Karthick R

Facial Expression conveys non-verbal cues, which plays an important role in interpersonal relations. The Cognitive Emotion AI system is the process of identifying the emotional state of a person. The main aim of our study is to develop a robust system which can detect as well as recognize human emotion from live feed. There are some emotions which are universal to all human beings like angry, sad, happy, surprise, fear, disgust and neutral. The methodology of this system is based on two stages- facial detection is done by extraction of Haar Cascade features of a face using Viola Jones algorithm and then the emotion is verified and recognized using Artificial Intelligence Techniques. The system will take image or frame as an input and by providing the image to the model the model will perform the preprocessing and feature selection after that it will be predict the emotional state.

This work has been designed to develop an a dynamic road signal based on an emergency with density. The sync signal automatically switches to detecting traffic density at the intersection. Traffic congestion is a serious problem in many large cities around the world and has become a nightmare for travelers in these cities. The conventional traffic light system is based on the concept of fixed time assigned to each side of the join that cannot be varied by varying traffic density. The tie times assigned are fixed. But in an emergency, emergency timings change according to the distance and depth of the traffic. At the time the emergency vehicle is read by the receiver it will execute the management of the traffic light. These projects are infrared proximity sensors in the sightline configuration through the load to detect the traffic light density. The vehicle density is measured in several sectors based on the times assigned as a result. Every crossing of the emergency vehicle logs the data's to the cloud. This log signal would help with the destination acknowledgment. This synchronization will greatly reduce traffic jam.

The Medical bot project is built using artificial algorithms that analyses user’s queries and understand user’s message. This System is a web application which provides answer to the query of the patients. Patients just have to query through the bot which is used for chatting. Patients can chat using any format there is no specific format the user has to follow. The System uses built in artificial intelligence to answer the query. The answers are appropriate what the user queries. The User can query any Medical related activities through the system. The user does not have to personally go to the Medical for enquiry. The System analyses the question and then answers to the user. The system answers to the query as if it is answered by the person. With the help of artificial intelligence, the system answers the query asked by the patients. The system replies using an effective Graphical user interface which implies that as if a real person is talking to the user. The user just has to register himself to the system and has to login to the system. After login user can access to the various helping pages. Various helping pages has the bot through which the user can chat by asking queries related to Medical activities. The system replies to the user with the help of effective graphical user interface. The user can query about the Medical related activities through online with the help of this web application. The user can query Medical related activities such as date and timing of annual day, sports day, and other cultural activities. This system helps the patients to be updated about the Medical activities.

Cloud computing is the web-based empowering agent for sharing of mechanical infrastructural assets, programming, and computerized content, permitting them Infrastructure, Platforms, Software) to be offered on a compensation-for-use premise, similar to any utility assistance. Dramatic development in Computer capacities, the extra-conventional pace of development in advanced substance utilization, trailed by unstable development of uses have brought forth the beginning of Cloud Computing. The bookmarks which are saved offline can be only accessed by the specific system. The bookmarks are stored in the cloud using platform-as-a-service. Platform-as-a-service (PaaS) is the following layer up – just as the basic stockpiling, organizing, and virtual servers this will likewise incorporate the instruments and programming that designers need to assemble applications on top of: that could incorporate middleware, database management, operating system, and development tools.

The proposed project is based on a Dietitian app. The proposed app lets us discover what should we eat based on our weight, height, age, sex, and physical activity. It calculates BMI and BMR and tells us how many calories should we ideally need to intake per day. The calories we should intake will be feed in and based on the RETE algorithm the amount of food intake for the day will be decided. The proposed application is for any type of body person, it is also suited for any range of weight people. It will ideally inform how should we cut down the weight using target programs such as 1LB per week gain/loss. The given system will suggest a food list according to the meal that is if it’s breakfast lunch or dinner. It will accordingly organize heavy calorie food & light calorie food. The system will give more accurate results as it accepts the data entered by the user and processes it depending on some metrics already known to the application on the basis of which a diet plan is generated and ask the user if the user accepts the diet plan. If not accepted the system may also give an alternative diet plan

Smart home has become more and more popular in recent years. Due to the rapid development in the field of the Automation industry, human life is becoming more advanced and better in all aspects. In the present scenario, Automated systems are being preferred over the non-automated system. With the rapid growth in the number of consumers using the internet over the past years, the Internet has become an important part of life, and IoT is the newest and emerging internet technology. Internet of things plays an important role in human life as well as in the educational field because they are able to provide information and complete the given tasks while we are busy doing some other work. In this project, a prototype and implementation of Smart Home Automation with Wi-Fi technology are demonstrated. ESP8266 is used as a Wi-Fi technology. The proposed system consists of a hardware interface and software interface. In the hardware interface, the integration of ESP8266 Wi-Fi technology for controlling home appliances, door lock and unlock and sensors is manifested, and an application is provided for controlling to multiple users of home, with smart phones, tablets, and laptops. This system is one of the best methods for controlling home devices with ease with multiple users and one of the best methods for an energy management system. The access to the whole system is given by its admin only to different users. This system is also expandable for controlling various appliances used at home and also for the security and safety purpose of the home through sensors as long as it exists on Wi-Fi network coverage.

The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection methods is wearing a face mask in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments across the world to impose lockdowns to prevent virus transmissions. Reports indicate that wearing facemasks while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. A hybrid model using deep and classical machine learning for face mask detection will be presented. A face mask detection dataset consists of with mask and without mask images, we are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and Tensor Flow and Keras. Our goal is to identify whether the person on image/video stream is wearing a face mask or not with the help of computer vision and deep learning.

With the current improvement of development towards pharmaceutical, distinctive ultrasound methodologies are open to find the fetal prosperity. It is analyzed with diverse clinical parameters with 2-D imaging and other test. In any case, prosperity desire of fetal heart still remains an open issue due to unconstrained works out of the hatchling, the minor heart appraise and inadequate of data in fetal echocardiography. The machine learning strategies can find out the classes of fetal heart rate which can beutilized for earlier evaluating. With this background, we have utilized Cardiotocographic Fetal heart rate dataset removed from UCI Machine Learning Store for predicting the fetal heart rate health classes. The Prediction of fetal health rate are achieved in six ways. Firstly, the data set is preprocessed with Feature Scaling and missing values. Secondly, exploratory data investigation is done and the dispersion of target feature is visualized. Thirdly, the raw data set is fitted to all the classifiers and the performance is analysed before and after feature scaling. Fourth, the raw data set is subjected to undersampling methods like ClusterCentroids, RepeatedENN, AllKNN, CondensedNearestNeighbour, EditedNearestNeighbours, InstanceHardnessThreshold and NearMiss. Fifth, the undersampled dataset by above mentioned methods are fitted to all the classifiers and the performance is analyzed before and after feature scaling. Sixth, performance analysis is done using metrics like Precision, Recall, F-score, Accuracy and running time. The execution is done using python language under Spyder platform with Anaconda Navigator. Experimental results shows that the Decision Tree classifier tends to retain 98% before and after feature scaling for the underrsampling with EditedNearestNeighbours, RepeatedENN and AllKNN methods.

Concurring to information from the Centresfor Illness Control and Anticipation, instruction and religion are both capable indicators of lasting or dissolving unions. The chance of a marriage finishing in separate was lower for individuals with more knowledge, with over half of relational unions of those who did not complete high school having finished in separate compared with roughly 30 percent of relational unions of college graduates. With this overview, the divorce rate dataset from UCI dataset repository is used for predicting the divorce class target with the following contributions. Firstly, the Divorce rate dataset is subjected with the data cleaning and exploratory data analysis. Secondly, the data set is settled with different classifiers to look at the classification before and after feature scaling. Thirdly, the dataset is processed with various cross validation of training and testing dataset i.e 80:20, 30:70, 40:60, 50:50 to improve the accuracy of all the classifiers. Fourth, the dataset is processed with 15, 20 and 30 components of principal component analysis and then applied with all classifier algorithm to analyze the accuracy of divorce rate prediction. Fifth, the performance analysis is done with precision, recall, accuracy, fscore and running time to infer the classification before and after feature scaling. Experimental results show that the Random Forest classifier is found to have the accuracy of 98% for all PCA reduced dataset with 15, 20 and 30 components. The result showsthat Random Forest classifier is found to have the accuracy of 98% for 40:60, 50:50 of training and testing dataset.

Anamoly detection in videos plays an important role in various real-life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Nowadays, there has been a rise in the amount of disruptive and offensive activities that have been happening. Due to this, security has been given principal significance. Public places like shopping centers, avenues, banks, etc. are increasingly being equipped with CCTVs to guarantee the security of individuals. Subsequently, this inconvenience is making a need to computerize this system with high accuracy. Since constant observation of these surveillance cameras by humans is a near-impossible task. It requires workforces and their constant attention to judge if the captured activities are anomalous or suspicious. Hence, this drawback is creating a need to automate this process with high accuracy. Moreover, there is a need to display which frame and which parts of the recording contain the uncommon activity which helps the quicker judgment of that unordinary action being unusual or suspicious. Therefore, to reduce the wastage of time and labour, we are utilizing deep learning algorithms for Automating Threat Recognition System. Its goal is to automatically identify signs of aggression and violence in real-time, which filters out irregularities from normal patterns. We intend to utilize different Deep Learning models (CNN and RNN) to identify and classify levels of high movement in the frame. From there, we can raise a detection alert for the situation of a threat, indicating the suspicious activities at an instance of time and spray the smoke spray.

Multi sensor data fusion allows large scale deployments for environmental monitoring applications especially in the areas like homes, other buildings and infrastructures and industries. In such areas early fire detection is of great importance as the consequences of a fire are catastrophic. This project predicts the possibility of catching fire using a multi-sensor scheme of data fusion to enhance the performance of the early fire detection process by detecting the concentration of inflammable gases in the atmosphere and by measuring the atmospheric temperature.

Agricultural productivity is something on which Indian economy highly depends. This is the one of the reasons that disease detection in plants plays a vital role in agriculture field, as having disease in plants are unavoidable. If proper care is not taken in this area, then it causes serious effects on plants and due to which the overall agriculture yield will be affected. For instance, a disease named little leaf disease is a hazardous disease found in pine trees in United States. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself if detected properly by identifying the symptoms of diseases can result in increased productivity. This paper presents an algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases. It also covers diseases classification techniques that can be used for plant leaf disease detection. Image segmentation is one of the method which will segment the raw images in to two or more clusters and the programmed algorithm will work fine in analyzing these clusters for disease classification and prediction of type of disease that a plant leaf gets affected

Businesses and people outsource database to realize helpful and low-cost applications and administrations. In arrange to supply adequate usefulness for SQL inquiries, numerous secure database plans have been proposed. In any case, such plans are helpless to protection leakage to cloud server. The most reason is that database is facilitated and handled in cloud server, which is past the control of information proprietors. For the numerical extend inquiry (“>”, “<”, etc.), those plans cannot give adequate protection security against viable challenges, e.g., security spillage of measurable properties, get to design. Besides, expanded number of questions will definitely spill more data to the cloud server. In this paper, we propose a two-cloud engineering for secure database, with a arrangement of crossing point conventions that give security conservation to different numeric-related extend questions. Security analysis shows that privacy of numerical information is strongly protected against cloud providers in our proposed scheme.

Most forms of human papillomavirus can create alterations on a woman's cervix that can lead to cervical cancer in the long run, while others can produce genital or epidermal tumors. Cervical cancer is a leading cause of morbidity and mortality among women in low- and middle-income countries. The prediction of cervical cancer still remains an open challenge as there are several risk factors affecting the cervix of the women. By considering the above, the cervical cancer risk factor dataset from KAGGLE data warehouse is executed for predicting the cervical cancer risk classes. The cervical cancer data set is normalised with incomplete data and Pattern Calibration. Secondly, the interpretive data analysis is carried out, and the target feature's dispersion of the cervical cancer risk is visualised. Thirdly, several classifiers are fitted to the unprocessed data set, and the performance is measured with pre and post feature scaling. Fourth, oversampling methodologies are applied to the pre - processed data set. Fifth, the oversampled dataset by differment methods are applied to all the classifiers and the performance is compared with pre and post feature scaling. Sixth, Precision, recall, Fscore, accuracy, and running time are some of the metrics used in performance analysis. The code is written in Python and executed with Anaconda Navigator on the Spyder framework. The findings of the experiments reveal that the Random forest classifier tends to sustain 96% accuracy pre and post scaling for unporocessed dataset. Similarly the same classifier tends to sustain 98% accuracy for all the oversampling techniques.

The Internet of Things (IoT) wireless LAN in healthcare has moved away from traditional methods that include hospital visits and continuous monitoring. The Internet of Things allows the use of certain means, including the detection, processing and transmission of physical and biomedical parameters. With powerful algorithms and intelligent systems, it will be available to provide unprecedented levels of critical data for real-time life that are collected and analyzed to guide people in research, management and emergency care. This chapter provides a quick overview of IoT features and how they relate to wireless discovery and technology to deploy the medical applications you need. In the world, the revolution in any industry is to connect your products and devices to the Internet and make them independent and remotely connected, so that anyone can use and view them from anywhere and anytime. The Internet of Things provides us with a home automation system that uses smart devices to overcome this obstacle, allowing us to easily manage our appliances. A smart city is a vision to integrate a variety of information and communication solutions for residents with essential services, such as smart parking on all streets. The main motivation for using the Internet for parking objects is simply collecting data to get free parking. The IoT-based RTSSPS architecture is divided into three parts: a WSN-based smart street parking module, an IoT-based smart street parking module, and an IoT-based smart street parking module. IoT-based cloud with street parking algorithm, rating and future directions.

In recent days Augmented Reality is an emerging trend in marketing and sales strategies. Augmented reality ads are immersive, which means they help marketers create a certain emotional connection with customers. Unlike images or banners, for example, AR ads are interactive and lifelike consumers can see and even interact with them. Now-a-days people prefer online shopping rather than the traditional window shopping and Augmented Reality allows brands to give customers unique experiences with the convenience of tapping into their mobile devices. So the main purpose is to build an “AR Watch Try-On application” is to develop android application for trying different watches in a Virtual way using a mobile which supports AR camera. This application can be used on Online Watch Shopping websites and applications such as Titan, Fastrack, Sonata and so on. The application will eliminate the human efforts by physically visiting the Watch shops which is very time-consuming activity. User can try out multiple watches and different varients of those watches.

The main objective of our project is to construct a fully functional voice-based home automation system that uses the Internet of Things and Natural Language Processing. The home automation system is user-friendly to smartphones and laptops. A set of relays is used to connect the Node MCU to homes under controlled appliances. The user sends a command through the speech to the mobile devices, which interprets the message and sends the appropriate command to the specific appliance. The voice command given by the user is interpreted by the mobile device using Natural Language Processing. The system utilizes a node microcontroller unit (Node MCU) as a Wi-Fi-based gateway to connect to the Google Assistant. It determines operation must be completed by which the appliance to fulfill the user’s request. The user increased mobile capabilities we will be using a smart phone in this project. A smartphone application as nearly all of the data transferred can be processed by cloud. The user increased mobile capabilities we will be using a smart phone in this project. The IoT -based system for home automation can easily and efficiently control appliances. The Node MCU is interfaced with the appliances and programmed in a manner that they respond to mobile inputs.

In today’s world it became difficult for daily routine check-up. The Heart disease system is an end user support and online consultation project. Here the motto behind it is to make a person to know about their heart related problem and according to it formulate them how much vital the disease is. It will be easy to access and keep track of their respective health. Thus, it’s important to predict the disease as earliest. Attributes such as Bp, Cholesterol, Diabetes are fed into Classification methods of Machine Learning are been used to predict risk of heart disease.

In this experimental investigation the Aluminium 6063 is treated with Aluminium Oxide (Al2O3) and Chicken Bone Ash (CBA). This Aluminium metal matrix composite is mixed at certain compositions and observed with the mechanical properties. Two main mechanical properties which includes Surface roughness and corrosion behavior is mainly focused in this research work. In this Research work aluminium hybrid metal matrix composite (AHMMC) is fabricated through stir casting process. Al6063 shows good mechanical properties and corrosion behavior changes, when combined with reinforcements, Al2O3 and Chicken Bone Ash (CBA). Stir casting is an efficient cycle for the manufacture of aluminum hybrid composites. There are numerous boundaries in this cycle, which influence the behavior of corrosion and mechanical properties of the composites. Stir casting is a fluid state technique for the manufacture of composite materials, in which a scattered stage is blended in with a liquid network metal by methods for mechanical mixing. Stir Casting is the least difficult and the most financially savvy strategy for fluid state manufacture. Finally in this research work, when the compositions of each and every reinforcement increase, simultaneously the surface roughness of the composite also get increases.

In this experimental investigation the Aluminium 6063 is treated with Aluminium Oxide (Al2O3) and Chicken Bone Ash (CBA). This Aluminium metal matrix composite is mixed at certain compositions and observed with the mechanical properties. Two main mechanical properties which includes Surface roughness and corrosion behavior is mainly focused in this research work. In this Research work aluminium hybrid metal matrix composite (AHMMC) is fabricated through stir casting process. Al6063 shows good mechanical properties and corrosion behavior changes, when combined with reinforcements, Al2O3 and Chicken Bone Ash (CBA). Stir casting is an efficient cycle for the manufacture of aluminum hybrid composites. There are numerous boundaries in this cycle, which influence the behavior of corrosion and mechanical properties of the composites. Stir casting is a fluid state technique for the manufacture of composite materials, in which a scattered stage is blended in with a liquid network metal by methods for mechanical mixing. Stir Casting is the least difficult and the most financially savvy strategy for fluid state manufacture. Finally in this research work, when the compositions of each and every reinforcement increase, simultaneously the surface roughness of the composite also get increases.

The cashew nut is essential for physical and emotional well-being. It is an energetic diet and the best food medication for many illnesses. Nuts protects from malignant growth, coronary illness, circulatory strain, and various degenerative infirmities connected to aging. It can be used for several medicinal purposes. Every part of cashew has some important medicinal properties. Cashew kernel contains proteins, carbohydrates, vitamins, and fats which help gain energy. Cashew nuts are used for many purposes like blood sugar, weight loss, cancer, cold and flu, aging, urinary disorders, digestive disorders, and bone relaxation. In comparing cashew with other nuts, Cashew kernels have good properties, including proteins, carbohydrates, fibers, and minerals, then almond, hazelnut, and walnuts. Cashew kernels contain the highest number of proteins (21%) when compared with Almonds (20.8%), Hazelnuts (15.6%), and Macadamia Nuts (60.9%). Cashew contain large amount of carbohydrate (22%) compared to other nuts like almonds, walnuts, etc. There are some strong benefits of Cashew for health. They boost the immune system, act as an antioxidant, remove gallstones, and beneficial for anemia. They are good sources of healthy fats that are necessary for our body to absorb fat-soluble vitamins. Its bark is known as the antihypertensive and glucose-lowering part. It has beneficial effect on the eyes and skin. This is rich in vitamin C, so it can be used for skin problems like acne, flawless freckles, skin lines and protects from aging.

During late years, foundry industry has seen an expanding mindfulness about the significance of the filling stage for the creation of metallurgical stable and dimensionally stable castings. Specifically, oxide as well as gas entanglement into the greater part of the liquid metal during the filling of shape hole can cause shocking bringing down of the mechanical properties of the throwing, particularly during throwing of those combinations inclined to frame oxides in contact with air, for example, light composites or malleable iron. This could thusly be damaging to the "wellbeing" of the throwing during its presentation under the forced assistance conditions. In this way, much consideration is centered around understanding the methods for limiting or taking out the ensnarement of stages which are exogenous to the dissolve, for example, oxides and air pockets along the fluid metal surface. Water displaying is one such choice that could give valuable data on the conditions that may make air/gas/oxide entanglement during the filling procedure. One more alternative that has profoundly entered the current foundry situation yet may consistently be practical is the utilization of throwing recreation. The multifaceted nature of the filling procedure described by serious extent of non-consistency, instability, choppiness and free surface development calls for exploratory approval so as to have a genuine comprehension of the helpfulness of water models in reenacting the stream during constant throwing process and furthermore on the degree of programming capacity. Consequently it was proposed to contemplate the different parts of move through some chosen gating frameworks usually utilized in foundries utilizing water models and furthermore reenact a similar utilizing programming to get some crucial comprehension of the capacities and constraints of the two choices.

During late years, foundry industry has seen an expanding mindfulness about the significance of the filling stage for the creation of metallurgical stable and dimensionally stable castings. Specifically, oxide as well as gas entanglement into the greater part of the liquid metal during the filling of shape hole can cause shocking bringing down of the mechanical properties of the throwing, particularly during throwing of those combinations inclined to frame oxides in contact with air, for example, light composites or malleable iron. This could thusly be damaging to the "wellbeing" of the throwing during its presentation under the forced assistance conditions. In this way, much consideration is centered around understanding the methods for limiting or taking out the ensnarement of stages which are exogenous to the dissolve, for example, oxides and air pockets along the fluid metal surface. Water displaying is one such choice that could give valuable data on the conditions that may make air/gas/oxide entanglement during the filling procedure. One more alternative that has profoundly entered the current foundry situation yet may consistently be practical is the utilization of throwing recreation. The multifaceted nature of the filling procedure described by serious extent of non-consistency, instability, choppiness and free surface development calls for exploratory approval so as to have a genuine comprehension of the helpfulness of water models in reenacting the stream during constant throwing process and furthermore on the degree of programming capacity. Consequently it was proposed to contemplate the different parts of move through some chosen gating frameworks usually utilized in foundries utilizing water models and furthermore reenact a similar utilizing programming to get some crucial comprehension of the capacities and constraints of the two choices.

Electrical and electronic devices are constantly present in human lives, as providing communication, entertainment or transportation. Ever increasing use of power electronics equipment and communication equipment in everyday life is increasing electromagnetic pollution day by day. This pollution may degrade the performance of electronic and electrical equipment. Any RF radiation emitting devices emit Electro Magnetic (EM) radiation and without proper shielding, the radiation could be harmful to humans and other biological elements. Modernization in new generation of mobile telecommunication system, with enhanced bandwidth and power, the biological effects of electromagnetic radiation from these gadgets is a real concern to many It is necessary that all electronics equipment or systems must be constructed to ensure that any electromagnetic disturbance it generates must be constructed with inherent level of immunity to externally generated Electromagnetic disturbances. These needs to design the equipment known as TEM cell with symmetric open structure geometry to limit the amount of unwanted radiation, the shielding of critical parts, making equipment less immune to external interference.