Wireless Monitoring and tracking employ pervasive computing systems, with smart sensors embedded in physical environment. So a low power, low cost, reliable radio technology is desired.
This paper embarks on the implementation of a secure premise as a PAN, a ‘BLUEHOME’, deploying ‘BLUETOOTH’ as an efficient, effective electromagnetic interface. Supporting an ad-hoc network, we can track the no of visitors entering, manipulate the environmental data collected, monitor health of a structure specifically upon a drastic change in the acoustic level, all actuating the sensors which extend the control from the physical world into the cyber space. The sensors, placed at different locations, are capable of transmitting the events recorded to a central controller via ‘Bluetooth’, for computation and the resulting action.
Hence, support can be provided for how BLUETOOTH provide a latent adaptive topology, exhibit a good response time, throughput and be easier to implement this monitoring system.
Embedded Based ARM
This paper, based on ARM7 processor and real-time embedded operating system (μC/OS-II), establishes an embedded telemedicine platform ground on LPC2104 and realizes some very popular embedded application technologies such as USB communication, embedded Internet communication, infrared communication, etc.
Meanwhile the volume of the hardware is smaller; power consumption is lower; the functions are mightier and the expansibility is stronger. In addition, for the embedded real-time μC/OS-II in use has gone through the reliability authentication, the whole running system is more stable and the program maintenance and update is more convenient.
The telemedicine system based on this technology has been tested to be stable and efficient, and has obtained the results as expected.
VOICE CONTROLLED ROBOTS
This paper describes the voice activated robot control system developed using the 32-bit MCU-DSP chip based on the TriCore. The system is in real time providing isolated speech recognition and PWM based control of a simple robot. This paper aims to study the features in the TriCore that make it suited for such application in comparison with conventional Digital Signal Processors. The system also explores the use of speech as an interface between human users and embedded devices in the area of consumer electronics.
The microcontroller chips suited for controlling applications in embedded systems were not suited architecturally for computing intensive DSP processing, which is at the heart of speech recognition and speech processing. Thus extra digital signal processors needed to be used in tandem increasing cost of the system as a whole and reducing performance.
The TriCore Architecture developed solves this problem by integrating both microcontroller and DSP capabilities optimized for real-time embedded systems unifying the best of three worlds- real time capabilities
Principal Component Analysis and Neural Network Based Face Recognition
One of the incidents that shook the whole world recently was assassination of Benazir Bhutto. This was not the first assassination; a lot of assassination has taken place. But this is special case because they were unable to trace the culprit in this 21st century. So this has led to the need of tracing the culprit. Necessity is the mother of all discoveries. So as per the necessity scientists have come up with a face detection technique. But this has one disadvantage. That is there is no data base or memory for it. To eliminate that disadvantage we can combine neural networks along with face detection technique.
To cope up 21St smart criminal I have introduced a new automatic face detection technique. My approach to the face recognition problem is to combine the Principal Component Analysis and the Neural Networks. Here the faces of the culprits are traced from the photo or from a running camera shoot by eliminating the back ground. Then using transformation the face is described by a set of eigenfaces. The transformation works are performed by the Principal Component Analyzer. Neural networks here act as a recognizer or say as a memory bank. Here each face is efficiently represented by its projection onto the space expanded by the eigenfaces are stored as a descriptor in memory. With the help of these descriptor the neural network traces each and every faces captured by the camera and finds the match in it. By doing so we can trace the culprit from a large crowd.
Embedded Navigation System For The Visually Impaired Using Dijikstra Algorithm
For a visually impaired person, the outdoor navigation is usually difficult and dangerous. The visual impaired, usually, rely on a cane or a guide dog for his navigation. This holds well only if the destination chosen by the person is already known to him. If he has chosen a destination which is unknown to him, then it proves to be a very difficult task.
Hence a need of a navigation system which is user friendly to the blind is very important.
In this paper, we have developed an effective navigation system using the Dijikstra algorithm to guide the visually impaired from their starting point to the destination. Since it uses Dijikstra algorithm, it also indicates the shortest path from the starting point to the destination, thus consuming time and energy. This system comprises an appropriate modeling of the navigational environment, fast routing algorithms generating lists of maneuvers, suitable positioning tools based on sensor fusion and Kalman filtering, reliable map matching algorithms for route checking, and, finally, efficient guidance instructions communicated via a text to speech software. The positioning of the user is taken care of by the GPS. Thus, this paper when utilized in an effective manner can be very helpful to the blind and helps them to overcome the darkness and make them to lead a bright life like us.
In 1965, engineer Gordon Moore predicted that the number of transistors on an integrated circuit -- a precursor to the microprocessor -- would double approximately every two years. Today, we call this prediction Moore's Law, though it's not really a scientific law at all. Moore's Law is more of a self-fulfilling prophecy about the computer industry. Microprocessor manufacturers strive to meet the prediction, because if they don't, their competitors will [source: Intel].
To fit more transistors on a chip, engineers have to design smaller transistors. The first chip had about 2,200 transistors on it. Today, hundreds of millions of transistors can fit on a single microprocessor chip. Even so, companies are determined to create increasingly tiny transistors, cramming more into smaller chips. There are already computer chips that have nanoscale transistors (the nanoscale is between 1 and 100 nanometers -- a nanometer is one billionth of a meter). Future transistors will have to be even smaller.
Enter the nanowire, a structure that has an amazing length-to-width ratio. Nanowires can be incredibly thin -- it's possible to create a nanowire with the diameter of just one nanometer, though engineers and scientists tend to work with nanowires that are between 30 and 60 nanometers wide. Scientists hope that we will soon be able to use nanowires to create the smallest transistors yet, though there are some pretty tough obstacles in the way.
In this article, we'll look at the properties of nanowires. We'll learn how engineers build nanowires and the progress they've made toward creating electronic chips using nanowire transistors. In the last section, we'll look at some of the potential applications for nanowires, including some medical use
Neural networks have seen an explosion of interest over the last few years, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology and physics. Indeed, anywhere that there are problems of prediction, classification or control, neural networks are being introduced.
A type of artificial intelligence that attempts to initiate the way a human brain works. Rather than using a digital model, in which all computations manipulate zeros and ones, a neural network works by creating connections between processing elements, the computer equivalent of neurons. The organizations and weights of the connections determine the output. Neural networks are particularly effective for predicting events when the networks have a large dB of prior examples to draw on, strictly speaking, a neural network implies a non-digital computer, but neural networks can be simulated on digital computer.
The field of neural networks was pioneered by Bernard Widrow of Stanford University in the 1950s.Neural network are currently used prominently in voice recognition systems Image recognition systems, industrial robotics, medical imaging, and data mining and aerospace applications. The other areas of applications of neural networks are
Neural networks in practice
Neural networks in medicine
Modeling and Diagnosing the Cardiovascular System
Electronic noses - detection and reconstruction of odors by ANNs
Instant Physician - a commercial neural net diagnostic program
Neural networks in business
Over 1.5 billion people around the world use a cellular phone; however, chances are most of these users are unaware of the damage they may be doing to their bodies. At the present time, the greatest polluting element in the earth's environment more serious even than global climate change and chemical pollution is the proliferation of electromagnetic fields. Increased exposition of RF electromagnetic field (EMF) produced by the appliances used in the telecommunications, industry and medicine may lead to biological effects in more individuals. Radio frequency (RF) and microwave radiation are considered as a type of non-ionizing electromagnetic radiations present in the environment and are perceived as health risk. According to our research project focused on studying the effect of radiation on human and animal cells, we found that the radio waves emitted from a cellular phone may harm body cells and damage DNA.
The impact of microwave (MW)/radio frequency radiation (RFR) on important biological parameters is probably more than a simply thermal one. Exposure to radio frequency (RF) signals generated by the use of cellular telephones have increased dramatically and reported to affect physiological, neurological, cognitive and behavioral changes and to induce, initiate and promote carcinogenesis.
This notable microwave radiation which is from mobile phones can be reduced by using suitable microwave absorbers. The problem with this solution is that absorbers reduce the signal power of the mobile from the base station. Absorbers also create a problem of resonance inside circuit boards of the mobile, hence leading to short circuits and improper functioning of the mobile. The problem with radiation is like the case of the ozonolysis which was identified only after the depletion of the ozone. This should not happen in the case of microwave radiation; hence we are into the research of a proper solution which will be helpful for the technology, communication, environment and human health. Thus we try save the future generation with good ecology and technology.
Development of Microprocessor Based Innovative Real Time Traffic Flow Control
This paper is about the real time innovative traffic flow control. It uses micro processor 8085-a basic yet simple of its type. This method employs a sensible algorithm that possesses the capability to automatically divide the time slot for every lane on each direction. Ambiguous situation of all kinds can be handled to the maximum by the processor eliminating the necessity for manual assistance.
In this system the main consideration that we take into account for effective control is the volume of traffic on the road. Traffic volume is determined by sensors placed at equal intervals on the road. These sensors are meant to interrupt the microprocessor and signal green to the traffic on the priority which lane is jammed heavily. The sensors interrupt the processor through the programmable interrupt controller (PIC-I.C.8259) and the processor decides the priority as per our requirement and signals the output through programmable peripheral interface (PPI-I.C.8255).
This system can operate so efficiently that the traffic is cleared at the least time and the fuel wastage is minimised and the time wasted in traffic is minimised, in contrast with the existing system.