Human Computer Interactions has been a matter of great consideration for engineers, researchers, designers and industrial experts from decades. Every device, be it a smart phone, personal computer, ATM machines, etc. comes with a user interface for a layman to understand and to use the device. With the advancing technology, different modes of user interface are proposed. The most common of all is a touch interface. Most of the interactive devices now come with a touch interface. This paper presents an approach to provide a similar external touch interface for laptops and computers that further can modify for much smaller devices such as mobile phones.

Disasters unsettle the economic and social stability of society. Shortage of skilled rescue workforces, as well as the risks involved in search and rescue operations, are becoming foremost problems during an emergency situation. To solve these problems, we have designed and implemented an Urban Search and Rescue (USAR) robot. The robot is designed and implemented in such a way that includes the application of digital electronics, embedded programming, digital signal processing and digital sensors. This USAR robot uses the microcontroller PIC 16F690 to control its movement by using a radio frequency module and PIC 16F73 to collect the sensor’s data and transmit the data through Bluetooth module. These are low power and cost-effective chips. The PIR sensor, Co2 gas sensor, and temperature sensor will collect the data of the disaster area and transmit the data to the service station. Even though, a camera is operated for visual purpose. In this paper not only we have designed and implemented USAR robot but also we tested and analyzed the result. 

The vision system is developed to reduce the human effort and improve productivity in the Vehicle Quality Assurance (VQA) shop for inspection of a car bearing a Vehicle Identification Number (VIN), assigned to it at the assembly shop. This project work is carried out in association with M/s Renault Nissan Automotive India Pvt Ltd, Chennai.
The vision system consists of a camera fixed on a pan-tilt camera frame and an Optical Character Recognition (OCR) software. The camera frame is mounted on a belt conveyor with remote control of forward, backward and tilting motion. The image of VIN present at the car door is captured through a digital camera placed adjacent to the car. The characters in the VIN image thus obtained are extracted using MATLAB, with configurable OCR software. Template matching method is followed in the OCR process. The MATLAB code can overcome trivial issues in VIN image inspection at the quality shop. Development of a graphic user interface to the software is also described.

Nowadays, Radio Frequency Identification (RFID) technology used for automatic object tracking and identifying purpose. RFID technology used in so many applications especially in automobiles, security and health care systems. RFID reader and RFID tags are main processing units in RFID system. RFID tags give the information on what an object is, where it is and even its condition, and what is happening, share related data and respond to the reader. RFID reader module used for reading data from lots of RFID tags. In convention methods [1][2] doesn’t contain any read controller methodology and doesn’t contain any storage element for RFID tags data storing. In this paper, we propose a new approach for RFID tag data reading in FPGA. This approach is more flexible in structure and easily updates the design for any applications. This design is easily adaptable for different chips and communication mechanism. This design has reading controlling methodology and along with storing capability of RFID tags by using FIFO. Here we are using Universal Asynchronous Receiver and Transmitter protocol for communicating RFID reader to PC. For simulation, we are using ModelSim software and for synthesis, purpose using XILINX ISE 14.7.

Accurate prediction of cancer can play a crucial role in its treatment. The procedure of cancer detection is incumbent upon the doctor, which at times can be subjected to human error and therefore leading to erroneous decisions. Using machine learning techniques for the same can prove to be beneficial. Many classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN) are proven to produce good classification accuracies. The following study models data sets for breast, liver, ovarian and prostate cancer using the aforementioned algorithms and compares them. The study covers data from condition of organs, which is called standard data and from gene expression data as well. This research has shown that SVM classifier can obtain better performance for classification in comparison to the ANN classifier.

This paper aims in design and implementation of Voice over Internet Protocol (VoIP) system with a high compression rate. The system uses a Raspberry Pi B+ ARM 11 microcontroller which is faster in processing the audio signal by means of CODEC2 software. An Audio Adapter (CM-108 or 109) is interfaced with the Raspberry Pi, which acts as a bridge in providing the processed voice signal to Raspberry Pi in its required PCM format. The setup is implemented in Local Area Network (LAN) in which the data transmission occurs. During the transmission of the data, the wireshark software was used to analyze the data in the network. A detailed analysis of the comparison results of different CODECs for compression rate and the estimated frame sizes are given. From the results, it is proved that the use of CODEC2 is an efficient system for VoIP. For secure communication, the AES encryption protocol with static private key was implemented. The 3.2Kbps compression technique is suitable for VoIP system as it has high compression rate and less delay compared to the other systems.