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Internet of things (IoT) remains one of the most electrifying and fast burgeoning fields. It permits most of the things like any objects are controlled with very less manpower and we can control things anywhere and anytime by using network. In this paper that going to be constructing that the “Detection of Blockage in Manhole Using IoT”. Detecting a struck in the manhole pipe, due to blockage of sludge in a pipe. Here by using detecting the length of the pipe using ultrasonic sensor till where the sludge struck with the help of capturing image of sludge to aware of, due to gloominess inside a manhole by provide a luminescence, which helps to capture picture of particular sludge. And with the help of developing an application to control the device, by using that application data access can be done (captured picture) using a cloud. In traditional method, sewers have to do cleaning in all the cities (areas). In gutters, workers stand in the waste, which reaches chest level and with the help of long wooden sticks and broomsticks they clear blockage. In some areas workers crawl into a sewage, without wearing any protective gear. And those workers are treated very badly by the society. Thus, sewers need to work a lot to clear blockage. But now by using this technique it will be very much easier to reduce a man power and also incremental steps can be added further.

Image processing for medical field has contributed a max beyond limits and many fuzzy solutions have also been proposed. In current scenario of technological addiction cataract based problems are encountered due to prolong exposure towards sharp light emitting devices. 55% of vision impairment is reported from cataract under urban region. In this paper, a cataract density ration is analyzed under color image processing for acquiring affected and unaffected region. The paper has reached the accuracy rate of 87.3% under medical samples.

Wireless spread spectrum is a standout amongst the most valuable assets. With the fast development of the quantity of remote gadgets, interchanges over the unlicensed range groups get to be extremely swarmed. Data dissemination in the wireless environment is usually characterized as the spreading of data to numerous goals through communicating. The principle target is to achieve the most extreme number of neighbors with each sent parcel. The main objective of the paper is to find the best routing and resource allocation strategies in order to minimize the average end-to-end delay of multiple data connections in the cognitive radio based wireless mesh network. Wireless mesh nodes utilize the cognitive radio to share the spectrum with primary users. Depending on the primary user's activities, the spectrum resources available to the cognitive mesh nodes are varying in both space and time. In this joint design scheme can accommodate the traffic load, or achieve half the delay compared to the disjoint methods.

Energy saving is one of the major concerns in the present era. The project highlights the necessity of Power Audit in the residential feeders and the need of local MicroGrid design. The present study deals with Power Audit Analysis of 132 residential houses and 10 commercial buildings, connected to the 250 Kva distribution transformer feeders. The Detailed Power Audit is carried out for 10 houses connected to the feeder and preliminary audit is carried out for 122 houses. Recommendations are proposed further with Micro Grid for reducing the dependency of at least 20% loads of houses on Main Grid and for encouraging people to generate their own power. The suggested implementation tested with ETAP simulation and concluded with the improvement of energy efficiency of Residential houses and thereby reducing the energy wastage.

A Wireless sensor network is a collection of Wireless nodes with limited energy capabilities that may be mobile or stationary and are located randomly on a dynamically changing environment. How to effectively control the power of the sensor nodes and extend the life time of the whole network become a very important issue. This project presents the clustering approach which includes the Wireless sensor network. In the clustering approaches share the loads with cluster head nodes. To extend the cluster head's life and extend the life time of network based on the distance between the cluster head and base station. Energy usage is minimized by exploiting density estimation, sleeping modes and duty cycle control and distance between the cluster head and nodes. In this work, we proposed clustering mechanism. Nodes associate with the nearby CH. Nodes are classified in to critical nodes and non-critical nodes. Critical nodes are continuously transmission between the CH and nodes. so energy usage of critical node is high at the same time non-critical node based on the open loop system. It is not continiously transmit, so minimized energy usage of non-critical nodes. The proposed mechanism will effectively reduce the frequency of the transmission of the sensor nodes more close to sink and achieve the effectiveness of saving power and extending the lifetime of network.

In this paper, we present a Modified Revised Wilson Current Mirror Level Shifter (MRWCMLS) to convert subthreshold voltage to supply voltage with low leakage power. Increasing speed and complexity of today's designs resulted in increase in power consumption. System on Chip (SoC) may have few modules which are supplied with subthreshold voltage to achieve low power consumption and the remaining work with above threshold voltage supply. The level shifter which can convert subthreshold voltage level to supply voltage level is designed to minimize circuit leakage power with optimum number of transistors in the circuit. MRWCMLS has been implemented in 180 nm CMOS technology and is simulated using Cadence Virtuoso Simulator and the results are compared with the existing level shifters. In comparison with Revised Wilson Current Mirror Level Shifter (RWCMLS), the leakage power with normal transistors and with high Vth transistors type of implementation of the proposed MRWCMLS, is reduced by 34% and 43% respectively.

This paper aimed to compare the analysis of two different face annotation techniques. There is a sudden powerful research in mining weakly labeled web facial images on the internet to tackle the existing longtime research challenges in computer vision and image processing. In this paper, unified learning framework for auto face annotation by mining web facial images and another scheme Mining weakly labeled web facial images for search-based face annotation are analyzed and the former designed with two learning schemes such as inductive and transductive learning's which are used for this framework. For inductive, weak label laplacian support vector machine is proposed and for transductive weak label regularized local coordinate coding is used. By combining inductive and transductive learning schemes produces a maximum efficacy. For search -based face annotation two algorithms such as ULR algorithm is used to refine the weak labels of web facial images using machine learning techniques and clustering algorithm is used to improve the scalability of the web facial images.

The paper deals with harmonic reduction of cascaded multilevel inverter with non equal DC sources using particle swarm optimization algorithm. The proposed Scheme for multilevel inverter is multicarrier PWM control using PSO algorithm. The system is an effective replacement for the conventional method which has high switching losses and eliminates the use of transformer. The simulation result portrays the effective control in the switching angle to obtain minimum THD performance. The simulation of cascaded multilevel inverter is done in Matlab software package in Simulink environment. The application of this scheme is in grid and standalone applications.