This paper provides a brief overview of the Intelligent Traffic Management System based on Artifi... more This paper provides a brief overview of the Intelligent Traffic Management System based on Artificial Neural Networks (ANN). It is being utilized to enhance the present traffic management system and human resource reliance. The most basic problem with the current traffic lights is their dependency on humans for their working. The technologies used in the making of this automated traffic lights are Internet of Things, Machine Learning and Artificial Intelligence. The basic steps used in Internet of Things are reported along with different ANN trainings. This ANN model can be used for the minimization of traffic on roads and less waiting time at traffic lights. As a result, we can make traffic lights more automated which in turn eventually deceases our dependency on human resources .
In the field of computer science known as "machine learning," a computer makes predictions about ... more In the field of computer science known as "machine learning," a computer makes predictions about the tasks it will perform next by examining the data that has been given to it. The computer can access data via interacting with the environment or by using digitalized training sets. In contrast to static programming algorithms, which require explicit human guidance, machine learning algorithms may learn from data and generate predictions on their own. Various supervised and unsupervised strategies, including rule-based techniques, logic-based techniques, instance-based techniques, and stochastic techniques, have been presented in order to solve problems. Our paper's main goal is to present a comprehensive comparison of various cutting-edge supervised machine learning techniques.
Detection of fake news based on deep learning techniques is a major issue used to mislead people.... more Detection of fake news based on deep learning techniques is a major issue used to mislead people. For the experiments, several types of datasets, models, and methodologies have been used to detect fake news. Also, most of the datasets contain text id, tweets id, and user-based id and user-based features. To get the proper results and accuracy various models like CNN (Convolution neural network), DEEP CNN, and LSTM (Long short-term memory) are used
Fire incident is a disaster that results in the loss of life, damage to the property and endless ... more Fire incident is a disaster that results in the loss of life, damage to the property and endless disaster to the victim. Fire extinguishing is an exceptionally unsafe undertaking and it might likewise include death risk. Robotics is the answer to ensure the safeguarding of the surroundings and also the life of firefighters. Fire sensing and extinguishing robot is a model which can be used in extinguishing the fire with minimum human intervention. There is a threat to the life of the fire fighters in extinguishing the fire and there are some difficult areas where they cannot reach like that in the tunnels. At similar kind of places this automatic robot is veritably useful to perform the task. This robot can be controlled remotely by mobile phone using Bluetooth module. The robot is equipped with the flame sensors that automatically detects the fire and gives the further signal to the extinguisher units to start the pump and extinguish the fire by spraying water. Arduino uno is used as the microcontroller to operate the whole operation. The proposed robot has been used for various trials and proper evaluation has been done to check the proper functioning and to get the desired result.
In many fields, such as industry, commerce, government, and education, knowledge discovery and da... more In many fields, such as industry, commerce, government, and education, knowledge discovery and data mining can be immensely valuable to the subject of Artificial Intelligence. Because of the recent increase in demand for KDD techniques, such as those used in machine learning, databases, statistics, knowledge acquisition, data visualisation, and high performance computing, knowledge discovery and data mining have grown in importance. By employing standard formulas for computational correlations, we hope to create an integrated technique that can be used to filter web world social information and find parallels between similar tastes of diverse user information in a variety of settings .
The project's major goal is to create an intelligent trash can that would aid in maintaining a cl... more The project's major goal is to create an intelligent trash can that would aid in maintaining a clean and environmentally friendly environment. The Swachh Bharat Mission motivates us. Since technology is becoming increasingly intelligent, we are utilising Arduino nano to develop an intelligent dustbin to help clean the environment. The ultrasonic sensors on the trashcan are part of the dustbin control and management system, which happens to be designed with a microcontroller-based platform. In the suggested method, we used an ARDUINO NANO, an ultrasonic sensor, a Mini servo motor, and jumper wire linked to a charger to construct an intelligent trash can. The Smart Dustbin application will launch when all hardware and software connections have been made. Dustbin lid will wait for the person to pass by at a distance of 60 cm.
A technology called Quantum Dot Cellular Automata (QCA) offers a far more effective computational... more A technology called Quantum Dot Cellular Automata (QCA) offers a far more effective computational platform than CMOS. Through the polarization of electrons, digital information is represented. In comparison to CMOS technology, it is more attractive because to its size, faster speed, feature, high degree of scalability, greater switching frequency, and low power consumption. This paper suggests structures of basic logic gates in the QCA technology. For the aim of verification, the produced circuits are simulated, and their results are then compared to those of their published counterparts. The comparison outcomes provide hope for adding the suggested structures to the collection of QCA gates.
Online platforms are being increasingly used for ecommerce. It is increasingly being popularized ... more Online platforms are being increasingly used for ecommerce. It is increasingly being popularized through online modes of advertising. The paper aims to study the Real estate portals to evaluate those parameters which are more helpful than others. Although increasingly used the portals have hardly been investigated from the user's perspective. This paper looks into their experience of online property information search. Based on 25 responses collected on a 10 questions survey, the technical features offered by the portals are assessed based on user experience. Somehow when it comes to decision making based on the portal, there are many parameters that need to be considered. In this research, lack of features, neighborhood understanding, communication lag are attributed to the failure. One case study is taken for the purpose, PRIME PROPERTIES, which is newly launched provides an ideal online market place for Builders, Developers, Real Estates, and Agent, Sellers and Buyers to advertise their listings online. This portal is developed by students of IGNOU under guidance of Experienced Teacher and Senior student support. This is an instance of direct customer handling information display and easing customer needs and burden through direct transaction through our site to pay the installments as well as other enquiries. The portal taken for study includes functions like updating and maintaining details regarding different options for taking property on rent and buys or sell property. Also included are advertisement of property of handling through online chatting with the idea of direct interaction between property dealer and the customer. Property detail display include transaction category, property type, state, city and area etc details.
Robotics is a combination of science, engineering and technology that produces machines, called r... more Robotics is a combination of science, engineering and technology that produces machines, called robots, that can replace human actions. Robots imitate the action of human beings; it can perform the task not only what a human can do but also what they not able to do. This paper provides an overview of a robotic arms that can be controlled using a smart host microcontroller and can be powered by either solar energy or by direct power supply. The paper includes a thorough review of the referenced papers, which focuses on the development of the robotic arm with the use of smart host microcontroller and a camera function for real time image processing. There are different research papers are followed and real time image processing based Robotic arm showed the better performance and applications among other Arduino or Raspberry pi based robotic arms. Different robots/ robotic arms are capable of surveillance and also with an alternate application in detecting and following a pre specified object. There are various fields where these robotic arms play a vital role such as, in farming a robotic arm can be used to pluck fruits/vegetables from trees and plants or to implant seeds into soil without the need of human touch, in military base to remove the land mines that can be harmful for soldiers, in the medical industries (complicated surgery or pharmaceutical field), in the field of science, where a nuclear waste can be disposed by the help of a robotic arm so that it may cause no harm to any human being.
These days analysing patient data in the form of medical images to perform diagnose while doing d... more These days analysing patient data in the form of medical images to perform diagnose while doing detection and prediction of a disease has emerged as a biggest research challenge. All these medical images can be in the form of X-RAY, CT scan, MRI, PET and SPECT. These images carry minute information about heart, brain, nerves etc within themselves. It may happen that these images get corrupted due to noise while capturing them. This makes the complete image interpretation process very difficult and inaccurate. It has been found that the accuracy rate of existing method is very less so improvement is required to make them more accurate. This paper proposes a Machine Learning Model based on Convolutional Neural Network (CNN) that will contain all the filters required to de-noise MRI or USI Images. This model will have same error rate efficiency like those of data mining techniques which radiologists were interested in. The filters used in the proposed work are namely Weiner Filter, Gaussian Filter, Median Filter that are capable of removing most common noises such as Salt and Pepper, Poisson, Speckle, Blurred, Gaussian existing in MRI images in Grey Scale and RGB Scale.
A non-spinning machine element called an axle is used to support rotating parts such as wheels an... more A non-spinning machine element called an axle is used to support rotating parts such as wheels and pulleys. The axle is one of the train's most important components, and it is connected to the wheel via an interference fit. Since the beginning of railway history, derailment due to axle failure has been one of the most devastating sources of devastation. The goal is to use Computer-Aided Build software to design a railway wheel axle with specific dimensions, then model it using simulation software with the required loading conditions and constraints. This paper used Unigraphics NX-12 to model the train wheel axle and then imported it into Hypermesh software to simulate it.
Recently, in the whole world, enormous electric energy is consumed by the street lights. These li... more Recently, in the whole world, enormous electric energy is consumed by the street lights. These lights are automatically turn on when it becomes dark and automatically turn off when it becomes bright. This is the huge waste of energy in the whole world and should be controlled. Street lights in India consume approximately 20-40% of the electrical energy produced in the entirenation and the demand for electricity in recent years has increased day by day. In this paper, smart street light is introduced which is IoT based, it aims to automate the light system, also, LEDs are used to assures the low power consumption. The operation of this system is to maintain the intensity of streetlights to 40% of the maximum intensity if no vehicles passing through the road. Electricity theft problem is also address in this paper uses a sudden signal of power drop or phase drop to detect the exact pole at which electricity theft is happening or if that particular street light is faulty. Moreover, all these data are shared through IoT about and can be controlled and monitored by a mobile application.
Heaviness has been related to stroke, depression, and cancer are some of the most serious dangers... more Heaviness has been related to stroke, depression, and cancer are some of the most serious dangers to human existence. Heart disease, stroke, obesity, and type II diabetes are all disorders that have an impact on our way of life. Using data mining and machine learning approaches to forecast disease based on patient treatment history and health data has been a battle for decades. Many studies have used data mining approaches to forecast specific diseases using pathology data or medical profiles. These methods attempted to predict disease recurrence. Based on historical data from a multi-label classification problem, the review will focus on chronic disease prediction using various techniques such as convolutional neural networks (CNN), heterogeneous convolutional neural networks (HCN), and recurrent neural networks (RNNs). The study examines the current state of the art approaches for action recognition and prediction, as well as the future possibilities of the research.
Recent research shows that humans respond to music and that music has a significant impact on bra... more Recent research shows that humans respond to music and that music has a significant impact on brain activity. Every day, the average person listens to up to four hours of music. People usually listen to music that matches their mood and interests. This project focuses on developing an application that uses facial expressions to propose songs based on the user's mood. Nonverbal communication takes the form of a facial expression. The Emotion-based music player project is a revolutionary concept that allows users to automatically play songs based on their feelings. It recognises the user's facial expressions and plays music that matches their mood. Computer vision is an interdisciplinary tool that allows computers to analyse digital images or movies at a high level. The computer vision components of this system employ facial expressions to assess the user's emotion. When an emotion is recognised, the system offers a playlist for that emotion, saving the user time from having to manually select and play songs.
One of the most well-known challenges in machine learning and computer vision applications is han... more One of the most well-known challenges in machine learning and computer vision applications is handwritten digit recognition. To overcome the challenge of handwritten digit and/or letter recognition, a variety of machine learning algorithms have been used. The current research focuses on using Neural Networks to overcome the problem. Deep neural networks, deep belief networks, and convolutional neural networks are the three most well-known methodologies. The accuracy and performance of these three neural network algorithms are compared and assessed in terms of a variety of variables such as accuracy and performance. However, the rate of recognition accuracy and performance is not the only factor in the assessment process; there are more relevant metrics like execution time. Random and standard dataset of handwritten digit will be used for conducting the experiments. The trials will be conducted using a random and standard dataset of handwritten digits. The results demonstrate that Deep belief network is the most accurate algorithm among the three neural network techniques, with a 98.08 percent accuracy rate. Deep belief network, on the other hand, has a comparable execution time to the other two methods. Each method, on the other hand, has a 1-2 percent error rate due to digit form similarities, particularly with the digits (
Gears are the most essential and commonly utilised power transmission components. It is really es... more Gears are the most essential and commonly utilised power transmission components. It is really essential to operate machines involving different weights and speeds. When a load is increased beyond a certain limit, gear teeth frequently fail. Composite materials, in comparison to other metallic gears, offer significantly better mechanical qualities, such as a higher strength-to-weight ratio, increased hardness, and hence a lower risk of failure. Al6063 and SiC were employed to build a metal matrix composite for spur gear production in this work. This study discovered that composite materials outperformed steel alloys and cast iron in terms of characteristics, and that composites can thus be utilised to replace metallic gears.
Lactic acid is the most common and important chemical compound used in the pharmaceutical, cosmet... more Lactic acid is the most common and important chemical compound used in the pharmaceutical, cosmetic, chemical, and food industries. Various attempts have been made to produce lactic acid efficiently from inexpensive raw materials. Lactic acid can be produced by various methods such as fermentation of sugars and food waste. In this way, lactic acid is an environmentally friendly product that has gotten a lot of attention in recent years. The strains were isolated from five separate samples of curd, kimchi, garlic, rice water, and mango peel for the study. The study discusses the generation of lactic acid from various culinary wastes, including potato peel, orange peel, sugarcane peel, garlic peel, and mango peel. In the future, more emphasis should be placed on achieving maximum productivity and yield. Purification methods must be efficient enough to increase output while reducing product loss.
Image In painting is the process of reconstructing lost or deteriorated parts of images and video... more Image In painting is the process of reconstructing lost or deteriorated parts of images and videos. It is an important problem in computer vision and holds several importance in many imaging and graphics applications, e.g. restoring old photos and videos, automatic scene editing, denoising, compression and image based rendering. The traditional method of Image In painting which are mostly based on machine learning models work well for background in painting, they cannot hallucinate novel image contents for challenging tasks such as in painting of faces and complex objects as well as failing to capture high level objects semantics. It has been discovered that by simply introducing a small bit of noise to the original data, most mainstream neural nets may be readily misled into misclassifying items. This is because most machine learning models only learn from a little quantity of data and the input-to-output mapping is nearly linear, which is a major disadvantage and leads to overfitting. The present method where we use GANs, or Generative Adversarial Networks, are a type of generative modelling that employs deep learning techniques such as convolutional neural networks. GANs has a capability of learning from data that is unstructured or unlabeled, the algorithms try to learn using method of feature extraction which is very different, more reliable and fully automatic. Celeb Faces Attributes Dataset (Celeb A) is large scale face attributes dataset with more than 200K celebrity images, each with 40 attributes annotations.
Design And Implementation Of Air Quality Monitoring System Using Blynk App
Today, air pollution ... more Design And Implementation Of Air Quality Monitoring System Using Blynk App Today, air pollution is one of the significant environmental issues that causes adverse health effects in human bodies such as cancer, cardiologic disease and, high mortality rate resulting in damaging effects on the welfare of humans, animals and other living organisms of the environment. According to the recent research survey from WHO, India was the third most polluted country globally in 2020. Every year, about 2.5 million Indians, almost 30%, die from air pollution caused by burning fossil fuels. Given this, our group has developed a project based on an air quality monitoring system used to detect the various parameters of air that are perilous to human beings and society. An IoT-based system was developed that detected the various parameters with the help of different sensors such as PM2.5, DHT11, LDR sensor, MQ-135, and the rain sensor. These sensors continuously sense the air quality index, rain, humidity, temperature, and smoke, finally providing all the information on the smart phone. In addition, it also helps us to fetch the data from any location where the device is installed. In this project, the Blynk app is implemented, a platform with IOS and android app to dominate and equate with Arduino Uno using ESP8266wifi controller. This app continuously monitors the value, throws an alert to the user with the help of a buzzer whenever the threshold value is exceeded.
Friction stir processing is a technique for improving the characteristics of metals by causing lo... more Friction stir processing is a technique for improving the characteristics of metals by causing local, severe plastic deformation. This deformation is achieved by forcing a non-consumable tool into the workpiece and rotating it in a stirring action while being pushed laterally through it. The primary goal of this experiment is to investigate Friction Stir processing parameters, surface composite production using friction stirs, and material mechanical characteristics. The various ceramic particles, such as SiC and Al2O3, were used as reinforcement particles. The parameter for this experiment is considered as the traveling speed, tool rotation speed, and tilt angles. The main effect of the reinforcement is to improve mechanical properties, such as hardness, impact strength, and strength.
This paper provides a brief overview of the Intelligent Traffic Management System based on Artifi... more This paper provides a brief overview of the Intelligent Traffic Management System based on Artificial Neural Networks (ANN). It is being utilized to enhance the present traffic management system and human resource reliance. The most basic problem with the current traffic lights is their dependency on humans for their working. The technologies used in the making of this automated traffic lights are Internet of Things, Machine Learning and Artificial Intelligence. The basic steps used in Internet of Things are reported along with different ANN trainings. This ANN model can be used for the minimization of traffic on roads and less waiting time at traffic lights. As a result, we can make traffic lights more automated which in turn eventually deceases our dependency on human resources .
In the field of computer science known as "machine learning," a computer makes predictions about ... more In the field of computer science known as "machine learning," a computer makes predictions about the tasks it will perform next by examining the data that has been given to it. The computer can access data via interacting with the environment or by using digitalized training sets. In contrast to static programming algorithms, which require explicit human guidance, machine learning algorithms may learn from data and generate predictions on their own. Various supervised and unsupervised strategies, including rule-based techniques, logic-based techniques, instance-based techniques, and stochastic techniques, have been presented in order to solve problems. Our paper's main goal is to present a comprehensive comparison of various cutting-edge supervised machine learning techniques.
Detection of fake news based on deep learning techniques is a major issue used to mislead people.... more Detection of fake news based on deep learning techniques is a major issue used to mislead people. For the experiments, several types of datasets, models, and methodologies have been used to detect fake news. Also, most of the datasets contain text id, tweets id, and user-based id and user-based features. To get the proper results and accuracy various models like CNN (Convolution neural network), DEEP CNN, and LSTM (Long short-term memory) are used
Fire incident is a disaster that results in the loss of life, damage to the property and endless ... more Fire incident is a disaster that results in the loss of life, damage to the property and endless disaster to the victim. Fire extinguishing is an exceptionally unsafe undertaking and it might likewise include death risk. Robotics is the answer to ensure the safeguarding of the surroundings and also the life of firefighters. Fire sensing and extinguishing robot is a model which can be used in extinguishing the fire with minimum human intervention. There is a threat to the life of the fire fighters in extinguishing the fire and there are some difficult areas where they cannot reach like that in the tunnels. At similar kind of places this automatic robot is veritably useful to perform the task. This robot can be controlled remotely by mobile phone using Bluetooth module. The robot is equipped with the flame sensors that automatically detects the fire and gives the further signal to the extinguisher units to start the pump and extinguish the fire by spraying water. Arduino uno is used as the microcontroller to operate the whole operation. The proposed robot has been used for various trials and proper evaluation has been done to check the proper functioning and to get the desired result.
In many fields, such as industry, commerce, government, and education, knowledge discovery and da... more In many fields, such as industry, commerce, government, and education, knowledge discovery and data mining can be immensely valuable to the subject of Artificial Intelligence. Because of the recent increase in demand for KDD techniques, such as those used in machine learning, databases, statistics, knowledge acquisition, data visualisation, and high performance computing, knowledge discovery and data mining have grown in importance. By employing standard formulas for computational correlations, we hope to create an integrated technique that can be used to filter web world social information and find parallels between similar tastes of diverse user information in a variety of settings .
The project's major goal is to create an intelligent trash can that would aid in maintaining a cl... more The project's major goal is to create an intelligent trash can that would aid in maintaining a clean and environmentally friendly environment. The Swachh Bharat Mission motivates us. Since technology is becoming increasingly intelligent, we are utilising Arduino nano to develop an intelligent dustbin to help clean the environment. The ultrasonic sensors on the trashcan are part of the dustbin control and management system, which happens to be designed with a microcontroller-based platform. In the suggested method, we used an ARDUINO NANO, an ultrasonic sensor, a Mini servo motor, and jumper wire linked to a charger to construct an intelligent trash can. The Smart Dustbin application will launch when all hardware and software connections have been made. Dustbin lid will wait for the person to pass by at a distance of 60 cm.
A technology called Quantum Dot Cellular Automata (QCA) offers a far more effective computational... more A technology called Quantum Dot Cellular Automata (QCA) offers a far more effective computational platform than CMOS. Through the polarization of electrons, digital information is represented. In comparison to CMOS technology, it is more attractive because to its size, faster speed, feature, high degree of scalability, greater switching frequency, and low power consumption. This paper suggests structures of basic logic gates in the QCA technology. For the aim of verification, the produced circuits are simulated, and their results are then compared to those of their published counterparts. The comparison outcomes provide hope for adding the suggested structures to the collection of QCA gates.
Online platforms are being increasingly used for ecommerce. It is increasingly being popularized ... more Online platforms are being increasingly used for ecommerce. It is increasingly being popularized through online modes of advertising. The paper aims to study the Real estate portals to evaluate those parameters which are more helpful than others. Although increasingly used the portals have hardly been investigated from the user's perspective. This paper looks into their experience of online property information search. Based on 25 responses collected on a 10 questions survey, the technical features offered by the portals are assessed based on user experience. Somehow when it comes to decision making based on the portal, there are many parameters that need to be considered. In this research, lack of features, neighborhood understanding, communication lag are attributed to the failure. One case study is taken for the purpose, PRIME PROPERTIES, which is newly launched provides an ideal online market place for Builders, Developers, Real Estates, and Agent, Sellers and Buyers to advertise their listings online. This portal is developed by students of IGNOU under guidance of Experienced Teacher and Senior student support. This is an instance of direct customer handling information display and easing customer needs and burden through direct transaction through our site to pay the installments as well as other enquiries. The portal taken for study includes functions like updating and maintaining details regarding different options for taking property on rent and buys or sell property. Also included are advertisement of property of handling through online chatting with the idea of direct interaction between property dealer and the customer. Property detail display include transaction category, property type, state, city and area etc details.
Robotics is a combination of science, engineering and technology that produces machines, called r... more Robotics is a combination of science, engineering and technology that produces machines, called robots, that can replace human actions. Robots imitate the action of human beings; it can perform the task not only what a human can do but also what they not able to do. This paper provides an overview of a robotic arms that can be controlled using a smart host microcontroller and can be powered by either solar energy or by direct power supply. The paper includes a thorough review of the referenced papers, which focuses on the development of the robotic arm with the use of smart host microcontroller and a camera function for real time image processing. There are different research papers are followed and real time image processing based Robotic arm showed the better performance and applications among other Arduino or Raspberry pi based robotic arms. Different robots/ robotic arms are capable of surveillance and also with an alternate application in detecting and following a pre specified object. There are various fields where these robotic arms play a vital role such as, in farming a robotic arm can be used to pluck fruits/vegetables from trees and plants or to implant seeds into soil without the need of human touch, in military base to remove the land mines that can be harmful for soldiers, in the medical industries (complicated surgery or pharmaceutical field), in the field of science, where a nuclear waste can be disposed by the help of a robotic arm so that it may cause no harm to any human being.
These days analysing patient data in the form of medical images to perform diagnose while doing d... more These days analysing patient data in the form of medical images to perform diagnose while doing detection and prediction of a disease has emerged as a biggest research challenge. All these medical images can be in the form of X-RAY, CT scan, MRI, PET and SPECT. These images carry minute information about heart, brain, nerves etc within themselves. It may happen that these images get corrupted due to noise while capturing them. This makes the complete image interpretation process very difficult and inaccurate. It has been found that the accuracy rate of existing method is very less so improvement is required to make them more accurate. This paper proposes a Machine Learning Model based on Convolutional Neural Network (CNN) that will contain all the filters required to de-noise MRI or USI Images. This model will have same error rate efficiency like those of data mining techniques which radiologists were interested in. The filters used in the proposed work are namely Weiner Filter, Gaussian Filter, Median Filter that are capable of removing most common noises such as Salt and Pepper, Poisson, Speckle, Blurred, Gaussian existing in MRI images in Grey Scale and RGB Scale.
A non-spinning machine element called an axle is used to support rotating parts such as wheels an... more A non-spinning machine element called an axle is used to support rotating parts such as wheels and pulleys. The axle is one of the train's most important components, and it is connected to the wheel via an interference fit. Since the beginning of railway history, derailment due to axle failure has been one of the most devastating sources of devastation. The goal is to use Computer-Aided Build software to design a railway wheel axle with specific dimensions, then model it using simulation software with the required loading conditions and constraints. This paper used Unigraphics NX-12 to model the train wheel axle and then imported it into Hypermesh software to simulate it.
Recently, in the whole world, enormous electric energy is consumed by the street lights. These li... more Recently, in the whole world, enormous electric energy is consumed by the street lights. These lights are automatically turn on when it becomes dark and automatically turn off when it becomes bright. This is the huge waste of energy in the whole world and should be controlled. Street lights in India consume approximately 20-40% of the electrical energy produced in the entirenation and the demand for electricity in recent years has increased day by day. In this paper, smart street light is introduced which is IoT based, it aims to automate the light system, also, LEDs are used to assures the low power consumption. The operation of this system is to maintain the intensity of streetlights to 40% of the maximum intensity if no vehicles passing through the road. Electricity theft problem is also address in this paper uses a sudden signal of power drop or phase drop to detect the exact pole at which electricity theft is happening or if that particular street light is faulty. Moreover, all these data are shared through IoT about and can be controlled and monitored by a mobile application.
Heaviness has been related to stroke, depression, and cancer are some of the most serious dangers... more Heaviness has been related to stroke, depression, and cancer are some of the most serious dangers to human existence. Heart disease, stroke, obesity, and type II diabetes are all disorders that have an impact on our way of life. Using data mining and machine learning approaches to forecast disease based on patient treatment history and health data has been a battle for decades. Many studies have used data mining approaches to forecast specific diseases using pathology data or medical profiles. These methods attempted to predict disease recurrence. Based on historical data from a multi-label classification problem, the review will focus on chronic disease prediction using various techniques such as convolutional neural networks (CNN), heterogeneous convolutional neural networks (HCN), and recurrent neural networks (RNNs). The study examines the current state of the art approaches for action recognition and prediction, as well as the future possibilities of the research.
Recent research shows that humans respond to music and that music has a significant impact on bra... more Recent research shows that humans respond to music and that music has a significant impact on brain activity. Every day, the average person listens to up to four hours of music. People usually listen to music that matches their mood and interests. This project focuses on developing an application that uses facial expressions to propose songs based on the user's mood. Nonverbal communication takes the form of a facial expression. The Emotion-based music player project is a revolutionary concept that allows users to automatically play songs based on their feelings. It recognises the user's facial expressions and plays music that matches their mood. Computer vision is an interdisciplinary tool that allows computers to analyse digital images or movies at a high level. The computer vision components of this system employ facial expressions to assess the user's emotion. When an emotion is recognised, the system offers a playlist for that emotion, saving the user time from having to manually select and play songs.
One of the most well-known challenges in machine learning and computer vision applications is han... more One of the most well-known challenges in machine learning and computer vision applications is handwritten digit recognition. To overcome the challenge of handwritten digit and/or letter recognition, a variety of machine learning algorithms have been used. The current research focuses on using Neural Networks to overcome the problem. Deep neural networks, deep belief networks, and convolutional neural networks are the three most well-known methodologies. The accuracy and performance of these three neural network algorithms are compared and assessed in terms of a variety of variables such as accuracy and performance. However, the rate of recognition accuracy and performance is not the only factor in the assessment process; there are more relevant metrics like execution time. Random and standard dataset of handwritten digit will be used for conducting the experiments. The trials will be conducted using a random and standard dataset of handwritten digits. The results demonstrate that Deep belief network is the most accurate algorithm among the three neural network techniques, with a 98.08 percent accuracy rate. Deep belief network, on the other hand, has a comparable execution time to the other two methods. Each method, on the other hand, has a 1-2 percent error rate due to digit form similarities, particularly with the digits (
Gears are the most essential and commonly utilised power transmission components. It is really es... more Gears are the most essential and commonly utilised power transmission components. It is really essential to operate machines involving different weights and speeds. When a load is increased beyond a certain limit, gear teeth frequently fail. Composite materials, in comparison to other metallic gears, offer significantly better mechanical qualities, such as a higher strength-to-weight ratio, increased hardness, and hence a lower risk of failure. Al6063 and SiC were employed to build a metal matrix composite for spur gear production in this work. This study discovered that composite materials outperformed steel alloys and cast iron in terms of characteristics, and that composites can thus be utilised to replace metallic gears.
Lactic acid is the most common and important chemical compound used in the pharmaceutical, cosmet... more Lactic acid is the most common and important chemical compound used in the pharmaceutical, cosmetic, chemical, and food industries. Various attempts have been made to produce lactic acid efficiently from inexpensive raw materials. Lactic acid can be produced by various methods such as fermentation of sugars and food waste. In this way, lactic acid is an environmentally friendly product that has gotten a lot of attention in recent years. The strains were isolated from five separate samples of curd, kimchi, garlic, rice water, and mango peel for the study. The study discusses the generation of lactic acid from various culinary wastes, including potato peel, orange peel, sugarcane peel, garlic peel, and mango peel. In the future, more emphasis should be placed on achieving maximum productivity and yield. Purification methods must be efficient enough to increase output while reducing product loss.
Image In painting is the process of reconstructing lost or deteriorated parts of images and video... more Image In painting is the process of reconstructing lost or deteriorated parts of images and videos. It is an important problem in computer vision and holds several importance in many imaging and graphics applications, e.g. restoring old photos and videos, automatic scene editing, denoising, compression and image based rendering. The traditional method of Image In painting which are mostly based on machine learning models work well for background in painting, they cannot hallucinate novel image contents for challenging tasks such as in painting of faces and complex objects as well as failing to capture high level objects semantics. It has been discovered that by simply introducing a small bit of noise to the original data, most mainstream neural nets may be readily misled into misclassifying items. This is because most machine learning models only learn from a little quantity of data and the input-to-output mapping is nearly linear, which is a major disadvantage and leads to overfitting. The present method where we use GANs, or Generative Adversarial Networks, are a type of generative modelling that employs deep learning techniques such as convolutional neural networks. GANs has a capability of learning from data that is unstructured or unlabeled, the algorithms try to learn using method of feature extraction which is very different, more reliable and fully automatic. Celeb Faces Attributes Dataset (Celeb A) is large scale face attributes dataset with more than 200K celebrity images, each with 40 attributes annotations.
Design And Implementation Of Air Quality Monitoring System Using Blynk App
Today, air pollution ... more Design And Implementation Of Air Quality Monitoring System Using Blynk App Today, air pollution is one of the significant environmental issues that causes adverse health effects in human bodies such as cancer, cardiologic disease and, high mortality rate resulting in damaging effects on the welfare of humans, animals and other living organisms of the environment. According to the recent research survey from WHO, India was the third most polluted country globally in 2020. Every year, about 2.5 million Indians, almost 30%, die from air pollution caused by burning fossil fuels. Given this, our group has developed a project based on an air quality monitoring system used to detect the various parameters of air that are perilous to human beings and society. An IoT-based system was developed that detected the various parameters with the help of different sensors such as PM2.5, DHT11, LDR sensor, MQ-135, and the rain sensor. These sensors continuously sense the air quality index, rain, humidity, temperature, and smoke, finally providing all the information on the smart phone. In addition, it also helps us to fetch the data from any location where the device is installed. In this project, the Blynk app is implemented, a platform with IOS and android app to dominate and equate with Arduino Uno using ESP8266wifi controller. This app continuously monitors the value, throws an alert to the user with the help of a buzzer whenever the threshold value is exceeded.
Friction stir processing is a technique for improving the characteristics of metals by causing lo... more Friction stir processing is a technique for improving the characteristics of metals by causing local, severe plastic deformation. This deformation is achieved by forcing a non-consumable tool into the workpiece and rotating it in a stirring action while being pushed laterally through it. The primary goal of this experiment is to investigate Friction Stir processing parameters, surface composite production using friction stirs, and material mechanical characteristics. The various ceramic particles, such as SiC and Al2O3, were used as reinforcement particles. The parameter for this experiment is considered as the traveling speed, tool rotation speed, and tilt angles. The main effect of the reinforcement is to improve mechanical properties, such as hardness, impact strength, and strength.
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Today, air pollution is one of the significant environmental issues that causes adverse health effects in human bodies such as cancer, cardiologic disease and, high mortality rate resulting in damaging effects on the welfare of humans, animals and other living organisms of the environment. According to the recent research survey from WHO, India was the third most polluted country globally in 2020. Every year, about 2.5 million Indians, almost 30%, die from air pollution caused by burning fossil fuels. Given this, our group has developed a project based on an air quality monitoring system used to detect the various parameters of air that are perilous to human beings and society. An IoT-based system was developed that detected the various parameters with the help of different sensors such as PM2.5, DHT11, LDR sensor, MQ-135, and the rain sensor. These sensors continuously sense the air quality index, rain, humidity, temperature, and smoke, finally providing all the information on the smart phone. In addition, it also helps us to fetch the data from any location where the device is installed. In this project, the Blynk app is implemented, a platform with IOS and android app to dominate and equate with Arduino Uno using ESP8266wifi controller. This app continuously monitors the value, throws an alert to the user with the help of a buzzer whenever the threshold value is exceeded.
Today, air pollution is one of the significant environmental issues that causes adverse health effects in human bodies such as cancer, cardiologic disease and, high mortality rate resulting in damaging effects on the welfare of humans, animals and other living organisms of the environment. According to the recent research survey from WHO, India was the third most polluted country globally in 2020. Every year, about 2.5 million Indians, almost 30%, die from air pollution caused by burning fossil fuels. Given this, our group has developed a project based on an air quality monitoring system used to detect the various parameters of air that are perilous to human beings and society. An IoT-based system was developed that detected the various parameters with the help of different sensors such as PM2.5, DHT11, LDR sensor, MQ-135, and the rain sensor. These sensors continuously sense the air quality index, rain, humidity, temperature, and smoke, finally providing all the information on the smart phone. In addition, it also helps us to fetch the data from any location where the device is installed. In this project, the Blynk app is implemented, a platform with IOS and android app to dominate and equate with Arduino Uno using ESP8266wifi controller. This app continuously monitors the value, throws an alert to the user with the help of a buzzer whenever the threshold value is exceeded.