Showing papers in "International Journal of Engineering Research and in 2020"

Abstract: The management of the attendance can be a great burden on the teachers if it is done by hand. To resolve this problem, smart and auto attendance management system is being utilized. By utilizing this framework, the problem of proxies and students being marked present even though they are not physically present can easily be solved. This system marks the attendance using live video stream. The frames are extracted from video using OpenCV. The main implementation steps used in this type of system are face detection and recognizing the detected face, for which dlib is used. After these, the connection of recognized faces ought to be conceivable by comparing with the database containing student's faces. This model will be a successful technique to manage the attendance of students.

Abstract: Accidents in the present era are contributing to major deaths worldwide due to increase in vehicular density. It has been estimated that over 3, 00,000 persons die and 1-1.5 lakh persons are injured every single year in road accidents throughout the world. Bangalore today is obviously one of the most sought after cities in the country with the rapid growth in the IT industry and the rise in the number of job opportunities in the city. With the rising population in the city there is also a corresponding increase in the number of vehicles as well as accidents. In this report, the accident analysis includes prioritization of some major accident spots generally referred to as Black spots by the use of ARCGIS 10 software package. The study area includes some major accident spots in south Bangalore, Karnataka. The study includes visiting these accident prone sites, collecting required data for analysis and cross-checking the data with Bangalore traffic police records. KeywordsRoad accidents, GIS applications, Black spots.

Abstract: Analyzing the big textual information manually is tougher and time-consuming. Sentiment analysis is a automated process that uses computing (AI) to spot positive and negative opinions from the text. Sentiment analysis is widely used for getting insights from social media comments, survey responses, and merchandise reviews to create data-driven decisions. Sentiment analysis systems are accustomed to add up to the unstructured text by automating business processes and saving hours of manual processing. In recent years, Deep Learning (DL) has garnered increasing attention within the industry and academic world for its high performance in various domains. Today, Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) are the foremost popular types of DL architectures used. We do sentiment analysis on text reviews by using Long Short-Term Memory (LSTM). Recently, thanks to their ability to handle large amounts of knowledge, neural networks have achieved a good success on sentiment classification. Especially long STM networks. Keywords—Sentiment Analysis, Text Classfication, LSTM,

Abstract: This study was carried out to determine whether there are balanced eating habits by revealing the habits of nutrition and the factors causing these habits in university students who cannot establish a routine feeding cycle. For this purpose, a questionnaire was applied to the students of the Food Processing Department of Ahi Evran University Kaman Vocational School and the results of the questionnaire were determined by using fuzzy logic system. In this study, Fuzzy Logic System has been established by using Fuzzy toolbox of Matlab program and as a result, it has been observed that evaluation of feeding style of fuzzy logic systems gives consistent results. As an alternative to statistically calculated methods, new approaches can be developed by using fuzzy logic in nutritional assessment and food engineering.

Abstract: With the advancement in technology Smart door locking system have become more advanced. The android based smart door lock system here is basically designed for normal mode and multi mode operations. Such system is very much required in Bank and Business organization. The system also gives functionalities for general user, where single user is authorized to operate the lock. The cost effective implementation with advanced functionality and easy to use interface makes the system very useful.

Abstract: Atik arac lastiklerinin depolanma ya da imha sureci zor, maliyetli ve zaman isteyen bir surectir. Imha edilme surecinde kimyasal yapisi nedeni ile cevreye kirletici gazlarin salinimina sebep olan atik lastikler, gelisen ve ilerleyen teknoloji ile alternatif urun baglaminda onemli bir geri donusum malzemesi olarak degerlendirilmektir. Atik arac lastikleri parcalanma asamasi sonrasi belirli boyutlarda granul haline getirilmekte ve farkli bircok alanda uretime tekrar kazandirilmaktadir. Bu deneysel calisma ile, Ogutulmus Arac Lastigi Agregasinin (OALA) 5 farkli oranda ince agregaya ikame edilerek, iki farkli cimento turu ile hazirlanan toplamda 12 farkli Kendiliginden Yerlesen Harc (KYH) numunelerinin taze ve sertlesmis ozelliklerinin incelenmesi amaclanmistir. EFNARC’e uygun hazirlanan taze KYH numunelerin islenebilirlik ozelliklerinin degerlendirilmesi mini yayilma ve mini V-hunisi deneyleriyle yapilmistir. Sertlestirilmis KYH'nin mekanik ozelliklerini belirlemek icin 40x40x160mm boyutlarinda prizmatik numunelerin 3., 7. ve 28. gunlerinde basinc ve uc noktali bukme testleri yapilmis ve 28. gun 50x50x50mm kubik numuneler uzerinde kilcal su emme testi yapilmistir. CEM-V 42.5R ve CEM-V 32.5R cimento ile uretilen KYH karisimlarinda OALA’nin optimum kullanilabilirlik orani grafikler ve tablolar araciligi ile yorumlanmistir. Bu calisma ile KYH karisiminda OALA orani arttiginda, kilcal su emme miktarinin arttigi, basinc ve egilme kuvvetlerinin azaldigi gorulmustur.

Abstract: In the era of chatbots, besides imitating humans they can also perform complex tasks like booking tickets for movie etc. Out of various implementations, RASA is open source implementation for NLU and DIET model. It can interact with database, api, conversational flow, interactive learning with reinforcement Neural network. In this study, various features of rasa core are studied and upto much extent it can perform complex tasks. Implementation details are studied like interaction with database, API. Tracker Store has been examined with modifying the socket.io core file adding metadata to the user message data, so that user ip and port can be captured. Furthermore, the action, interactive learning and implementation details are tested on windows Pycharm IDE. Keywords—Chatbot,Rasa,open source,NLP

Abstract: In this study, engine performance and exhaust emission tests were performed using pure gasoline and volumetrically 10% ethanol-C2 or methanol-C1/gasoline blends (G100, E10, and M10) fuels in a single-cylinder, four-stroke, water-cooled, spark-ignition (SI) engine under constant engine speed (1500 rpm) and different loads (25%, 50%, 75%, and 100%). In the tested engine, the brake specific fuel consumption values of G100, M10 and E10 fuels under full load condition were found to be as 0.279 kg/kWh, 0.296 kg/kWh and 0.307 kg/kWh, respectively. When the exhaust emissions were examined, E10 and M10 fuels were observed to have lesser CO, CO2, NOX, and HC emissions compared to pure gasoline. The lowest CO emission was determined as 3.15% for E10 fuel at 75% load. NOX emission decreased with the increase of engine load in all fuel blends, the best performance is measured as 908.86 ppm in E10 fuel at 100% load. The minimum HC emission for E10 fuel was measured as 116.36 ppm at 75% load. Compared with G100 fuel, E10 and M10 blends emitted 39% and 35% less HC emissions, respectively at 75% load. In addition, E10 and M10 fuels generated 8% and 5% less CO2 emissions at all engine loads, respectively, as compared to G100 fuel. As a result of thermodynamic analyses; The highest exergy efficiency values were found to be at 21.0% for G100, 17.92% for E10, and 16.85% for M10, respectively. Besides, the energy efficiencies were obtained to be as 30.01% for G100, 28.33% for E10, and 29.90% for M10, respectively. According to the sustainability analysis, E10 fuel performed better results than M10 fuel in order to be an alternative to G100 fuel.

Abstract: Technology plays a critical role in all daily activities of the present day. One of these needs is to create a smart home that controls operation and turns off electronic devices via a smartphone. This implementation can be implemented effectively using package tracking software that includes IoT functions to control and simulate a smart home. IoT technology can be applied to many real life issues, such as: homework, treatment, campus, office, etc. In this paper, the focus is on a safe home system that includes devices such as: air conditioning, alarm, lighting, and doors. Garage that is some of the day to day issues. The aim of this research is to come up with a simulation of smart devices that can be controlled by the end-user smart device remotely and then show the concept called smart home. Use of Cisco Packet Tracking Features Simulated smart home and IoT devices are monitored. Simulation results show that smart objects can be connected to the home portal and objects can be successfully monitored which leads to the idea of real life implementation. Keywords— IOT technology, Cisco Packet Tracer, Home gateway, IoT server, IoT moniotor

Abstract: Breast cancer is a dominant cancer in women worldwide and is increasing in developing countries where the majority of cases are diagnosed in late stages. The projects that have already been proposed show a comparison of machine learning algorithms with the help of different techniques like the ensemble methods, data mining algorithms or using blood analysis etc. This paper proposed now presents a comparison of six machine learning (ML) algorithms: Naive Bayes (NB), Random Forest (RT), Artificial Neural Networks (ANN), Nearest Neighbour (KNN), Support Vector Machine (SVM) and Decision Tree (DT) on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset which is extracted from a digitised image of an MRI. For the implementation of the ML algorithms, the dataset was partitioned into the training phase and the testing phase. The algorithm with the best results will be used as the backend to the website and the model will then classify the cancer as benign or malignant.

Abstract: For decades the Egyptian made machine tools have not updated since they were first introduced in 1960. The goal of this study is to introduce a working model for the modification of the present produced milling machine. Modification of the milling machine column is carried out by redistribution of the material were used in the casting of its column. The same mass of the material will be reshaped to be honeycomb-like rather than the present hollow structure. Several scenarios for the design of gearboxes are carried out. For the design and updating of milling machines, an integrated set of Ansys and Solidworks beside tailored written Visual Basic codes are used. Gearlab and VB codes are used for calculating the cutting parameters, gearboxes design, kinematic and calculating forced vibration frequencies. The redistribution of the material of the machine column gives light, stiff and well-damped structure. The redesign proposal gives versatile design and more reliable modifications.

Abstract: In the upcoming era of technology Virtual Reality and Augmented Reality are not new eye catching technology but still it has some limitations to put a stop for actual enactment. It is true that the progress of new technologies has made it more beneficial to afford the hardware and software made available AR, VR and MR in the number of domains including education. The nature of technologies provides a number of opportunities. It may help from traditional allocation of separate lessons to take care of pastoral responsibility to learning concepts. These technologies fulfill the needs of learners in the technological century. It reinvents the door of education and makes the education field interactive using appropriate virtual settings. This discussion of this works includes the reinvention of education using AR, VR and MR technologies. Its modified way of education fills the needs of practical lessons. Keywords— Augmented Reality, Education, Mixed Reality,

Abstract: Chronic Kidney Disease also recognized as Chronic Renal Disease, is an uncharacteristic functioning of kidney or a failure of renal function expanding over a period of months or years. Habitually, chronic kidney disease is detected during the screening of people who are known to be in threat by kidney problems, such as those with high blood pressure or diabetes and those with a blood relative Chronic Kidney Disease(CKD) patients. So the early prediction is necessary in combating the disease and to provide good treatment. This study proposes the use of machine learning techniques for CKD such as Ant Colony Optimization(ACO) technique and Support Vector Machine(SVM) classifier. Final output predicts whether the person is having CKD or not by using minimum number of

Abstract: In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the mostly used biometrics. It can used for security, authentication, identification, and has got many more advantages. Despite of having low accuracy when compared to iris recognition and fingerprint recognition, it is being widely used due to its contactless and non-invasive process. Furthermore, face recognition system can also be used for attendance marking in schools, colleges, offices, etc. This system aims to build a class attendance system which uses the concept of face recognition as existing manual attendance system is time consuming and cumbersome to maintain. And there may be chances of proxy attendance. Thus, the need for this system increases. This system consists of four phasesdatabase creation, face detection, face recognition, attendance updation. Database is created by the images of the students in class. Face detection and recognition is performed using Haar-Cascade classifier and Local Binary Pattern Histogram algorithm respectively. Faces are detected and recognized from live streaming video of the classroom. Attendance will be mailed to the respective faculty at the end of the session. Keywords—Face Recognition; Face Detection; Haar-Cascade classifier; Local Binary Pattern Histogram; attendance system;

Abstract: Cognitive Radio directs at amplifying the use of the limited radio bandwidth while accommodating the increasing number of services and applications in wireless networks. For cognitive radio networks to operate efficiently. Secondary users (SU) should be able to exploit the radio spectrum that is unused by the primary network. A censorious component of cognitive radio is thus spectrum sensing. In this report, we propose a simulation methodology for the spectrum sensing technique to meet the requirements of the IEEE 802.22 standard. The sensing performance is described through extensive simulation using MATLAB simulation tool. In most of the existing work. The simulation scenario of the CSS algorithm has been based on common theoretical assumptions rather than to meet the operational requirements of the WRAN standards. Further, it can be found that spectrum sensing and sharing have been designed separately. This research paper discusses the algorithm framework of local sensing using energy detection and cooperative sensing based on machine learning to meet the functional requirement of the IEEE 802.22 WRAN standard. The simulation results of the proposed spectrum sensing algorithm lead to formulating effective coalition formation games in order to make effective strategic interaction among secondary users. Keywords—Cognitive radio; wireless network; secondary user; spectrum sensing; energy detection

Abstract: There are too many technologies involved in today’s Agriculture, out of which spraying pesticides using drones is one of the emerging technologies. Manual pesticide spraying causes many harmful side effects to the personnel involved in the spraying process. The Exposure effects can range from mild skin irritation to birth defects, tumors, genetic changes, blood and nerve disorders, endocrine disruption, coma or death. The WHO (World Health Organization) estimated as one million cases of ill affected, when spraying the pesticides in the crop field manually. This paved the way to design a drone mounted with spraying mechanism having 12 V pump, 6 Litre storage capacity tank,4 nozzles to atomize in fine spray , an octocopter configuration frame ,suitable landing frame, 8 Brushless Direct Current (BLDC) motors with suitable propellers to produce required thrust about 38.2 KG(at 100% RPM) and suitable LithiumPolymer (LI-PO) battery of current capacity 22000 mAh and 22.2 V to meet necessary current and voltage requirements. A First-Person View (FPV) camera and transmitter can also be fixed in the drone for monitoring the spraying process and also for checking pest attacks on plants. This pesticide spraying drone reduces the time, number of labor and cost of pesticide application. This type of drone can also be used to spray disinfectant liquids over buildings, water bodies and in highly populated areas by changing the flow discharge of the pump.

Abstract: This paper deals with the basics about electroencephalogram, its processing and feature extractions. Prominently used extraction methods such as Principal Component Analysis, Independent Component Analysis, Time-Frequency Analysis, Wavelet Transform have been discussed here along with mathematical representations. Software tools and their use towards EEG are highlighted. Keywords-Electroencephalogram, tests, waves, processing, feature extractions, mean, standard deviation, power, variance, skewness, software tools

Abstract: Character recognition is one in all the emerging fields within the computer vision. The most abilities of humans are they will recognize any object or thing. The hand transcription can easily identify by humans. Different languages have different patterns to spot. Humans can identify the text accurately. The hand transcription cannot be identified by the machine. It's difficult to spot the text by the system. During this text recognition, we process the input image, extraction of features, and classification schema takes place, training of system to acknowledge the text. During this approach, the system is trained to seek out the similarities, and also the differences among various handwritten samples. This application takes the image of a hand transcription and converts it into a digital text. Keywords—HTR(Handwritten Text Recognition), NN(Neural Network),CNN(convolutional Neural Network), RNN(Recurrent Neural Network), CTC(Connectionist Temporal Classification), TF(TensorFlow)

Abstract: In an attempt to address major causes of pollution from gas flaring and transportation, the Nigerian government introduced the use of CNG (compressed natural gas) as an alternative fuel for automobiles in 1997. However, progress has been very slow as the government has concentrated more on LNG (liquefied natural gas) exportation, LPG (liquefied petroleum gas), and gas to power projects. These projects have aided in reducing gas flaring, but pollution from transportation is still increasing. This article provides an extensive review of the benefits and recommendations to foster the use of CNG as an alternative fuel for automobiles in Nigeria. The use of CNG as an alternative fuel for automobiles in Nigeria has benefits ranging from reduction in pollution to an increase in productivity, efficiency, safety, and energy security. Thus, to encourage the use of CNG as automobile fuel in Nigeria, the government needs to develop a targeted carbon tax system, favourable market-based policies and natural gas transmission and distribution network; increase availability and access to CNG refuelling stations and public awareness; subsidise vehicle conversion expenses; begin with bi-fuel/dual-fuel automobiles; assign responsibilities; reform gas pricing; partner with automobile producers in Nigeria.

Abstract: The current paper has as major purpose the design of a single-phase inverter for educational purposes. This project has the aim to use Arduino board to ease the Pulse Width Modulation (PWM) implementation on a single-phase inverter, substituting analogical circuitry. To achieve those aims, a first complete theoretical analysis will be made, including the study of the different conventional PWM techniques. The complete design is modeled in Proteus software and its output is verified practically. Keywords— Single-phase inverter, PWM, Arduino; Proteus simulations

Abstract: This study reviewed to assess the challenges of irrigation development in Ethiopia based on use and development of irrigation water and its contributions to the national economy, opportunities, and future development perspectives. Although, Ethiopia is considered as a water tower of Africa, only 5% irrigation potential is developed yet. It is believed that irrigation can increase security of crop production and income earning. Concurrently, in many parts of the country; it uplifted the food security of many smallholder farmers. However, evidence has shown that there are several challenges on the performance of irrigation schemes and most are not performing at the best of their capacity. The key challenges impeding the success of irrigation development are; poor scheme management, imperfect market, financial shortage, insufficient technical skill, lack of awareness about the use of irrigation, environmental and, social impact and institutional challenges. Local resources and adequate catchment management; soil and water conservation using physical and biological measures is essential. Poor irrigation management is highly related to lack of sufficient skills. Thus, expansion of training for farmers and water user associations by governmental and nongovernmental organizations will have a significant impact on irrigation development. There is a strong need to improve access to market information to irrigators in other to improve the system in general and an effective extension system should be in place to guide farmers to manage traditional irrigation efficiently This paper argues that there is a need of attention by irrigation administrators, policy makers and development practitioners to tackle these challenges in order to develop irrigation potential and to solve food insecurity in Ethiopia.

Abstract: Metropolitan systems are developing rapidly, growing in number and size, frequently disregarding essential planning guidelines, primarily in terms of spatial distribution. According to UN predictions, urban and metropolitan systems will markedly expand in the next 3 decades, raising shared concerns in distribution management, determining inequalities between social classes, even in developed countries. Soil becomes, then, the most important economic asset, since correct spatial distribution rules will significantly influence the perception of value in urban and metropolitan systems, determining long term effects on decision-making processes. Keywords— Economic sustainability in urban planning, Real estate values, Soil protection and awareness, Spatial distribution

Abstract: Life's routine tempo appears to be rapid and energetic and includes diverse tasks. Bird-watching is a popular hobby which offers relaxation in everyday life. Innumerable people visit bird sanctuaries to observe the elegance of different species of birds. To provide birdwatchers with a convenient tool for identifying the birds in their natural habitat, we developed a Deep Learning model to help birders recognize 60 bird species. We implemented this model to extract information from bird images using the Convolutional Neural Network (CNN) algorithm. We gathered a dataset of our own using Microsoft’s Bing Image Search API v7. We created an 80:20 random split of the data. The classification accuracy rate of CNN on the training set was observed to be 93.19%. The accuracy on testing set was observed to be 84.91%. The entire experimental research was carried out on Windows 10 Operating System in Atom Editor with TensorFlow library.

Abstract: This study evaluates bioclimatic principles application in the design of office buildings in hot-dry Climate region of Nigeria, using university senate buildings. Purposive sampling technique was adopted for the study whereby, three university senate building where selected from Dutse, Keffi and Zaria. data were collected primarily from field survey using interview and checklist. Other secondary data were collected from the institution of study. Data collected were analysed using a five point Likert scale rating with weighted values ranging from 0 to 4 or absent to very high respectively, where mean weight values of variables were derived. Result shows a low rating of 1.33 which entails that the design of office buildings in hot-dry region of Nigeria does not fully take into cognizance the application of bioclimatic principles. Building envelop and orientation, Renewable energy source, sun shading devices, indoor air and natural cooling elements were therefore recommended in developing any office building within the hot-dry climatic

Abstract: Polycystic Ovary Syndrome (PCOS) is a condition that affects girl or women during their child-bearing years and disturbs the levels of hormones. This disturbance results in problems affecting many body systems. Women having PCOS have skip or irregularity in menstrual periods as well as cysts formation in the either or both ovaries. Symptoms of PCOS are irregular periods, excess androgen, polycystic ovaries, abnormal BMI, disturbed levels of hormones (LH, FSH, DHEAS), poor insulin resistance. But as per research studies, these symptoms are not sufficient for accurate detection for diverse data. This article presents an approach where classification of PCOS will use physical symptoms and sonograms. The results of only physical symptoms are presented here. The sonogram analysis along with the physical symptoms of PCOS are needed for accurate detection and reducing number of outliers during analysis. Such detection of PCOS also helps in proper treatment and reducing the health loss. The performance analysis of various Machine learning algorithms like Multilayer Perceptron, K-star, IB1 instance-based, Locally weighted learning, Decision Table, M5 rules, Zero R, Random Forest and Random Tree to classify PCOS is presented. Amongst all the algorithms K-star algorithm is out performing in all the performance measure. Keywords— Classification, Machine Learning, Polycystic Ovary Syndrome, performance measures, sonography

Abstract: Today, mobile phones are used everywhere, and android is the primary operating system dominating the mobile operating system market field with a market share of more than 80% and most of the applications are free to download. We are targeting the horticulture sector in which smartphones can be used to provide the farmer with the details of all the different types of crops that he can harvest and also the best efficient way in which he can get the yield. All this information will be provided in regional audio form also so that it will be easy for farmers to understand. For example, it can be extremely useful for the farmers in India as he/she will get information in multiple languages within a few key presses. Even an illiterate person can use this app easily.

Abstract: Information about effects of different land use types on soil physical and chemical properties is crucial for best land management practices. Therefore, this study was conducted to investigate the effect of land use type on selected soil physical and chemical properties at sire morose sub watershed Hidbu abote district Ethiopia. Three land use types were selected from the sub watershed (Forest, grazing and cultivated land). Undisturbed core and disturbed composite soil samples were collected randomly from three sites with three replications from each land use type at two varying depths (0-20 cm and 20-40 cm) and subjected to laboratory soil analysis. Accordingly, the highest mean value sand and clay were recorded in the surface soil of grazing and cultivated land respectively. The mean bulk density of the soils ranged from 0.94 to1.4g cm and the mean total porosity ranged from 52.95 to 64.53%, which indicate good soil structure. The pH ranged from 5.9 to 6.19 while the mean value of OM range from 1.03 to 5.2%. However, the mean value of total N range from 0.09 to 0.25%. The mean value of available P ranged from 17.67 to 24.8 mg/kg, which implies high available P in the study area. The exchangeable basic cations and CEC values were within medium to high ranges in all land use types. Most of the physical and chemical properties of the soils of the study area were distinctly influenced by the different land use types.

Abstract: Tridax procumbens (T. procumbens) Linn. is a medicinal plant found in tropical, sub-tropical and mild temperate regions around the world being used in Ayurveda treatment for liver disorders, boils, blisters, cuts, wound healing and as an anticoagulant, antifungal, and insect repellent. The plant is known to contain flavonoids, alkaloids, carotenoids, hydroxycinnamates, lignans, benzoic acid derivatives, phytosterols and tannins. The plant is also associated with endophytes to produce secondary metabolies by endophytes possessing antibacterial and antifungal activities. Different parts of this plant and essential oil are associated with ethnopharmacological properties like wound healing, antibacterial, immunomodulation, antiinflammatory, antidiabetic, vasorelaxant, antihyperlipidemic, anticancer, antiplasmodial, anticoagulation and antihepatic. Most of these studies validate the concept of earlier claims that T. procumbens’s potential as a medicinal plant. Further studies are required to unravel other pharmacological activities as well as the target-based mechanism of actions. The review also highlights the need for exploring lead molecules from these myriad of compounds that are of vital importance in drug discovery strategies.

Abstract: The wireless sensor networks is the decentralized and self configuring type of network in which senor nodes can sense information and pass it to base station. Due to decentralized nature and far deployment energy consumption is the major issues of wireless sensor networks. To reduce energy consumption of wireless sensor hierarchal clustering is the efficient type of clustering technique. In this scheme whole network will be divided into fixed size clusters and cluster heads are selected in each cluster. The cluster heads are selected on the basis of energy and distance from base station. The sensor node which has least distance from the base station and has maximum energy is selected as cluster head. The cluster heads can communicate with each other and data will be transmitted to base station. In this research work, WEMER protocol is implemented and improved to increase lifetime of wireless sensor networks. In the WEMER protocol, whole network is divided into clusters and cluster heads are selected in each cluster. The leader nodes are also selected in the network which take data from the cluster heads and pass it to base station. In the improvement of WEMER protocol. Gateway nodes are deployed in network to increase lifetime of WSN. In the proposed improvement gateway nodes are deployed near to base station which takes data from the leader nodes. The leader nodes take data from the cluster head. The proposed WEMER protocol and WEMER protocol are implemented in MATLAB. The simulation results shows that proposed WEMER protocol has less number of dead nodes, high number of alive nodes, send more number of packets and more remaining energy consumption. CHAPTER