56.              Maximum Speed / Time recorder using micro controller  

Abstract ECG Tele Monitoring Project:
This paper presents a new revolutionary concept in the field of medical sciences, with the rapid advancement of electronics in medical applications has paved path for the invention of a virtual heath monitoring system rather than conventional manually operated ECG system, here we implemented a new system “ECG telephone monitoring system comprised of an portable ECG terminal with an health monitoring system.

This system is capable of transmitting the human body signals effectively for monitoring purpose by analyzing them perfectly. In emergency condition there is an intense need of immediate and accurate diagnosis based on the condition and the body signals from the electrocardiography (ECG). This conventional method of analyzing the health conditions of the patient takes a lot of time so with an intent to reduce the reaction time we implemented this new ECG TELEMONITORING system.

This system is also known as telemetric ECG it can perform the direct transmissions in real time with in shorter duration of time facilitates a continuous monitoring over the varying parameters. And the transmission of the signal can be either through wire or wireless. Standard telephonic wires are used to transmit the data where as in wireless transmission for monitoring and transmitting the ECG signals of the patients we implement the monitoring center server based on ZIGBEE link. By this the doctor can take the prevention steps based on the ECG signals delivered by the ECG compatible software.

The design and operation of this remote ECG monitoring is clearly explained in the coming sections. Apart from several methods of recording and analyzing these ECG signals this new concept of using mobile phone in monitoring purposes, offer many advantages in real time applications. By this we can monitor the patient condition and an accurate therapy can be provided, it is a low cost and high distance coverage, can easily interface with the peripheral devices for the efficient exchange of data.

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Introduction to Develop a Multiple Interface Based Fire Fighting Robotics Project:

A monitoring system that is based on the real time is presented in a multiple interface that is usually used in the automation of home. The home and building security system includes security modular, appliance controller module, fire fighting robot, television security device, GSM modem, remote supervise computer and appliance control module.

Industry personal computer is the main controller of the fire fighting robot. In order to control the mobile robot we order the command that acquire sensor data and programmed the supervised remote system with the visual basic. Security information can be received by the robot from the interface of the wireless RS232 and a generate user interface is designed for the computer control of the fire fighting robot.

In the results of the experiments the users will control the mobile robot with the help of the RF controller, remotely supervise computer and supervised control. Obstacle can be avoided by the robot using IR sensors as well as ultrasonic sensors as per the fusion method of the multi-sense. Two flame sensors can be used to know the source of the fire and fight it with the help of the extinguisher. We are also planning to design an obstacle detector in the future modular using the IR sensor and ultrasonic sensor along with the fusion of the algorithm.

For getting more quick and easy environment map in the outdoor and indoor we need to combine the laser finder . Usually a home provides safety of the security of factory, office building and laboratory is necessary to the life of human and we have also created a multi-sensor security based system that includes a robot for fire fighting in the intelligent building we design a fire fighting robot that comes with an extinguishers. 50cm, 80kg and 130 cm are the respective shapes.

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Introduction:-

The main objective of this paper is to design a device which can test the electronic components accurately. In this paper we will discuss the testing of electronic components and how to repair them. A multi meter like device is designed by using a 8051 micro controller. By using this we cannot know the operational parameters of the device but we know only whether the device is working or not.

Micro controller working:

We will select an AT89C52 microcontroller which comes under the family of 8051. It is an low power and high performance 8 bit cmos microcontroller. The special feature of this microcontroller is that it has 8kb of internal flash memory which is not available in most of the microcontrollers. It is a powerful and highly flexible for the design of embedded control applications. It is a 40 pin device in which 32 pins can be used for input and output purpose and it has 256 bytes of ram. It has idle mode which halts the normal execution and allows the interrupt to continue execution.

Testing process:

An IC555 timer is used to generate a pulse which is used for testing the electronic component. The pulse is fed to the input line of the micro controller. A control unit is present in the circuit so as to adjust the pulse frequencies accordingly. At the output line of the micro controller we connect the electronic components to check its working. We can see the output values in the led. By using this device we can check the working of transistors and diodes. The present available multi meters have only specific capability of checking only diodes or transistors. We cannot know the operational parameters of the components so cannot know at what point of value the component cannot work in the circuit. Thus we can conclude that this device is high performance capable and low cost when compare to that of available multi meters.


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An circuit breaker is an automatically-operated electrical switch designed to protect an electrical circuit from damage caused by overload or short circuit. Its basic function is to detect a fault condition and, by interrupting continuity, to immediately discontinue electrical flow. Unlike a fuse, which operates once and then has to be replaced, a circuit breaker can be reset (either manually or automatically) to resume normal operation. Circuit breakers are made in varying sizes, from small devices that protect an individual household appliance up to large switchgear designed to protect high voltage circuits feeding an entire city.
This project is the related with the automation of currently available circuit breakers.

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Transducers for high-power sonars, an important tool for undersea exploration and monitoring, may be required to work in deep water where pressures are higher than several tens of MPa.
In contrast with the piezoelectric devices commonly used as highpower sonars for seabed resource exploration, electroactive polymers offer the benefits of high coupling efficiency, low cost, and the ability to form large area skins or other devices. One question about the use of electroactive polymers for sonar has been their ability to withstand the rigors of the deep-sea environment. In arecent experiment, we have verified that the dielectric elastomer type of electroactive polymer can maintain good operational characteristics even in an ultrahigh-pressure environment by showing that the electroactive strain response to an applied voltage was unaffected by externally applied pressures of up to 100 MPa.
Index Terms—Dielectric elastomers, electroactive polymer artificial
muscle, transducer

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Abstract:-

Now-a-days, Automated systems have less manual operations, flexibility, reliability and accurate. Due to this demand every field prefers automated control systems. Especially in the field of electronics automated systems are giving good performance. In the present scenario of war situations, unmanned systems plays very important role to minimize human losses. So this robot is very useful to do operations like obstacle detection.

This project aims at designing and executing the obstacle detection and avoidance robot. A robot obstacle detection system including a robot housing which navigates with respect to a surface and a sensor subsystem having a defined relationship with respect to the housing and aimed at the surface for detecting the surface. The ultrasonic sensor is a pair sensors has a receiver and a transmitter sensor. The transmitter sends the ultrasonic waves, and if the receiver senses any of the transmitted signal it indicates the presence of an obstacle. If the receiver doesn’t sense any signal it indicates the absence of obstacle. If any obstacle is detected the directions of the robot will be automatically changed.

This robot is fitted with motors. A micro controller is used to control all operations. According to the motor operations the robot will operate as specified in program.

However, the microcontroller being used for the project has latched outputs and as such one does not have to keep the buttons on remote control passed for more than a few milliseconds. The working prototype of the land rover
including remote is designed using micro controllers at both ends with appropriate code written in "C" language.

The programming language used for developing the software to the microcontroller is Embedded/Assembly. The KEIL cross compiler is used to edit, compile and debug this program. Micro Flash programmer is used for burning the developed code on Keil in to the microcontroller Chip. Here in our application we are using AT89C51 microcontroller which is Flash Programmable IC.AT represents the Atmel Corporation represents CMOS technology is used for designing the IC. This IC is one of the versions of 8051.

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Abstract:-

Description of the Project:-

This paper describes the hardware design flow of lifting based 2-D Forward Discrete Wavelet Transform (FDWT) processor for JPEG 2000. In order to build high quality image of JPEG 2000 codec, an effective 2-D FDWT algorithm has been performed on input image file to get the decomposed image coefficients. The Lifting Scheme reduces the number of operations execution steps to almost one-half of those needed with a conventional convolution approach. Initially, the lifting based 2-D FDWT algorithm has been developed using Mat lab. The FDWT modules were simulated using XPS(8.1i) design tools. The final design was verified with Matlab image processing tools.

Comparison of simulation results Matlab was done to verify the proper functionality of the developed module. The motivation in designing the hardware modules of the FDWT was to reduce its complexity, enhance its performance and to make it suitable development on a reconfigurable FPGA based platform for VLSI implementation. Results of the decomposition for test image validate the design. The entire system runs at 215 MHz clock frequency and reaches a speed performance suitable for several realtime applications. The result of simulation displays that lifting scheme needs less memory requirement.

IntroductionA majority of today’s Internet bandwidth is estimated to be used for images and video. Recent multimedia applications for handheld and portable devices place a limit on the available wireless bandwidth. The bandwidth is limited even with new connection standards. JPEG image compression that is in widespread use today took several years for it to be perfected. Wavelet based techniques such as JPEG2000 for image compression has a lot more to offer than conventional methods in terms of compression ratio. Currently wavelet implementations are still under development lifecycle and are being perfected. Flexible energy-efficient hardware implementations that can handle multimedia functions such as image processing, coding and decoding are critical, especially in hand-held portable multimedia wireless devices.

Background
Data compression is, of course, a powerful, enabling technology that plays a vital role in the information age. Among the various types of data commonly transferred over networks, image and video data comprises the bulk of the bit traffic. For example, current estimates indicate that image data take up over 40% of the volume on the Internet. The explosive growth in demand for image and video data, coupled with delivery bottlenecks has kept compression technology at a premium.

Among the several compression standards available, the JPEG image compression standard is in wide spread use today. JPEG uses the Discrete Cosine Transform (DCT) as the transform, applied to 8-by-8 blocks of image data. The newer standard JPEG2000 is based on the Wavelet Transform (WT). Wavelet Transform offers multi-resolution image analysis, which appears to be well matched to the low level characteristic of human vision. The DCT is essentially unique but WT has many possible realizations. Wavelets provide us with a basis more suitable for representing images.

This is because it cans represent information at a variety of scales, with local contrast changes, as well as larger scale structures and thus is a better fit for image data.

Aim of the project
The main aim of the project is to implement and verify the image compression technique and to investigate the possibility of hardware acceleration of DWT for signal processing applications. A hardware design has to be provided to achieve high performance, in comparison to the software implementation of DWT. The goal of the project is to

. Implement this in a Hardware description language (Here VHDL).

. Perform simulation using tools such as Xilinx ISE 8.1i.

. Check the correctness and to synthesize for a Spartan 3E FPGA Kit.

The STFT represents a sort of compromise between the time- and frequency-based views of a signal. It provides some information about both when and at what frequencies a signal event occurs. However, you can only obtain this information with limited precision, and that precision is determined by the size of the window.

While the STFT compromise between time and frequency information can be useful, the drawback is that once you choose a particular size for the time window, that window is the same for all frequencies. Many signals require a more flexible approach—one where we can vary the window size to determine more accurately either time or frequency.

Problem Present in Fourier TransformThe Fundamental idea behind wavelets is to analyze according to scale. Indeed, some researchers feel that using wavelets means adopting a whole new mind-set or perspective in processing data. Wavelets are functions that satisfy certain mathematical requirements and are used in representing data or other functions. This idea is not new. Approximation using superposition of functions has existed since the early 18OOs, when Joseph Fourier discovered that he could superpose sines and cosines to represent other functions.

However, in wavelet analysis, the scale used to look at data plays a special role. Wavelet algorithms process data at different scales or resolutions. Looking at a signal (or a function) through a large “window,” gross features could be noticed. Similarly, looking at a signal through a small “window,” small features could be noticed. The result in wavelet analysis is to see both the forest and the trees, so to speak.

This makes wavelets interesting and useful. For many decades scientists have wanted more appropriate functions than the sines and cosines, which are the basis of Fourier analysis, to approximate choppy signals.’ By their definition, these functions are non-local (and stretch out to infinity). They therefore do a very poor job in approximating sharp spikes. But with wavelet analysis, we can use approximating functions that are contained neatly in finite domains. Wavelets are well-suited for approximating data with sharp discontinuities.

The wavelet analysis procedure is to adopt a wavelet prototype function, called an analyzing wavelet or mother wavelet. Temporal analysis is performed with a contracted, high-frequency version of the prototype wavelet, while frequency analysis is performed with a dilated, low-frequency version of the same wavelet. Because the original signal or function can be represented in terms of a wavelet expansion (using coefficients in a linear combination of the wavelet functions), data operations can be performed using just the corresponding wavelet coefficients.

And if wavelets best adapted to data are selected, the coefficients below a threshold is truncated, resultant data are sparsely represented. This sparse coding makes wavelets an excellent tool in the field of data compression. Other applied fields that are using wavelets include astronomy, acoustics, nuclear engineering, sub-band coding, signal and image processing, neurophysiology, music, magnetic resonance imaging, speech discrimination, optics, fractals, turbulence, earthquake prediction, radar, human vision, and pure mathematics applications such as solving partial differential equations.

Basically wavelet transform (WT) is used to analyze non-stationary signals, i.e., signals whose frequency response varies in time, as Fourier transform (FT) is not suitable for such signals. To overcome the limitation of FT, short time Fourier transform (STFT) was proposed. There is only a minor difference between STFT and FT. In STFT, the signal is divided into small segments, where these segments (portions) of the signal can be assumed to be stationary. For this purpose, a window function "w" is chosen. The width of this window in time must be equal to the segment of the signal where its still be considered stationary. By STFT, one can get time-frequency response of a signal simultaneously, which can’t be obtained by FT.

Scaling
We’ve seen the interrelation of wavelets and quadrature mirror filters. The wavelet function  is determined by the high pass filter, which also produces the details of the wavelet decomposition.

There is an additional function associated with some, but not all wavelets. This is the so-called scaling function. The scaling function is very similar to the wavelet function. It is determined by the low pass quadrature mirror that iteratively up- sampling and convolving the high pass filter produces a shape approximating the wavelet function, iteratively up-sampling and convolving the low pass filter produces a shape approximating the scaling function.We’ve already alluded to the fact that wavelet analysis produces a time-scale view of a signal and now we’re talking about scaling and shifting wavelets.

What exactly do we mean by scale in this context?
Scaling a wavelet simply means stretching (or compressing) it. To go beyond colloquial descriptions such as “stretching,” we introduce the scale factor, often denoted by the letter a.

If we’re talking about sinusoids, for example the effect of the scale factor is very easy to see:

One-Stage Decomposition
For many signals, the low-frequency content is the most important part. It is what gives the signal its identity. The high-frequency content on the other hand imparts flavor or nuance. Consider the human voice. If you remove the high-frequency components, the voice sounds different but you can still tell what’s being said. However, if you remove enough of the low-frequency components, you hear gibberish. In wavelet analysis, we often speak of approximations and details. The approximations are the high-scale, low-frequency components of the signal. The details are the low-scale, high-frequency components. The filtering process at its most basic level looks like this:

The original signal S passes through two complementary filters and emerges as two signals. Unfortunately, if we actually perform this operation on a real digital signal, we wind up with twice as much data as we started with. Suppose, for instance that the original signal S consists of 1000 samples of data. Then the resulting signals will each have 1000 samples, for a total of 2000. These signals A and D are interesting, but we get 2000 values instead of the 1000 we had. There exists a more subtle way to perform the decomposition using wavelets.

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