In the Past a Few Years, smart devices like smart phones and tablets have radically change in many aspect, started from Entertainment to Shopping services to transfer Money and Banking, the next is Health Services.
With the development in information technology And the big development in cloud computing Here smart phones have entered heavily in all aspects of health care.
Now with the revolution of the smart devices (smart phones or tablets) and it's applications, there is many applications and tools are available started from attachments that allow to diagnose an infections and Now remotely and continuously monitor each heartbeat , blood pressure readings, the rate and depth of breathing, body temperature, oxygen concentration in the blood, glucose, brain waves, activity, mood, so the end result will be can reduce using of doctor ,also reduce the cost , and give us speed up and give power to patients , so make it possible for Patient to use portable devices (smart phones or tablet) to access their medical information, and achieve the goal to put information technology to work in health care and make the integration of health information technology into primary care .So the using information technology give us the good solution that won’t replace physicians.
Health Information technology give the providers of health care to give better manage patient care. By making the health information are available electronically anytime and anywhere is needed, Health Information technology can help us to improve the quality Of Health , so can decrease the cost.
Now, after all these advantages should shed light on the side of personal privacy And Hacking side that must have been tested all application and tools, All of these tools must be accurate and needs to be tested. So that must provide the highest level of security and privacy for the patients. After that. The application does not arrive the goal with 100% percent, according to the limitation that mentioned later.

Image processing is used in every sphere of life such as agriculture, remote sensing, wireless, medical etc. Bi-omedical imaging plays a vital role in the detection of diseases. Without image processing, it is not possible to detect diseases such as cancer, tumors etc. Medical equipment such as ultrasound, MRI, CT scan machine is totally dependent on image processing algorithms. Radiologists utilize these image processing algorithms to detect diseases and abnormalities. Matlab is a proprietary tool which is used by image architects in order to design these algorithms. Image processing algorithms designed using Matlab provides efficiency, accuracy, flexibility and timing constraints. The present paper addresses various image processing algorithms designed using Matlab. The performance of these algorithms is also analyzed visually as well as statistically in order to check the quality of images.

Existing smart rest room automated faucet systems operate on traditional control theory, with absolute control value, irrespective of its degree of accuracy. For example, a hands-free hand wash basin may be programmed to release water when an object is about 2cm close to the infrared sensor. This absolute control value has pitfalls such as, ascertaining the quantity of water required for each operation, without activating the water flow switch to release water at maximum rate, leading to wastage of water resources. In order to develop an efficient and accurate smart rest room automated faucet system that will release water at an approximate quantity as required for varying condition, this research paper delves into employing a data-centric model for understanding and designing a smart rest room automated faucet system, that is more accurate in operation and properly utilizes water resources. To achieve this goal, we first designed a fuzzy model using MATLAB, for the proposed smart rest room automated faucet system, and then implemented the model on embedded atmel328 microcontroller, interfaced with an infrared obstacle sensor and an electronic flow control switch to automate rest room faucet activities. In order to understand and improve its operation, data logged from the system infrared sensor for 3cm distance, was mined for proper understanding of the system operational accuracy. During which the result indicated proper water utilization at various rate of water dispensation, as a function the nearness of the object to the sensor. This supports the improvement promised by the proposed system, when adopted in existing smart rest room automated faucet systems design and re-design.

The monitoring of road conditions and surface anomalies such as potholes, bumps etc., has shown a great importance in the safety and comfort of road users from pedestrian to drivers. Detection and identification of such road anomalies not only reduces the causes of road accidents but also avoid vehicle damages. This can provision the management authorities to keep a track of road conditions along with maintenance of roads. Monitoring the road conditions is a challenging task and potholes detection plays an important role in the repairing of asphalt road surface. Many approaches exist to collect data about road surface conditions, however most of these approaches are low-speed human visual inspection or approaches that uses advanced and costly measuring equipments. Therefore, there is a need to develop a cost effective system that can manages these kind of issues. In this paper, a Participatory Sensing system based on raspberry pi is designed and developed to detect and record road surface anomalies that are measured by the inertial measurement unit (IMU) and GPS sensor. An android application is also designed and developed to alert the user from an upcoming high-intensity rough area on the road. Message Queuing Telemetry Transport (MQTT) protocol is used to publish and subscribe data from raspberry pi to data servers.

Physiological signal processing techniques are commonly used in emotion recognition. Heart rate variability (HRV) is an important tool in disease diagnosis and psychological investigations. Because of the chaotic nature of HRV, customary methods may not be proficient. Taking the advantage of geometrically based algorithms can lead to the uncomplicated and better representation of heart rate dynamics. The aim of this study was to test whether a simple HRV measure, based on triangle phase space mapping and polynomial fitting, provides a useful emotion recognition technique. HRV of women (n = 12) aged 19-25 years were compared to that of 12 matched aged men, while subjects were induced by four emotional stimuli: happy, sad, afraid, and relax. Kruskal-Wallis test was applied to show the level of significance of the features. The results confirm that emotional responses to sad, afraid and relax stimuli can be differentiated by the proposed indices. In addition, they are significantly different in both genders' physiological reactions. It seems that the suggested simple quantifiers are most promising in offering new insight into the dynamics assessments of HRV signals in different emotional states.

Vehicular adhoc networks (VANETs) are relegated as a subgroup of Mobile adhoc networks (MANETs), with the incorporation of its principles. In VANET the moving nodes are vehicles which are self-administrated, not bounded and are free to move and organize themselves in the network. VANET possess the potential of improving safety on roads by broadcasting information associated with the road conditions. This results in generation of the redundant information been disseminated by vehicles. Thus bandwidth issue becomes a major concern. In this paper, Location based data aggregation technique is been proposed for aggregating congestion related data from the road areas through which vehicles travelled. It also takes into account scheduling mechanism at the road side units (RSUs) for treating individual vehicles arriving in its range on the basis of first-cum-first order. The basic idea behind this work is to effectually disseminate the aggregation information related to congestion to RSUs as well as to the vehicles in the network. The Simulation results show that the proposed technique performs well with the network load evaluation parameters.