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It is very common part of discussion that normal structures lag behind in terms of energy saving and its corresponding impacts on environment. This drives research to show implementation of common solutions and concepts that can be easily applied by majority of individuals to fulfill sustainable and self-sufficient goals to lead to a better habitat to live in. The aim of paper is to explore proper application of most common and most essential cost-effective design solutions to make structure following a step towards self-sufficient in itself. The paper has emphasized on quantitative and mathematical approach of study generating owns secondary data, from various research papers that are based upon similar background aspects. The value analyzed for solar panel tilt should range from 20o-30o for maximum efficiency, similarly distance between panels should be 1m-1.6m and horizontal shading device and vertical shading device should have at least depth of 450mm and 700mm respectively. The study is limited to a particular climate and region. i.e., Northeast region of India and focuses only upon most critical parameters. This paper will provide new directions for self-sufficiency in structures, which will further add values to the domain of architecture and civil engineering. Further, new areas of research can be application of new design alternatives for self-sufficiency, with respect to several other climatic conditions and regions. [ABSTRACT FROM AUTHOR]

The increase in data from modern sources, the heterogeneous nature of data, ambiguous and unstructured data, and the so-called Big Data with all of its five v's characteristics, indicate a growing need to use approaches that provide assistance in modeling and processing these data, provide additional automated data processing, and so on. The majority of all these studies involve one or more big data sets that may be used in various applications. Most of these selected papers use one or more distributed frameworks (such as MapReduce, Spark, or HDFS Hadoop distributed file systems). Furthermore, more than one strategy of Web mining is dealt with (such as Naive Bayes, Logistic Regression, and Random Forest, as examples) more than recommender system types (collaborative filtering, or/and content-based filtering). Various data sets were used (such as Movie Lens data set, LDOSCoMoDa data set, real bank loans dataset, using Facebook and Twitter for collecting data, data was taken across different companies, thousands of movies were used as exemplary data sets, or data sets used a sample data from different schools of Central Board of Secondary Education (CBSE) across India). Testing accuracy on the dataset obtained is required in the accuracy used (precision and recall). The best precision was 0.9886 and the best recall was 0.9835 in these studies. We have displayed some studies that have high precision and low recall and some other studies that have low precision and high recall. This paper introduces a literature survey about recommender systems that deal with big data through web mining techniques. [ABSTRACT FROM AUTHOR]

Agriculture is the backbone of success of rural countries like India. In this way, the proposed procedure is to utilize mechanization and web of thing (IoT) innovation to form agribusiness smart. There are currently several commercial IoT frameworks for water system planning that create differentiators for water monitoring and storage. However, this framework focuses on exploiting newly available water resources without controlling the selected water resources. Think about it, an inexpensive Arduino-based IoT framework was developed to design a computerized water system, and it will provide estimation of water requirements by using low-cost available sensors. This paper is around IOT based keen cultivating and water structure framework. The extreme motivation of this paper is to computerize the method of watering to plants. This work makes a difference us to notice the values of different parameters like moisture, temperature, humidity of plants and water them appropriately. This can be done utilizing Arduino board, voltage controller and transfer which commands the engine. In this paper, we have created an brilliantly water system framework that will control the water apportioning to the trim intelligently without any administrator and endeavors low-cost Arduino-based water system gadgets, sensors, particularly advanced procedures actualized in water system frameworks and farming, such as shrewdly water system frameworks. The main vision of this research is to detect minimum amount of water needed to nourish plants. Mass of the ranchers waste time instead of focusing on providing water to the crops at the time of need. The proposed framework find out the desired quantity of water on the basis of information received through the sensors - The main advantage of the system is the use of precision agribusiness and cloud platforms, which can expand the water use compost, which also helps in decision making. to increase crop yields. the weather conditions of the field. This article moreover points to create the water system framework for domestic gardening and this framework can be kept up without any human checking. It consequently checks the dampness of the soil beneath the tree and plants within the domestic cultivate and in case the dampness is moo it demonstrates the message and pours water naturally to the plants from the water capacity to which it is associated. The exact utilization of water system strategy is needed as there may be a requirement of precipitation or there may be dried regions. For this cause, a mechanized water system framework is utilized in which it is appropriate in all weather conditions. The soil dampness detector will sense the water substance and demonstrate either to pump the water or not. This will offer assistance to diminish the wastage of water additionally makes a difference to grow the plants indeed in the event that the human isn't physically present. The developed IoT framework has been tested in several field tests to calculate sensor accuracy, independent monitoring and operation, and usability monitoring, and to evaluate its capabilities and functionality. This framework appears to have been used effectively for the management and control of various water resources: water, groundwater, seawater and wastewater. By extension, it has been shown that the frame can be used for long periods without a source of control, which will make it a ideal device for using in annual crops. [ABSTRACT FROM AUTHOR]

Farmers grind away in the fields to take home just an exiguous income. Now, the agriculture industry is already a burdened industry with uncertainties from all directions. One of the major issues the industry is facing is crop loss. In India, every year around 30-40 per cent crops are lost. This has adverse effects on food security of the highly populated nation. For that matter, India is the 16th hungriest country in the world. Thus, there is a need to identify, understand and overcome agronomic losses. Extreme climate events and crop diseases are the two major reasons for crop losses. While climate events are less controllable, plant disease prevention becomes an important area of interest. Detecting plant diseases at early stages using images serves as key to preclusion of severity. In this paper, we have surveyed some of the significant papers on plant disease detection using image processing. [ABSTRACT FROM AUTHOR]

Grape is one of the most cultivated fruit crops in India and widely used to produce the food items. Among the world, grapes are considered as most significant fruit and it comprises various nutrients, namely Vitamin C. However, grape plants suffer with diseases which extremely affect good quality grape yield. The major six general grape leaf disease and pests are brown spot, leaf blight, downy mildew, anthracnose, and black rot, which produces severe economic suffers to grape commerce. Thus, the early detection of grape leaf disease is highly needed to produce healthy grape yield. Moreover, computer vision driven approaches have been employed effectively in modern years for detecting and classifying plants diseases. In this paper, hybrid approach with fuzzy logic and neural network has been proposed to classify the grape leaf disease. The work is further extended to identify whether leaf is affected with pesticide or not and percentages of pesticide is calculated if it is affected with pesticides. Optimization approach has been used to find accurate results. This optimization based deep learning approach achieved the accuracy of pesticide identification 93.43%. [ABSTRACT FROM AUTHOR]

With the growing number of security breaches, the necessity for better security procedures and protocols has grown as well. According to a reports, lakhs of robberies are occurring in the United States of America each year. Though India is a developing country, these types of robberies are considerably more common. The primary purpose of this work is to develop a security solution that can help combat this. This paper primarily aims to design a software that is built from the ground up for detection of face, leading to facial recognition and finally, providing information to the user or the owner of the software if any unfamiliar face is there which is not a part of the database. The aim is to notify the owner about any unfamiliar person that is present and unrecognized by the camera. In case if the face is not recognized, alerts will be sent via SMS and Email. Some software has limited forward compatibility and can be difficult to run on weak hardware, thus it is necessary to have a software which is more powerful and easily run on the weak hardware. The proposed work has a great scope in the future applications ranging from simple automatic locking systems in households to an attendance system in corporate offices and even for an antiterrorism system. [ABSTRACT FROM AUTHOR]

Emerging technologies in smart wearables hold great potential to enhance people's day-to-day health by facilitating self-monitoring of physical activities. The research with these devices is in its early stages. In this research paper, using the expectation-confirmation theory (ECT), along with conformity, performance expectancy, and satisfaction, we investigated the factors that influence the intention to use continuously. Based on a sample of 678 smart wearable users, collected from Northern India, we have used structural equation modelling (Smart PLS4) and identified the impact of satisfaction post adoption technology, Habit to wear, data privacy and health information accuracy on the continuing intention of smart-wearable users. According to the findings, consumer satisfaction, health information accuracy, and data privacy are key variables that have a significant influence on the long-term intention to use smart wearables. This study has many implications for smartwatch manufacturers and designers looking to increase users' intent to continue using their products. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI), Blockchain, and the Internet of Things are all new technologies impacting people's lives. These technologies can change how we communicate, run our businesses, and even how governments work for their people. Artificial intelligence has disrupted the way traditional marketing practices are conducted and changed how business processes are done. Organizations and governments increasingly turn to artificial intelligence (AI) to improve customer experience, operational efficiency, fraud detection, and cyber security. The revolutionary buzzword, artificial intelligence (AI), has transformed our personal and professional lives. Industry 4.0 considers AIadoption significant due to its potential benefits. Since its inception, it has presented several possibilities and difficulties to various businesses. As a result, several AI-powered technologies have been created, and they have the potential to raise significantly living standards while also boosting the economy. This paper has conducted a conducive study of the marketing tools and techniques that adopt AI while looking through the loopholes to suggest howAI can be adopted quickly into the day-to-day lives of the human race. Based on this, it has recommended a course of action for India that entails the development of infrastructure, policies and rules, research and development, and humanresources. It is necessary for all parties involved to gather and address these problems. Infrastructure development, applications in the public sector, policy & regulation, technological development, and human resource development are all key responsibilities of the government. However, with the assistance of business, they may be accomplished effectively. For this study, the authors have employed secondary data. Future empirical studies might be conducted to compare the development of artificial intelligence technology in India to that of other emerging nations. The study is based on secondary data to demonstrate the development of artificial intelligence technology in India and overseas. However, empirical research may be conducted in the future. The writers' original points of view are presented in the article. [ABSTRACT FROM AUTHOR]

Nowadays in India, due to the increase in the number of accidents vehicles are being automated using a variety of Computer vision algorithms. This paper focuses on the detection of tail signals of cars under different illumination circumstances. This system is implemented using FAST and SIFT algorithm which helps to extract features from the images. The obtained features were optimized by using K-Means Clustering Algorithm. This huge feature vector is converted into 8 clusters. These optimized feature vectors were trained on five different classifiers as Decision Tree, SVM(RBF), Random Forest, and Voting Classifier. The trained data set used in this algorithm contains around 9052 images. The obtained accuracy results of different classifiers are as follows, Decision tress has 76.36%, SVM(RBF) has 77.91%, Random Forest has 87.52%, KNN has 89.72%, the Voting classifier has 86.52%. It is observed that KNN gives the highest accuracy among the five used classifiers. This has, to the best of the authors' knowledge, not been presented in literature before. [ABSTRACT FROM AUTHOR]

The Planning Commission, Government of India has estimated the water demand increase from 710 BCM (Billion Cubic Meters) in 2010 to almost 1180 BCM in 2050 with domestic and industrial water consumption expected to increase almost 2.5 times. The trend of urbanization in India is exerting stress on civic authorities to provide basic requirement such as safe drinking water, sanitation and infrastructure. There is a need for finding alternative to the traditional rapid sand filters employed in various cities for filtration purpose. Presently sand is being used as the filtration media which is limited resource. This paper discusses the use pervious concrete with specific aggregates as filtration device. Twelve concrete mixes were used to identify an optimum mix for treating turbidity effectively using lightweight expanded clay aggregates (LECA) considering the properties of w/c ratio and size of LECA and finding their impact on density, Infiltration rate, void ratio and removal of turbidity. It was observed that lower w/c ratio of 0.35 gave a higher density. The void ratio, infiltration rateand turbidity removal for LECA of size 10 mm and w/c ratio 0.4 gave the optimum results. [ABSTRACT FROM AUTHOR]

This paper examines the usage of the Internet of Medical Things (IoMT) in the growing smart technologies of older people. Using the theory of "Unified Theory of Acceptance and Use of Technology" (UTAUT) extended by "Protection motivation" and perceived risks, a model to determine IoMT usage was developed. A survey questionnaire from senior users in India was used to collect information from 259 older people. Empirical outcomes reveal performance expectancy, effort expectancy, facilitating conditions, perceived severity, perceived vulnerability, and perceived response cost determined the motivation to use IoMT for older adults. The findings also show that novelty-seeking moderates significantly the relationship between motivation and IoMT usage. This study advances the understanding of the motivators for IoMT usage among older people to engage them with smart technologies to monitor their health better. The research outcomes can be helpful to healthcare practitioners, having theoretical, practical, and social implications for building an intelligent well-being ecosystem for elderly people. [ABSTRACT FROM AUTHOR]

Hydrogeochemical behavior has an important factor to analysis the groundwater quality. The quality of the GW is directly interlinked with the GW recharge. GW management and protection is the important task not only for the Government but also it is responsibility of every human. The report of WHO told that 80 percentage of the disease of the whole world related with the water. In India as per the report of Niti Aayog 60 crore of our own country people are facing water problem. In this paper a brief review was done for the GW quality and its different types of analysis such as ANN, SCS-SN and many other different types of method. In our review we found that there is a significant spatial and temporal change in the GW and its parameters. Rainfall, Evapotranspiration are also the significant factors which influence the GW. In the coastal areas sea water intrusion is a major issue, to determine the hydrogeochemical characteristics of that influence region geophysical, geochemical and stable isotopes techniques are used. [ABSTRACT FROM AUTHOR]

Sign language is a crucial mode of communication for individuals who are deaf or hard-of-hearing, and a reliable sign language recognition system can greatly aid in bridging the communication gap. According to statistics provided by the Government of India, there are only around 250 accredited sign language interpreters in India, servicing a deaf population of 1.8 million to 7 million individuals. This paper presents a real-time sign language recognition system for Indian Sign Language (ISL) using YOLOv8 for object detection. The system uses a single convolutional neural network (CNN) architecture to process the entire image in one forward pass and predict the bounding boxes and class probabilities for each sign in the image. The results of the study demonstrate the feasibility and potential of the system in revolutionizing communication for the deaf and hard of hearing community and have applications in gesture-controlled robotics, home automation, game control, human-computer interaction, and sign language interpretation. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy worldwide, it has become imperative to explore and adopt sustainable energy practices. In this regard, predicting household electricity consumption accurately is essential, as it can help optimize energy usage and reduce waste. This paper focuses on using Long Short-Term Memory (LSTM) shows the neural networks to prevent household electricity consumption in India. The LSTM model was implemented using the Keras library in Python. The model was trained using the training set and tested using the testing set. The study demonstrated that LSTM neural networks are a promising approach to predicting household electricity consumption in India. Further research can be conducted to recover the accuracy of the perfect by including more variables such as household size, income, and appliance usage. [ABSTRACT FROM AUTHOR]

India is one of the hugest rice cultivating country in the world. For thousands of years rice is a most major food, consequently every mankind depends on it directly and indirectly. But the Main hindrance in rice production is rice leaf diseases. It greatly reduces the production rate. Rice leaf diseases have specific symptoms that cannot be easily identified by usual human's eye. Using one of the image processing techniques, the rice leaf diseases are detected efficiently. In order to detect the diseased image Median Filter, K-means Clustering, GLCM and SVM classifier algorithms were proposed. Accuracy, Precision and ROC of SVM classifier were calculated as performance metrices. Around 97±2 % accuracy was achieved in this method. This paper discusses the efficient methodology for rice leaf disease detection. By using proposed method diseased leaves are identified at the early stage, which can aid farmers in preventing further damage to their crops. [ABSTRACT FROM AUTHOR]

During COVID-19 pandemic from 2019 onwards emergent demand of online classes has become worldwide prevalent. In the present era of pandemics along with advanced information and communication technology (ICT), institutions have shifted their pedagogy and are providing effective class room learning using web. Students are also joyful getting rid of class room constraints like modality, rigidity and inconveniency. The main objective of this research was to determine quality learning and students career growth as educational outcome via massive open online courses (MOOCS) as compared to that of traditional classes going physically offline and face to face (F2F). A total of 92 students of UG and PG level from different Indian universities and 8 countries including India were interviewed through questionnaire shared to achieve the objective. No significant difference was observed. In many research questions MOOCS were better proved than F2F. This paper will enrich the domain of distance learning, management and promote online learning using ICT. [ABSTRACT FROM AUTHOR]

Indian Consumer traditionally been known for the reusing product through generations to fullest of its life. Globalization has changed Consumer needs, purchasing power & social status which has sparked the changes in consumption pattern. Products are getting manufactured for single use instead of durable. This has been generating the lots of waste in day today life. Increasing population, its demand & consumption pattern has triggered a sharp rise in the input material demand & price. India's limited natural resources makes it difficult to suffice need of population. Circular Economy (CE) is the solution for the imbalance in supply vs. demand. It will bring societal changes towards circularity of product and material. Circularity helps to optimize the manufacturing cost and bring down product cost. CE enables the reduction in the waste generation in manufacturing industry as well as at customer end. CE is one of the biggest contributing factors towards United Nations Sustainable Goal (SDG12) of Sustainable Consumption & Production. CE Model serve the need of different economic layers of society. CE will help India in achieving economic prosperity and environmental goals. This Paper summarize the Circular Economy application areas and benefits in Indian Manufacturing Industry. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are developing rapidly due to various factors, such as the climate and envi-ronment changes, reduction in prices comparing with conventional vehicles, due to the problems caused by gas-oline engines on the people as well as the environment. The automotive industry has changed to the EVs. EVs play a major role in reducing the emissions caused by the greenhouse gases which automatically leads to the reduction of air pollution. However, to enable the change from the traditional source of energy to fully EV powered motors, a new problem has emerged in society. The method of using electricity as a source of fuel is not a cheap task. It falls out of technology and infrastructure to support it as a primary source, infrastructure that is not available even in developed countries. EVs offer many benefits such as reducing pollution levels and oil imports bills etc. This paper offers reviews on electric vehicle mileage compiles and threats in promot-ing EVs. It also describes opportunities and challenges ahead in electric vehicles. [ABSTRACT FROM AUTHOR]

A lot of electrical and mechanical energy is wasted in the public toilets of government and private institutes, universities, and offices, in which exhaust fans run continuously during the daytime, throughout the year in India. Not only, a huge cost is involved just to exhaust foul air, but also, put on adverse effects on the environment. This event creates an undue burden on ecology and the economy. This study uncovers a solution to this research gap in the paper "Solar-assisted eco-innovation induces eco-ventilation." The system is an eco-friendly technology in which the eco-innovation system of heliostats focuses solar radiation on a hollow hot air bulb, creating a pressure difference to ensure air exchange, remove foul air, and enhance ventilation. Instead of depending on an electrical or mechanical exhaust system, this eco-innovation can be a business model that saves working costs as well as the environment, ensuring economical and ecological sustainability and also contributing to the development process. [ABSTRACT FROM AUTHOR]

After a deep questioner among students, faculty members and higher education experts. The demand for qualified engineers in the specific field as understandably gone down. The situation is grimmer for tier-2 and tier-3 colleges in India. The purpose of opting engineering course is not to get expertise in the particular course, instead to get a job in government sector with valid degree. The problem identified in the field of engineering education towards improving the quality in education is addressed with the help of exploratory data analysis. The dataset used in our experiment is collect from UCI machine Learning Repository having 33 variables and 1044 observations. The contribution made in the paper is to identify the vital attributes using single and multi-variant regression techniques. To perform prediction using Decision Tree, Random Forest, Support vector Machine and compare their performance in terms of classification accuracy and F-Score. In addition to that a convolution Neural Network (CNN) model is established in which, the vital attributes identified using regression techniques are provided as inputs and weights at each stage is estimated using Gradient Decent algorithm with step size 0.5. The classification accuracy from 63% is improved to 97% with the help of CNN model in 26664 iterations. The finding of the present research states that student having backlogs are less frequently opting for higher studies. [ABSTRACT FROM AUTHOR]

The backbone of India and even most parts of the world is agriculture. Maintaining perishable farm produce is important to not to waste it, which will impact the economy and food starvation. This paper presents a mobile application for farmers or farm produce owners to check the ripeness of fruits and vegetables, which will be useful to make decisions on selling and fixing the price based on grading. The application provides information on different ripening stages of the fruits and vegetables. It also presents the information on crop's requirements for growth in terms of soil, nutrients, weather conditions, season, etc., as a reference manual. In this work, firstly, identification of different stages of ripening of perishable farm produce in field/cold storage using image processing is performed. Secondly, a mobile application is developed to give real-time status and notification of farm produce. The application will be updated with the images taken by CCTV or mobile cameras at definite intervals and notify the product owner well in time before rotting of the produce. The assessment of fruit quality is important for the cultivator and the consumer. Maturity detection is very important for fruit/ vegetable warehouses. This fruit maturity mobile application is named "Krishi Seva Bandhu". The results show that the detection accuracy is 90% and the mean opinion score of farmers is 85%. [ABSTRACT FROM AUTHOR]

The deaths caused by road accidents are one of India's most pressing issues. The inattentiveness of the driver is responsible for almost 80% of all collisions. Mobile phone use, conversing with passengers, reaching behind the wheel to grab something, and drinking while driving are just a few of the factors that can cause a driver to become distracted. This project aims to create a reliable and effective system for detecting and classifying distracted drivers. The efficacy of CNNs in the field of computer vision was the inspiration for this paper, which proposes a paradigm based on Convolutional Neural Network which not only senses but also recognizes the driver who is distracted. For this purpose it is using a publicly available dataset from the Kaggle website as an input for this model. There are several different forms of distractions, but this study focuses on the manual distraction, which is focused on the driver's stance. The goal of this work is to keep an eye on the driver's actions and seek for diversion signs. Distractions are divided into two groups in the model: safe driving and unsafe or distracted driving. For this purpose, various architectures of CNN can be used. This work, however, employs sequential architecture and achieved the highest observed accuracy of 99% with a total of 9.5M trainable parameters. The primary goal of this research is to classify a test image into two states of the driver that have been considered. [ABSTRACT FROM AUTHOR]

Agriculture is the prime industry in India covering over most of the land and a huge portion of the economy. It is important to provide a proper advancement in this sector for the development of the nation. Agribots are introduced to automate simple, regular tasks so that we could focus on more important work thereby saving time and money. In this study, an agribot is introduced with an automated system for the seeding process in agriculture which reduces the labor cost. The system is designed from a hilly terrain perspective. It aims to increase the efficiency of the seeding process. The paper mainly focuses on implementing a Shrimp Rover mechanism for agriculture. This enables the robot to traverse on uneven terrain. The chassis of the robot is 3D printed using a FDM printer. Aluminum extrusions are used for the links. It will be capable of moving up and down the hill. The research work deals with the development of the robot and design related analysis. Moreover, a novel seeding mechanism has been implemented in this study, it enables the rover with an efficient seeding process. The proposed design is a semi-automated rover, but a fully automated robot can be put forth in the future study. Moreover, the study of developing features such as weed cutting, irrigation, soil nutrient analysis into this robot can be implemented. The proposed design of the agribot was capable of sowing seeds one at a time at equal distances, also the rover was able to traverse through uneven terrains. [ABSTRACT FROM AUTHOR]

Renewable Energy resources contribution is increasing in power generation because of fast depletion of fossil fuels. Solar power generation is one of the major sources of renewable energy resources in tropical countries like India. But solar power generation is facing the challenge of continuous and reliable power supply because of its infrequent nature. Hence reliability evaluation of Photovoltaic (PV) system has become a demanding research area. The impact of unreliable power supply can be improved by using energy storage system viz. battery. In this paper, power generation probability of PV system is obtained using Monte Carlo Simulation (MCS) technique and reliability of PV system with and without battery storage system is evaluated by considering failure rate and repair time for every component in the PV system which provide accurate results. The proposed methodology was implemented on K L E F 161.72 kW PV power plant connected to a load of 160 kW. The proposed methodology was implemented on K L E F 161.72 kW PV power plant connected to a load of 160 kW, the results obtained are presented and are analyzed. [ABSTRACT FROM AUTHOR]

Due to the growth in gross domestic product (GDP) of the country, there is an improvement in the quality of life of an individual. And the economic status of a country also depends on the amount of electrical energy consumed. So, the requirement for energy sources is also increasing day to day to meet their high energy demand. The conventional sources of energy like coal, natural gas, petroleum products etc. are depleting and at the same time they are hazardous to environment. Hence renewable sources of energy are integrated into the grid on a large scale. For optimal utilization of resources and efficient operation of the system and also to provide end consumer reliably, smart grid has been proposed to be implemented. So, in this paper various initiatives take by the government in planning, implementing and monitoring the smart grids are presented. Different implementation challenges and their possible challenges are also proposed. So, the steps taken by the government of India and governing bodies established to monitor the smart grid initiatives are providing a favorable condition. But the identified challenges are also to be considered for its effective implementation. [ABSTRACT FROM AUTHOR]

On Instagram, the quantity of devotees is a typical achievement marker. Consequently, adherents selling administrations become an enormous piece of the market. Influencers become assaulted with counterfeit supporters and this makes an entrepreneur pay more than they ought to for a brand underwriting. Distinguishing counterfeit supporters gets imperative to decide the credibility of an influencer. This examination intends to recognize counterfeit clients' conduct and proposes administered AI models to order credible and counterfeit clients. With the appearance of the Internet and online media, while many individuals have profited by the immense wellsprings of data accessible, there has been a huge expansion in the ascent of digital wrongdoings, especially focused towards ladies. As indicated by a 2019 report in the [1] Economics Times, India has seen a 457% ascent in cybercrime in the long term length somewhere in the range of 2011 and 2016. Most estimate that this is because of effect of online media like Facebook, Instagram and Twitter on our everyday lives. This paper reveals insight into the job of phony characters in cutting edge determined dangers and covers the referenced methodologies of distinguishing counterfeit online media profiles. To make a pertinent forecast of phony or real profiles, we will survey the effect of three regulated AI calculations: Random Forest Algorithm, Logistic Regression [ABSTRACT FROM AUTHOR]