Deep Learning incorporates numerous hidden layers and more rooted combinations that average Artificial Neural Networks (ANN), to produce more refined and better performing autonomy in learning algorithms. An incredible volume of literature details and improves upon Deep Learning related methods and their improvement through the years as well as their suitability in uses. Nevertheless, the primary focus of the literature review is not the enlistment of these techniques hence a concise overview will be provided over the mechanisms before delving into the intended applications

The classification of semantic segmentation-based unmanned aerial vehicle (UAV) application based on the datasets used in this work and the necessary data preprocessing steps for the optimization and implementation of the models are also involved. The optimization of the various models was done using the evaluation metrics and loss functions because deep neural networks (DNNs) are just about writing a cost function and its subsequent optimization. convolutional neural network (CNN) is a common type of artificial neural network (ANN) that has found application in numerous tasks, such as image and video recognition, image classification, recommender systems, financial time series, medical image analysis, and natural language processing. CNN is developed to automatically and adaptively learn spatial feature hierarchies via backpropagation using numerous building blocks, such as pooling, convolution, and fully connected layers. The result of identification was excellent. The image segmentation was detected and comprehend the actual components of an image down to the pixel level. The result created an entire image segmentation masks with instances using the new label editor in the label box.

In many countries fossil fuels are used as the main source to generate electricity, but due to the increase in energy consumption and the rapid depletion of the fossil fuel resources, the demand of alternate energy sources such as solar, wind or hydro power becomes high [1]. In this paper wind energy as an alternate energy resource for electric power generation is proposed in the form of a small wind farm for grid-connected application in Perlis Malaysia. The monthly wind speed data of Perlis which is the smallest state of Malaysia were measured and the wind mill parameters such as Air Density, Blade Length, Power Coefficient and Blade Length were calculated. The mechanical output power of the proposed wind turbine form is calculated to check out its performance and reliability. The results showed that the proposed wind energy power generating system is a good choice and can be implemented in Malaysia to provide enough power for small towns and rural areas.

Smart home uses a combination of the renewable energy power resources, the use of power generation from solar cells based on titanium dioxide (TiO2) which acts as the only type which produces an efficient solar cell power to obtain the electricity to recharge the standby storage device from the sunlight. The thin film of Titanium dioxide is synthesized by the sol-gel spin coating techniques at 2000 rpm on the glass. The films have a constant thickness of ~240nm. The annealing process consists of 150°C, 250°C and 350°C. The study of the absorbance and the wavelength values are important. At this condition, for the solar cell, the wavelength is around ~280nm to ~330nm. As the temperature of annealing increases the higher absorbance would be produced. The refractive index of TiO2 film is estimated at different annealing temperatures and it increases with the increasing of the annealing temperature. The application is suitable to smart home design. The dynamic output voltage obtained from the solar cells is interfaced with other circuitry such as inverters and interface charging circuit in order to inject the generated power into the standby storage device. The calculated result of this application is efficient to reduce the electrical bill by almost 30% of its original value.

This paper describes the TiO2 performance based energy gap related to its annealing process. TiO2 is one of the comprehensive band gap semiconductor materials which has been under extensive investigation in recently. This is due to its application in various fields such as photo electrolysis, photo catalysis, dye sensitized solar cells, gas sensor, optical fibers etc. Furthermore, advent of nanotechnology increases its applications many fold and different types of TiO2 have been used for different types of sensing applications. The TiO2 exists in different crystalline forms such as anatase, rutile and brookite. Solar cells consists of mono-crystalline, thin films, dye sensitized solar cells and multi-junction. TiO2 can be produced by using techniques like sputtering, vacuum evaporation, pulse laser deposition, molecular beam epitaxial, sol-gel and chemical bath deposition. Successful annealing process leads to a high performance solar cells. To fabricate the solar cells, there are four types of ways which are doctor blading, spin coat, sol-gel and screen printing. A comparison of annealing process, nanoscale structure and performance output powers been done successfully. The produced TiO2 also been tested with a high power performance.