In this paper, we propose a framework for developing a home automation system based on an IPv6 personal area network protocol – the 6LoWPAN. The proposed framework supports various kinds of end-devices. It provides the ability to remotely control the end-devices over Bluetooth Low Energy (BLE). It is able to automatically perform the appropriate actions based on user-predefined scenarios. The most advantage of the proposed framework is runtime configurable without any needs of reprogramming or resetting the whole system. We also develop a prototype of home automation system to prove the robustness and the advantage of our framework. Home automation today is not a new thing but most advanced home automation systems in existence today require a big and expensive change of infrastructure. This means that it often is not feasible to install a home automation system in an existing building. “Homatic” is a wireless home automation application that is supposed to be implemented in existing home environments, without any changes in the existing infrastructure. “Homatic” lets the user to control his home from his or her android smart phone. In the smart phone application the user can select actions what should happen with electrical and/or electronic devices in the network. Home automation is automation of the home, housework or household activity. Home automation may include centralized control of lighting, HVAC (heating, ventilation and air conditioning), appliances, and other systems, to provide improved convenience, comfort, energy efficiency and security. The concept of home automation has been around for a long time and products have been on the market for decades, though no one solution has broken through to the mainstream yet. Home automation for the elderly and disabled can provide increased quality of life for persons who might otherwise require caregivers or institutional care. It can also provide a remote interface to home appliances or the automation system itself, via telephone line, wireless transmission or the internet, to provide control and monitoring via a smart phone or web browser. This project will describe the approach which we are implementing to control various home appliances with Android smart phone.

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Image data processing is essentially the practice of applying arithmetic computations to pixel values in order to improve the picture's image appeal and extract actionable information. Image data fusion is a technique for combining data from numerous sources into a single digital object. The merged information allows for a more detailed image to be perceived visually. The notion of image fusion is used in a variety of fields. For example, in remotely sensed fields, many types of data are captured using various sensors to produce a fused binary image, such as a fused image with increased spatial and spectral resolution. Security, authentication, defensive system applications, and medical image processing are some of the other domains where image fusion can be used. In this paper, we look into SR-based picture fusion that handles both multi-component as well as global sparse representations issues. With the emergence of numerous imaging techniques in clinical imaging, multimodal clinical image fusion has grown as a strong tool for pharmaceutical research. The central reason is to compile the most meaningful data from several sources into a desired output, which is crucial for clinical diagnosing.

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In numerous fields of object recognition, image classification deep convolutional neural (CNN) has subsequently been proved to give legislature performance. Nonetheless, due to inherent hurdles, such as with the availability of a training phase, using a deep CNN to no reference image enhancement remains a complex undertaking. We present a Convolutional neural architecture in this research that can efficiently control this challenge. The suggested technique, known as the profound picture quality assessment, divides learning into two phases: 1) a part about factual deformation, and 2) a portion about the visual perception. The convolutional neural network learns to predict the optimum threshold mapping during the first level, and then the system tries to predict qualitative rating in the second part. We present a dependability chart that compensate for the inadequacy of an arbitrary reference image predictions mostly on homogenous location. In furthermore, two basic clinical effectiveness were also used to substantially estimate the reliability. In parallel, we provide a method for analysing whatever the deep convolution neural network model learnt by visualising sensory mistake map. The CNN model produced province accuracy throughout the testing.

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Global pollution is one among the main concerns of our era. Existing monitoring systems have inferior precision, low sensitivity, and need laboratory analysis. In this Smart Dustbin project, we have designed a prototype where the lid of the dustbin is opened, on detection of human hand and waste, and the level of waste available inside the dustbin is sent as notification in the form of LED. This dustbin can be a start to Smart Waste Management System where the officials can clean or empty the dustbin which depends on the notification received by them and not waiting for a call from a person of a society who informs the garbage trucks to come and take the waste from them. Our project focuses mainly on outdoor dustbins placed outside every corner of the street and societies that maintained by the Municipality. Hence our main motive is to efficiently organize and manage outdoor dustbins for a clean and hygienic environment.

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The current paper comprises of COVID-19 infection recognition utilizing assistant VGG16 and ResNet. One specific manifestation utilized in our accommodation for ILSVRC14 is called VGG16 and ResNet, the nature of which is surveyed with regards to order and detection. The instrument dependent on Convolutional Neural Network may assist the world with fostering an extra COVID-19 sickness moderation strategy. In this review, a computerized Covid-19 discovery framework has been presented, which utilizes signs from Chest CT scans to prepare the new profound deep learning model VGG16 and ResNet. The exhibition of the proposed framework has been assessed utilizing 3993 Chest CT pictures. The pictures were acquired from two distinct sources – University of Wonkwang Hospital and University of Chonnam National Hospital. Out of 3993 pictures, 3194 samples were used for testing purpose, and 799 samples were used for testing purpose. The proposed calculation has accomplished an affectability and explicitness of 100 % and 97.1 % separately, with a general precision of 98.5 %. The end shows that VGG16 and ResNet strategy is generally proficient than CNN Method to identify the COVID-19 sickness.

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The objective of this work is to automatic Sealant Dispensing unit in order to achieve high productivity of workpieces than the Sealant Dispensing machine using pneumatic power. Pneumatic is a huge topic of science and engineering dealing with the mechanical properties of air. In our project we take this pneumatic and a Dispensing unit, the pneumatic reciprocating constant pressure has an advantage of working in constant pressure, the Dispensing unit used requires adhesive material in order to bond different pieces together can benefit greatly from silicon glue. Commonly, silicon glue will bond quickly, but can be applied with precision, allowing user to create the most delicate and intricate metal easily and with minimal mess.

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Posture recognition is one of the most exciting areas of computer vision, due to the wide range of applications in various fields. The problems of the previous system, a simple camera, can be resolved with the help of a 3-d camera. In this study, methods for the use of the structure of the information to be provided by the Kinect 3-d camera for the purpose of recognition for the successful real-time intelligent monitoring and control. To achieve the orientation of the recognition, the system can make use of the Kinect to track the bones, joints, and the position. Through the analysis of the information contained on the site, the system will detect improper conduct.

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The most time-consuming part in university classes is attendance process, the traditional way of tracking attendance using pen and paper can be harder. This problem can be solved through smartphone very quickly and easily. This paper describes a method for Student’s Attendance System which will integrate with the face recognition and the fingerprint technology and the use of QR code. Automated attendance system is a system which will record the status of the student whether the person is absent or present. This involves a simple app built using kotlin in android studio. The proposed system has two applications, one is for the faculty where QR code can be generated and second one is for the students. A unique feature of QR code generation for every session makes it easier for the faculty to take the individual attendance. The students will need to scan the QR code generated by the faculty and the attendance downloaded by the faculty will be generated in the form of XLS sheet for recording the attendance. Furthermore, the paper will present and discuss the features and applications of the module and technical solutions.

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This research comprehensively assesses the response of G+30 high-rise buildings link with skybridge under earthquake loads. There are three method adopted for analysis static, Response spectrum and time history. In time history analysis, earthquake data from previous earthquakes (EL Centro 1940) is taken. Study focuses to evaluate two important parameters which are (a) story drift (b) maximum displacement. Analysis has been carried out using computer software. Based on result it is found that the story drift obtain from THM is slightly higher compared to RSM.

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Rice is deliberate as a major source of food among the rural population and also it is considered and the second most cereal crop cultivated over the world. Over the past decades, rice crops are crucially admitted as one of the powerful energy streams for the production of resources. Rice plant diseases are considered as a raising factor behind the agricultural, economic and communal loss in the upcoming development of the agricultural field. Identifying disease from the images of the plant is one of the interesting research areas in computer and agriculture field. This paper presents a survey of various image processing techniques using machine-learning approaches to identify region and classes of rice plant diseases based on images of diseases affected rice plants. Especially those techniques identify Leaf blast, Brown spot, sheath blight and bacterial blight disease of the plant on basis of the leaf characteristics. Further it analyses the noise reduction and segmentation algorithm to reduce the interference of complex background with the detection of target blade in the image by charactering it on basis of texture, color and shape. Feature identified on basis of the supervised and unsupervised learning algorithms to screen the seedling on the feature identified but it has some limitation. Towards effective identification, deep learning architecture based Convolution Neural Network has been outlined which can be effectively employed to determine the different sizes of the dataset on rice plant diseases.

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The objective behind this project is to develop a web application, which helps patients to get prescriptions and suggestions from their preferred choice of doctor, without actually step in to the hospital or make an appointment with doctor. The users using this ‘E-Healthcare: Medical Practice Management System’ need not go to any clinic to get the prescriptions or advice from the doctor. They simply login to our application as a registered member to raise a request for prescription from their preferred choice of doctor. In order to become registered member of our application they have to sign up with registration number provided by the hospital at the time of their visit. Along with registered members guest users can also look out for information like health tips, information regarding common medical conditions and doctors availability. Our application also allows individual specialists and hospitals to register. As an admin of this application one can generate various statistical reports. Any user who signed in to our application able to securely signed out.

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Data mining algorithms play a vital role to classify Gene expression data, for the prediction of diseases. With the help of gene expression data obtained from microarray technology, heterogeneous cancers can be classified into appropriate subtypes but accurate Cancer classification based on the DNA microarray data is still a difficult problem because there are huge numbers of genes relative to the number of training samples and it is a difficult task to create an optimal classifier for DNA analysis that deals with only a few samples with large number noisy features. Since it become difficult to human to see all those parameter in a short type of time span. The failure in diagnosing of right type of cancer, become inevitable to avoid, that may cause delay in treatment. It may cause causality also. We can use AI to sort out the problem. Here we reestablish the fact that a string matching based feature selection technique for finding most informative genes then we test the effectiveness of the proposed approach using a neural network based classifier on leukemia benchmark gene expression data sets. The obtained results are encouraging.

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This is a mechanical Segway. In this we have not used gyroscope and sensor. But we are making it high efficient. The system is able to operate in transporter mode and robotic mode. The first goal is to maintain stabilization in pitch dynamic. This project focuses on to manufactured Segway without using any type programming & Sensors a state feedback to stabilize system on transporter mode. The system consist of forward and backward movement when the driver operating switch in transporter mode in order to stabilize body. Small wheel is used so that there is no need of gyroscope for balancing purpose.

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AI research has focused on improving the decision-making capabilities of computers, i.e., the ability to pick high-quality actions in pursuit of a given objective. When the aim is aligned with the values of the humanity, this will cause tremendous benefits. When the target is misaligned, improving the AI system’s decision-making may cause worse outcomes for the humanity. The objectives of the proposed research are to make a mathematical framework during which fundamental questions useful Alignment is often investigated; to develop and experiment with methods for aligning the values of a machine (whether explicitly or implicitly represented) with those of humans; to know the relationships among the degree useful alignment, the decision-making capability of the machine, and therefore the potential loss to the human; and to understand especially the implications of the computational limitations of humans and machines for value alignment. The core of our technical approach are going to be a cooperative, game-theoretic extension of inverse reinforcement learning, allowing the various action spaces of humans and machines and therefore the varying motivations of humans; the concepts of rational meta-reasoning and bounded optimality will inform our investigation of the effects of computational limitations.

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Water quality index (WQI) is valuable and unique rating to depict the overall water quality status in a single term that is helpful for the selection of appropriate treatment technique to meet the concerned issues. Water quality is considered as a major issue in mega cities of developing countries. The city of Faisalabad has over 5.387 million population. Groundwater is the main source of drinking water in Faisalabad. The groundwater quality should be regularly monitored to cope up with drinking water quality index. However, WQI depicts the composite influence of different water quality parameters and communicates water quality information to the public and legislative decision makers [1]. Despite absence of a globally accepted composite index of water quality, some countries have used and are using aggregated water quality data in the development of water quality indices. Attempts have been made to review the WQI criteria for the appropriateness of drinking water sources. In water quality index (WQI) the study evaluated the groundwater physicochemical parameters (Turbidity, pH, Toral dissolved solids, Nitrates, Total Phosphates, Dissolved Oxygen, Bio-chemical Oxygen Demand, Fecal Coliform, Temperature Changes).

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This project is having a chatbot which will act as a assistant for the user. Chat bots are intelligent systems that understand user’s natural language queries and respond accordingly in a conversation, which is the focus of this study. It is more like a virtual assistant, people feel like they are talking with real person. They speak the same language we do, can answer questions. In banks, at customer care centers and enquiry desks, human is insufficient and usually takes long time to process the single request which results in wastage of time and also reduce quality of customer service. The primary goal of this chatbot is, customer can interact with mentioning their queries in plain English and the chat bot can resolve their queries with appropriate response in return.

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The objective of this paper is to study the effect of punch velocity & die corner radius in single stage deep drawing process and to determine the factors influencing on deep drawing process. CAD modeling of dies is done using Solid Edge V19 and simulation of deep drawing is carried out using AFDEX simulation software. Analysis is carried by varying punch velocity and die corner radius and keeping the following parameters like punch radius, binder holding force, coefficient friction, and blank thickness constant. Punch velocity is varied from 850mm-s to 950mm-s and die corner radius is varied in between 2mm to 7mm. The BHF (775N) and co-efficient of friction (0.125) are kept constant. The forming type is cold and hence the temperature is maintained at 25ºC.The material used for this simulation process is Aluminium Alloy AA6061.

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Our life is dependent upon trees. There is a long association of man and trees. Since the hoary past man and trees have been the two major creations of Nature. In his prehistoric days man turned to trees and plants to collect the things vitally necessary for his existence. Since that time man and trees have been interdependent, though man is more indebted to trees. Amongst the variety of flora available on the planet, “Sandalwood” are one of the most costly as well as less available trees. They are useful in medical sciences and cosmetics. From the past few years, we are finding that the newspapers and news channels are frequently filled with news regarding the smuggling activities. Since they are costly, smugglers allegedly cut down many of these trees and transport them to their factories for commercial purposes. Anti-smuggling system is a measure that has been taken to and cause substantial damage to natural and human resources. The main causes of forest re are extreme heat generated by collision of trees, lightning and some human uncontrolled behavior. The main objective of this project is to develop a system which can be used to restrict smuggling of sandalwood trees and stop these smuggling activities using GSM module and sensors.

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The significance of the security problems is greater in current data networks than in earlier systems because users are provided with the way to accomplish very critical operations like banking transfer and sharing of confidential business data, which require very high levels of protection. Weak security architectures allow successful eavesdropping (unauthorised attack), message tampering and modification attacks to occur, with huge consequences for end companies, users and other departments. The Advance Encryption standard (AES) block encryption present at the core of the f8 data hiding algorithm and also the f9 data reconstructing algorithm for Universal data Telecommunications System networks. The design aim is to enhance the data conversion rate means the throughput to an appropriate value hence the design can be used as a cryptographic sub-processor in very high speedy network uses. The work is to design an optimised solution for secure data communication AES is the standard encryption technique but proposed work is more optimised solution for the same when the chip area and encryption time considers as design parameters. Thesis work describe a new method for the Sbox-8 AES substitution and Key gen approach.

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This paper revolves around the MATLAB project from which we can calculate the solar angles i.e. solar azimuth angles, solar altitude angles, solar incidence angles of any specific time, date and month in a year. It will also help us to know the position of the sun with maximum radiation from which we know the optimum position of the solar panels for the generation of maximum solar power at any time for any specific locations. We can also compare the solar angles seasonally for any locations.

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The paper presents a new Model Predictive Power and Voltage Control (MPPVC) scheme to control and coordinate the dc-dc converter, inverter and rectifier for grid connected PV-Wind-Energy Storage Systems. The cascaded control method with multiple feedback loops has been traditionally employed for voltage and power control of PV inverters. But this method has very limited power regulation capability. As the fast increasing penetration of PV and Wind power generation systems in the distribution network, the voltage rise/drop has become a serious problem impacting negatively on the power quality and grid stability. As we are using renewable energy sources, fluctuating outputs from energy sources and variable power demand may deteriorate the voltage quality. To overcome these problems a MPPVC is proposed without using any PID regulators. By regulating the dc-bus voltage and controlling the active and reactive power flows, this method can support the power grid to maintain stable voltage, frequency and improve power factor. By controlling the bidirectional dc-dc converter of the battery energy storage system, the fluctuating output from the renewable energy sources can be smoothed, while stable dc-bus voltage can be maintained. Compared with the traditional cascade control, the proposed method is simpler and shows better performance. Numerical simulation have been conducted on a PV-Wind-Energy Storage Systems to verify capability and effectiveness of the proposed control strategy.

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The purpose of this project work is to study the material behavior in backward extrusion. The parameters considered for the process are Die corner radius, Co-efficient of friction, Ram velocity. Initial billet temperature (480), die land length (5mm) and die angle (30º) will be kept constant. The die corner radius (0.3,0.4,0.5) mm, Co-efficient of friction (0.1,0.15,0.2) and Ram velocity (1,2,3) mm-s, were varied in this project. Total 27 iterations were carried out and optimized values were obtained. Design was done using SOLID EDGE V19 and the simulation and analysis was carried out using AFDEX software.

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Water Scarcity is serious problem throughout the world for both urban and rural community. Urbanization, industrial development and increase in agricultural field and production has resulted in overexploitation of groundwater and surface water resource and resultant deterioration in water quality. The conventional water source namely well, river and reservoirs, etc. are inadequate to fulfill water demand due to unbalance rainfall. While the rainwater harvesting system investigate a new water source. The aim of the present study is to use rainwater and thus taking close to the concept of nature conservation. In this study, the rain water harvesting system is analyzed as a alternative source of water at area of Mumbai Metro Rail. The expected outcome of the study is the development of rainwater harvesting system for catchment area of Metro Rail Over Head Bridge, Station, Parking and Roads.

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The main sections of an airplane include the fuselage, wings, cockpit, engine, propeller, tail assembly, and landing gear, etc. These parts are subjected to various loads. These loads are distributed & transferred to other load taking units of an airframe by different types of fittings namely shear fitting, bending fitting, hinge fitting etc. This project deals with the design and analysis of a typical lug shear fitting representative of an airframe structure applications. The design will provide safety against Tension tear out failure & Shear bearing failure. In this project for preliminary sizing of the lug of a shear fitting suitable method (ESDU91008) which is used in aerospace industry & acceptable to aviation authorities like FAA, EASA, etc. is followed to design the lug of shear fitting. The shear fitting design involves performing numerical calculation, creating a solid CAD & FEM model and performing the finite element analysis. For material selection appropriate reference as per global aerospace industry standards is followed. The 3D CAD model of fitting is realized with the help of CATIA V5 software and Finite Element Analysis is carried out with MSC PATRAN and NASTRAN software.

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Aim of this project is to analyze the liquefaction susceptibility on selected sites. The selected sites of specific data related to Standard Penetration Tests data are collected for determination of liquefaction susceptibility of these sites. Liquefaction, which can be defined as a loss of strength and stiffness in soils, is one of the major causes of damage to buildings and infrastructure during an earthquake. To overcome a lack of comprehensive analyses of seismically induced liquefaction. The characteristics of liquefaction and its related damage to soils and foundations during earthquakes or settlements of structures. By using the research paper of Seed and Idriss in 1971 and then updated and refined by Youd and Idriss in1997, Youd et.al. In 2001 and Ray Seed in 2003 all this paper are ASCE and other researcher and calculated on Microsoft excel. Finally we can analyses the liquefied zones of sites with the help above research paper.

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