In-Motes Bins:a real time application for environmental monitoring in wireless sensor networks

In-Motes Bins is an agent based real time In-Motes application developed for sensing light and temperature variations in an environment. In-Motes is a mobile agent middleware that facilitates the rapid deployment of adaptive applications in Wireless Sensor Networks (WSN's). In-Motes Bins is based on the injection of mobile agents into the WSN that can migrate or clone following specific rules and performing application specific tasks. Using In-Motes we were able to create and rapidly deploy our application on a WSN consisting of 10 MICA2 motes. Our application was tested in a wine store for a period of four months. In this paper we present the In-Motes Bins application and provide a detailed evaluation of its implementation. © 2007 IEEE.

Grating Deices in polymer optical fibre

This thesis presents the fabrication of fibre Bragg gratings (FBGs) and long period gratings (LPGs) in polymer optical fibre (POF). Possible fabrication techniques were discussed to fabricate FBGs in polymer optical fibre including a detailed description of the phase mask inscription technique used to fabricate FBGs in both single and multi mode microstructured polymer optical fibre (mPOF). Complementing the fabrication of polymer optical fibre Bragg gratings (POFBGs), a technique has been developed to permanently splice POF to silica optical fibre with the use of an optical adhesive. This allowed for the fabricated POFBGs to be characterised away from the optical table, allowing for application specific characterisation. Furthermore Bragg gratings have been fabricated in polymer POF with a Bragg response within the 800nm spectral region. Within this spectral region, POF predominantly manufactured from PMMA experiences considerably smaller attenuation losses when compared to the attenuation losses within the 1550nm spectral region. The effect of thermally annealing fabricated POFBGs has been studied. This included demonstrating the ability to tune the Bragg wavelength of a POFBG sensor to a desired wavelength. Thermal annealing has also been used to manufacture wavelength division multiplexed sensors with the use of a single phase mask. Finally POFBGs have been fabricated in Topas Cyclic Olefin Copolymer. Fabrication of Bragg gratings within this copolymer allowed for the first demonstration of near immunity to relative humidity whilst monitoring changes in temperature of the environment the POFBG sensor was in. Bragg gratings fabricated in the Topas copolymer demonstrated sensitivity to relative humidity which was 65 times less than that of a PMMA based POFBG sensor. This decrease in sensitivity has the potential to significantly reduce the potential of cross sensitivity to relative humidity whilst being employed to monitor measurands such as temperature and axial strain.

Making motes intelligent:an agent-based approach to wireless sensor networks

In-Motes is a mobile agent middleware that generates an intelligent framework for deploying applications in Wireless Sensor Networks (WSNs). In-Motes is based on the injection of mobile agents into the network that can migrate or clone following specific rules and performing application specific tasks. By doing so, each mote is given a certain degree of perception, cognition and control, forming the basis for its intelligence. Our middleware incorporates technologies such as Linda-like tuplespaces and federated system architecture in order to obtain a high degree of collaboration and coordination for the agent society. A set of behavioral rules inspired by a community of bacterial strains is also generated as the means for robustness of the WSN. In this paper, we present In-Motes and provide a detailed evaluation of its implementation for MICA2 motes.

The multiple pheromone ant clustering algorithm and its application to real world domains

The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each descriptive attribute of the object rather than a single pheromone representing the whole object. Ants that encounter other ants frequently enough can combine the attribute values they are detecting, which enables the MPACA to learn influential variable interactions. This paper applies the model to real-world data from two domains. One is logistics, focusing on resource allocation rather than the more traditional vehicle-routing problem. The other is mental-health risk assessment. The task for the MPACA in each domain was to predict class membership where the classes for the logistics domain were the levels of demand on haulage company resources and the mental-health classes were levels of suicide risk. Results on these noisy real-world data were promising, demonstrating the ability of the MPACA to find patterns in the data with accuracy comparable to more traditional linear regression models. © 2013 Polish Information Processing Society.

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.