scholarly journals Intelligent Communication Module for Wireless Biosensor Networks

Biosensors ◽  
10.5772/7212 ◽  
2010 ◽  
Author(s):  
R. Naik ◽  
J. Singh ◽  
H. P.

our country India consists of very high population. Almost 9 millions of population in this world can be counted as a deaf or dumb people or both. We all know that the most valuable gift from the god given to human is the capability to watch, hear, spoke & to give response as per the situation arises. We all know communication is one of the most important medium through which one may carve up his/her feelings or express the information to others. The key points in communication are ability of listening and speak the word but so many from us are unlucky because they are not gifted by this ability from the god these are deaf & dumb and people. Now a days so many researches are going on to solve difficulties of these people of our society because they had to face very hard to communicate with normal person. It is too hard for mute(deaf & dumb) people to transmit their information to the normal people. As all normal people are not fully trained to understand different sign lingo, the communication between these two types of people becomes too complex. At the time emergency or other days whenever a mute (Deaf & Dumb) people are travelling passing a message (data) becomes too hard. Due to this disability one that has hearing and speaking disability doesn’t want to stand and face the race with normal person. Since the communication for the mute people is image (Visibility), not acoustic (Audio). For these mute people Hand motion plays a very part for communication. The data transmission between mute-deaf & normal people is always a very challenging job. Deaf people make use of sign language or gestures to make understand what he/she trying to say but it is impossible to understand by hearing people. The admittance to various communication based technologies plays an essential role for these (mute) handicapped peoples. Developing a small and compressed gadget for these mute people is a difficult task. Deaf-Dumb people find a difficulty in communicating with normal people and hence they always stay apart in their societies. Basically deaf-dumb ones uses various sign language for communication, & they always face lots of difficulty while communicating with normal people because they all not able to understand sign language every time. Hence there is always a hurdle in communication between these two type of peoples. There are so many researches has done in regulate to search a simple and easy way for mute people to communicate with the normal people and articulate themselves to the rest of the real world. So many improvements have been done in sign language but all are based on American gesture (sign) Language. Our research work is purely designed to provide an aid to this deaf-mute by developing and designing a smart communication module which will help to renovate sign language to text & speech communication with other and to help them lead a life in a much better way. Our paper represents a static gesture recognition algorithm that will be designed and implemented will be used in the smart communication system to bridge the communication gap between deaf & dumb and normal people. If the algorithm is implemented completely it can be can be also used to capture and analyze emotions of the people in area where high security is desired.


Author(s):  
Zheng Xiao

Background: In order to study the interference of wired transmission mode on robot motion, a mobile robot attitude calculation and debugging system based on radio frequency (RF) technology is proposed. Methods: Microcontroller STM32 has been used as the control core for the attitude information of the robot by using MEMS gyroscope and accelerometer. The optimal attitude Angle of the robot is calculated through nRF24L01 which is the core of the wireless communication module, attitude acquisition module and wireless data communication upper computer application platform. Results: The results shows that the positioning accuracy is better than±5mm. Conclusion: The experimental results show that the proposed attitude solving and debugging system of mobile robot based on RF technology has better reliability and real-time performance. The propped model is convenient for debugging of mobile robot system and has certain engineering application value.


2021 ◽  
Vol 55 ◽  
pp. 1320-1327
Author(s):  
Maria Giuffrida ◽  
Sara Perotti ◽  
Angela Tumino ◽  
Vincenzo Villois

2020 ◽  
Vol 11 (1) ◽  
pp. 298
Author(s):  
Youchung Chung

In this paper, an inverted F type antenna (IFA) for ZigBee communication of a sensor board has been designed and optimized, and it replaces the chip antenna on an RF (Radio Frequency) module that is not performing well enough for the ZigBee communication. The sensor board detects cattle behavior and identifies the breeding (estrus) period and transmits the data to the main station by the RF (Radio Frequency) module and IFA antenna. The proposed and optimized TRx (transmitting/receiving) IFA antenna of the ZigBee communication module has a return loss of −19 dB and a gain of 1.6 dB at 2.45 GHz. The size is about 2.5 × 0.5 cm in width and vertical length, and the height is 0.55 cm. The strength of signals with the chip antenna and the IFA antenna have been measured and compared. There is about a 20 dB enhancement with the IFA antenna compared to the chip antenna. The antenna is designed and applied to the RF transmission and reception (TRx) module. This antenna and sensor module can be applied to livestock in general as well as cattle.


1998 ◽  
Vol 4 (1) ◽  
pp. 73-95 ◽  
Author(s):  
KATHLEEN F. MCCOY ◽  
CHRISTOPHER A. PENNINGTON ◽  
ARLENE LUBEROFF BADMAN

Augmentative and Alternative Communication (AAC) is the field of study concerned with providing devices and techniques to augment the communicative ability of a person whose disability makes it difficult to speak or otherwise communicate in an understandable fashion. For several years, we have been applying natural language processing techniques to the field of AAC to develop intelligent communication aids that attempt to provide linguistically correct output while increasing communication rate. Previous effort has resulted in a research prototype called Compansion that expands telegraphic input. In this paper we describe that research prototype and introduce the Intelligent Parser Generator (IPG). IPG is intended to be a practical embodiment of the research prototype aimed at a group of users who have cognitive impairments that affect their linguistic ability. We describe both the theoretical underpinnings of Compansion and the practical considerations in developing a usable system for this population of users.


2006 ◽  
Vol 18 (06) ◽  
pp. 276-283 ◽  
Author(s):  
ROBERT LIN ◽  
REN-GUEY LEE ◽  
CHWAN-LU TSENG ◽  
YAN-FA WU ◽  
JOE-AIR JIANG

A multi-channel wireless EEG (electroencephalogram) acquisition and recording system is developed in this work. The system includes an EEG sensing and transmission unit and a digital processing circuit. The former is composed of pre-amplifiers, filters, and gain amplifiers. The kernel of the later digital processing circuit is a micro-controller unit (MCU, TI-MSP430), which is utilized to convert the EEG signals into digital signals and fulfill the digital filtering. By means of Bluetooth communication module, the digitized signals are sent to the back-end such as PC or PDA. Thus, the patient's EEG signal can be observed and stored without any long cables such that the analogue distortion caused by long distance transmission can be reduced significantly. Furthermore, an integrated classification method, consisting of non-linear energy operator (NLEO), autoregressive (AR) model, and bisecting k-means algorithm, is also proposed to perform EEG off-line clustering at the back-end. First, the NLEO algorithm is utilized to divide the EEG signals into many small signal segments according to the features of the amplitude and frequency of EEG signals. The AR model is then applied to extract two characteristic values, i.e., frequency and amplitude (peak to peak value), of each segment and to form characteristic matrix for each segment of EEG signal. Finally, the improved modified k-means algorithm is utilized to assort similar EEG segments into better data classification, which allows accessing the long-term EEG signals more quickly.


2008 ◽  
Vol 144 (1) ◽  
pp. 38-47 ◽  
Author(s):  
Michael L. Johnson ◽  
Jiehui Wan ◽  
Shichu Huang ◽  
Zhongyang Cheng ◽  
Valery A. Petrenko ◽  
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