowest cost. Simulation experiments are conducted to analyse the performance of RCFR, compared with original ad hoc on-demand distance vector routing and the method proposed by Kazemeyni. The results show that RCFR effectively enhances packet delivery ratio, decreases routing establishing time, balances energy consumption, and reduces average signalling overhead.
In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.
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