Adaptive scheme to Control Power Aware for PDR in Wireless Sensor Networks

Nowadays Wireless sensor networks playing vital role in all area. Which is used to sense the environmental monitoring, Temperature, Soil erosin etc. Low data delivery efficiency and high energy consumption are the inherent problems in Wireless Sensor Networks. Finding accurate data is more difficult and also it will leads to more expensive to collect all sensor readings. Clustering and prediction techniques, which exploit spatial and temporal correlation among the sensor data, provide opportunities for reducing the energy consumption of continuous sensor data collection and to achieve network energy efficiency and stability. So as we propose Dynamic scheme for energy consumption and data collection in wireless sensor networks by integrating adaptively enabling/disabling prediction scheme, sleep/awake method with dynamic scheme. Our framework is clustering based. A cluster head represents all sensor nodes within the region and collects data values from them. Our framework is general enough to incorporate many advanced features and we show how sleep/awake scheduling can be applied, which takes our framework approach to designing a practical dynamic algorithm for data aggregation, it avoids the need for rampant node-to-node propagation of aggregates, but rather it uses faster and more efficient cluster-to-cluster propagation. To the best of our knowledge, this is the first work adaptively enabling/disabling prediction scheme with dynamic scheme for clustering-based continuous data collection in sensor networks. When a cluster node fails because of energy depletion we need to choose alternative cluster head for that particular region. It will help to achieve less energy consumption. Our proposed models, analysis, and framework are validated via simulation and comparison with Static Cluster method in order to achieve better energy efficiency and PDR

SYSTEMATIC REVIEW OF SAR REDUCTION TECHNIQUES FOR MINIMIZING MOBILE PHONE RADIATION

In this mobile digital world cellular handsets and tablet pc’s have become the common used devices .These devices use the Electromagnetic Frequency (EMF) Spectrum which is wide spread in our atmosphere. Electromagnetic fields of all frequencies represent one of the most common and fastest growing environmental influences, about which anxiety and speculation are spreading. All populations are now exposed to varying degrees of EMF, and the levels will continue to increase as technology advances. The World Health Organization (WHO) established the International EMF Project in 1996 to assess the scientific evidence of possible health effects of EMF in the frequency range from 0 to 300 GHz and possibly reducing the effects caused by them. Our project aims in limiting the hazardous EM radiation emitted from the mobile phones. This can be achieved by using the PIFA antenna in the Transfer electromagnetic (TEM) cell experimental setu

Automatic Threshold Selections by exploration and exploitation of optimization algorithm in Record Deduplication

A deduplication process uses similarity function to identify the two entries are duplicate or not by setting the threshold.  This threshold setting is an important issue to achieve more accuracy and it relies more on human intervention. Swarm Intelligence algorithm such as PSO and ABC have been used for automatic detection of threshold to find the duplicate records. Though the algorithms performed well there is still an insufficiency regarding the solution search equation, which is used to generate new candidate solutions based on the information of previous solutions.  The proposed work addressed two problems: first to find the optimal equation using Genetic Algorithm(GA) and next it adopts an modified  Artificial Bee Colony (ABC) to get the optimal threshold to detect the duplicate records more accurately and also it reduces human intervention. CORA dataset is considered to analyze the proposed algorithm

Experimental Studies on Intelligent, Wearable and Automated Wireless Mobile Tele-Alert System for Continuous Cardiac Surveillance

Myocardial malfunctioning harms human health and since most people are affected by arrhythmia. It is one of themajor causes for sudden death. The chance of occurrence of severe myocardial problem will be increased after thefirst heart block. Detecting the onset of malfunctioning is ever challenging. This paper proposes to find out how theonset of myocardial problem can be detected automatically in an early stage by an uninterrupted surveillance device.When the device detects any abnormal myocardial functions, then it automatically alerts the patient and the doctorthrough the GSM (global system for mobile) mobile phones and the patient will be given first order medical attentionas soon as possible. Eventually this increases greatly the chance of survival of the victim