Google Android operated Smart Home -operating electrical appliances in home through Android mobile phones

The project aims in designing a system which makes operating of electrical appliances in home through Android mobile phone possible. The controlling of electrical appliances is done wirelessly through Android smart phone using the Bluetooth feature present in it. Here in this project the Android smart phone is used as a remote control for operating the electrical appliances. Android is a software stack for mobile devices that includes an operating system, middleware and key applications. Android boasts a healthy array of connectivity options, including Wi-Fi, Bluetooth, and wireless data over a cellular connection (for example, GPRS, EDGE (Enhanced Data rates for GSM Evolution), and 3G). Android provides access to a wide range of useful libraries and tools that can be used to build rich applications. In addition, Android includes a full set of tools that have been built from the ground up alongside the platform providing developers with high productivity and deep insight into their applications. Bluetooth is an open standard specification for a radio frequency (RF)-based, short-range connectivity technology that promises to change the face of computing and wireless communication. It is designed to be an inexpensive, wireless networking system for all classes of portable devices, such as laptops, PDAs (personal digital assistants), and mobile phones. It also will enable wireless connections for desktop computers, making connections between monitors, printers, keyboards, and the CPU cable-free. The controlling device of the whole system is a Microcontroller. Bluetooth module, 4-Relays board and LCD display are interfaced to the Microcontroller. The data received by the Bluetooth module from Android smart phone is fed as input to the controller. The controller acts accordingly on the Relays to switch connected electrical appliances. Also, the status of the electrical appliances can be seen on LCD display. In achieving the task the controller is loaded with a program written using Embedded ‘C’ language. The main objectives of the project are: 1. Controlling of AC devices wirelessly through mobile phone. 2. Usage of Android touchscreen smart phone in performing the task. 3. Bluetooth wireless transmission. 4. Display of electrical appliances status on graphical display. The project provides exposure to following technologies: 1. Google’s Android Open Source Technology. 2. Bluetooth wireless technology. 3. Interfacing Bluetooth module to Microcontroller. 4. Electromagnetic Relay switching principles. 5. Interfacing of 4-Relay board to Microcontroller. 6. Embedded C programming. 7. PCB designing. The major building blocks of the project are: 1. Regulated Power Supply. 2. Microcontroller. 3. Android smart phone. 4. Bluetooth module. 5. 4-Relay board with driver. 6. LCD display with driver. 7. Crystal oscillator. 8. Reset. 9. LED indicators. Software’s used: 1. PIC-C compiler for Embedded C programming. 2. PIC kit 2 programmer for dumping code into Micro controller. 3. Express SCH for Circuit design. 4. Proteus for hardware simulation.

Alarm Pattern Analysis Using Computational Intelligence Approach

In today’s high value manufacturing, machines are often equipped with sensors to detect disturbances in
the system, which may trigger the corresponding alarm(s) when limits are exceeded. Apart from displaying on a
terminal for human intervention, these alarm values are also logged to a database. Machine faults or breakdown
may be characterized by a set of alarm patterns. The ability to detect these patterns early can help to alert and
prevent impending machine failure, which is extremely useful for mission critical machines. This project involves
the development of pattern identification concepts and algorithms based on computational intelligence approaches
to predict machine failures. Some of these approaches include Ant Colony System, Genetic Algorithm, and
Statistical methods.
Students with keen interest to learn computational intelligence for pattern recognition and those with knowledge
in manufacture equipment management will have an added advantage for this project

Investigation of the Sequential Accelerator on the Perceptron for Pattern Recognition

In machine learning methods, when the input data becomes extremely large, the current direct methods
require too large learning times and memory. This project investigates one sequential method to overcome this
problem. It is quite a simple method to implement and is tested using the Perceptron as the base classifier. The
perceptron converges very slowly. So it will be interesting to find out if the proposed accelerator can improve
significantly the computational times of this simple classifier. The student will try various investigations on
different very large data sets and to measure their computational complexities. It has been shown that this
sequential method is very fast and only need a small subset of the large data set to complete the learning.

Investigation of the Sequential Accelerator on LDA for Pattern Recognition

In machine learning methods, when the input data becomes extremely large, the current direct methods
require too large learning times and memory. This project investigates one sequential method to overcome this
problem. It is quite a simple method to implement and is tested using the well-known LDA classifier. The student
will try various investigations on different very large data sets and to measure their computational complexities. It
has been shown that this sequential method is very fast and only need a small subset of the large data set to
complete the learning.

Equalization of Fading Channels using RBF Networks

Equalization of Fading Channels using RBF Networks
Summary: Equalization is the process of recovering the true input data from the received data which is corrupted
by noise and passes through a nonlinear communication channel. Earlier work by the supervisor and his group has
successfully used RBF neural networks for complicated nonlinear channels that are stationary. In this project, the
performance of the RBF equalizers will be investigated for time varying ( fading ) channels ( mainly for Raleigh
Fading Channels) and an implementation scheme for the equalizer will be evolved. Performance comparison with
other conventional equalizers will also be made.

Analysis of the quality of fingerprint image features

The most popular fingerprint feature used for matching is the feature points, called minutiae. Several approaches have been proposed which in a way, involves detecting the skeleton image to locate the minutiae. Subsequently, the geometrical and other information are extracted and used to match the minutiae. However, the performance of the minutiae extraction varies. Problem arises when there is noise or the fingerprint image is not clear. This could cause the introduction of false minutiae or the omission of valid minutiae. In this project, the main aim is to devise methods to analyse the quality of the minutiae so that the overall matching is improved. This
will involve analysing the property of the minutiae to provide suitable confidence level and providing consistent information that can be extracted from the minutiae. Good knowledge in C/C++ or Matlab programming is essential for this project.

Neural Network based Color Image Segmentation

Breast cancer is the most common cancer among women, and is the second leading cause of cancer
deaths in women today. Basically, the diagnosis procedure of breast cancer consists of two steps; (1) mammography
based breast abnormality detection; (2) biopsy based diagnosis. Biopsy is the only definitive way to determine
whether cancer is present.
In this project, biopsy color Image segmentation based on neural networks will be studied. The objective of breast
biopsy image segmentation is to segment cells and blood vessels in the image.
As the second part of the project, color image segmentation software will be developed.

Development of a Matlab-based Control System Laboratory

The aim of this project is to develop a Computer Aided Control System Design (CASCD) environment that
are typically utilised in an undergraduate controls laboratory. Due to their popularity and availability, MATLAB,
SIMULINK and the Real-Time Workshop toolbox are chosen as the prototyping environment. The following issues
should be addressed:

1. Standardisation: a consistent hardware interface to various laboratory apparatus and a consistent user
interface, for the following task: modelling, control design, data collection, parameter estimation, and real-time
experiment.

2. Control experiment via Internet: While the local real-time control could be extended for remote control via the
Internet, there will be some issues that are peculiar to Internet lab, e.g. all Internet experiments need to be selfresetting.
In addition, safety, security and user flexibilty are issues that need to be addressed 

Wavelet-based Deconvolution for System Identification

In many practical applications, we are given access to the input and ouput of a system whose
characteristics are unknown. The term ‘deconvolution’ is used to describe the operation of separating the input
function from the characteristics of the system we intend to identify. Conventional techniques for deconvolution
based on direct Fourier or Laplace transfoms suffer from the ill-conditioned nature of the problem in the presence
of noise. The aim of this project is to develop and implement a robust deconvolution technique based on wavelets
and study its performance as compared with other conventional techniques. An appreciation of Matlab and
numerical computation skills would be desirable.