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Ph. D RESEARCH PROPOSAL BY EWUNONU, TOOCHI CHIMA. B. Eng. (Nigeria, 2007), M. Eng. (FUTO, 2014) PROGRAMME: Ph. D DEPARTMENT: Electronics and Computer Engineering, Nnamdi Azikiwe University, Awka. RESEARCH AREA: Energy Optimisation in Fibre Optics Network. PROPOSED TOPIC: Neural Network for Predictive Energy Efficient - Future Optical Network. RESEARCH BACKGROUND The continuous advancement in semiconductor technology and microelectronics has enabled and sustained the miniaturization of equipments and their deployment in energy and cost efficient optical nodes. At the hub of this, lies the Optical Networks, which have sustained its promise as an evolving technology with various potentials to revolutionise our everyday life. It continues also to derive applications in so many areas of which many are yet to be envisioned. A “fibre optic node” is basically an inexpensive incorporation of a broadband optical receiver, which converts the downstream optically modulated signal coming from the hub to an electrical signal,( systematically combined and mostly remotely applied) with the aim of relaying signals (information), that can be further processed for specific purposes. “Neural networks” stemming its analogy from the biological neuron, is an artificial intelligence technology comprising primarily of mathematical compositions of simple functions that can together be trained to respond correctly to stimuli. It is fast gaining applications as a standalone technology or incorporation because of some of its desirable attributes which include: Pattern Classification, Learning Information and Generalization Processing, Optimisation and Control. Ability, Function Adaptation, Approximation, Clustering/Classification, Prediction/Forecasting, The similarities and perhaps dissimilarities between Optical Networks and Neural Networks have continued to inspire researchers to seek ways to exploit the attributes of these great technologies into combined and formidable systems that can derive diverse applications. RESEARCH AND TECHNICAL OBJECTIVES To develop a Neural Network for Predictive Energy Efficient for future Optical Network. To model a system that can improve energy efficiency of an optical neural network. To investigate the effect of the modelled system on the improvement of the energy efficiency. To measure, analyse and control physical variables and quantities in an improved energy efficient manner of an applicable area of relevance. To adapt and predict the outcomes of physical variables and quantities in an improved energy efficient manner of an applicable area of relevance. METHODOLOGY/DATA REQUIRED Intermittent and periodical measurements of physical variables and quantities like temperature, light, humidity, air flow from a relevant applicable area of interest. Design analysis of the Optical Network and Neural Network and its implementation in a target area of interest. The use of MATLAB or any other relevant computing, simulating, analytical and programming software or tool to model, train, simulate, compute and analyse the network using relevant data. The handy application of artificial intelligence of Neural Networks. The modelling, analysis of measurements and readings obtained should involve one or two aspects of pattern classification, learning and generalization, adaptation, clustering/classification, information processing, function approximation, prediction/forecasting and optimisation. EXPECTED OUTCOMES Through the investigations, considerations, evaluations and analyses of the data and results of the research, it is definitely expected that the research will produce an implementable, improved and effective model that will optimise and improve the energy efficiency of optical Networks. RELEVANCE OF RESEARCH The relevance of Optical networks is not yet exhausted in many aspects of human activities and by extension, has become a viable area for research, implementation and development. It is also a willing tool to the clamour for automation in many activities and sectors of national existence. This research promises to be a strong voice in this evolving area of optical networks and offers amongst other things: To emphasise on the many benefits of optical fibre networks in different aspects of our lives like medicine, security, remote and weather sensing, traffic control, fire detectors, etc and perhaps to suggest its application in our local environment. To proffer a solution to the priority challenge of Wireless sensor network (WSN). This is energy efficient as regards power consumption and efficient routing of data.