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A fiber Bragg grating (FBG) is one of the most common and widely used fiber optic sensors. One main issue when using a FBG-based sensor is that it is simultaneously sensitive to both the strain and the temperature, and compensation for the temperature and strain effects is necessary to measure these parameters. The available compensation techniques mean that the interrogation of FBG sensor systems is complex and make sensor networks bulky by increasing the number of sensors. Several of these compensation techniques are not feasible in in situ applications. In this paper, we propose a method for discriminating between the strain and the temperature by measuring the change in the single Bragg wavelength. Our proposed technique is based on measuring the sidelobe power, which appears adjacent to the main Bragg peak due to the strength of the interference between the forward and backward propagating waves of the Bragg grating sensor. We demonstrate by experiments that the proposed methodology can discriminate between the strain and temperature effects, making the interrogation system less complex with a very reasonable hardware cost.

This study introduces a geographical multi-layered clustering protocol for ad hoc wireless sensor networks (WSNs), where the size of clusters is variable so that the closer clusters to the base station (BS) have a smaller size than farther ones. Moreover, in each cluster, using some intelligent fuzzy rules and in a decentralised way, a novel subtree strategy is determined. In this way, some parent nodes are chosen that are responsible for collecting and aggregating data from their adjacent ordinary nodes and sending them to its cluster head, directly or via other parent nodes, which substantially decreases intra-cluster communication energy costs. Furthermore, these two compatible techniques can fairly mitigate the hot spot problem resulting from multi-hop communication with the BS. The simulation results demonstrate that the proposed protocol outperforms two energy-efficient protocols named DSBCA and LEACH in terms of functional network longevity for both small-scale and large-scale sensor networks.

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