Along with the ageing of population, the low cost and high efficiency physiological information monitor systems for the realization of long-term community guardianship are of great significance. This system can improve the life quality and reduce the medical expense. Our paper is a working model which incorporates sensors to measure parameters like body temperature, heart beat rate, blood pressure; and transfer it to the computer so that the patient’s health condition can be analyzed by doctors in any part of the hospital. Thus, it reduces the doctor’s workload and also gives accurate results. Further this system uses Zigbee technology which enables the viewing of all parameters on the computer. A micro-controller board is used for analyzing the inputs from the patient. Also all the process parameters within an interval selectable by the user can be recorded on the computer. This is very useful for future analysis and review of patient’s health condition. For more versatile medical applications, this paper can be improvised, by incorporating ECG, EMG, EEG systems, dental sensors and annunciation systems, thereby making it useful in hospitals as a very efficient and dedicated patient care system.

There is a serious flaw in existing image search engines, since they basically work under the influence of keywords. Retrieving images based on the keywords is not only inappropriate, but also time consuming. Content Based Image Retrieval (CBIR) is still a research area, which aims to retrieve images based on the content of the query image. In this paper we have proposed a CBIR based image retrieval system, which analyses innate properties of an image such as, the color, texture and the entropy factor, for efficient and meaningful image retrieval. The initial step is to retrieve images based on the color combination of the query image, which is followed by the texture based retrieval and finally, based on the entropy of the images, the results are filtered. The proposed system results in retrieving the images from the database which are similar to the query image. Entropy based image retrieval proved to be quite useful in filtering the irrelevant images thereby improving the efficiency of the system.