Volume 8 Issue 4
Author's Name: Saurabh S. Hher, Dhainje V. S
Abstract— In India large population is living all over the country and electricity supply demand need for this population makes recruitment of a large transmission and distribution system. Formulation of Transmission tower is proffered in assessment of confronting high voltage transmitting conductors and insulators to stance in need of altitude from ground level. Transmission Line Towers comprise of about 28 to 45 percent of the absolute cost of the Transmission Lines. The purpose of a transmission line tower is to support conductors booming electrical power and one or two ground wires at appropriate distances above the ground level and from each other. The observations from both structural and electrical fields are analysis in designing transmission line towers. There are various factors which influence the stability and performance of transmission tower are viewed in this paper. This Paper discussed and review the Methodology adopted for Analysis and Design of transmission towers. This paper can also be used for study of different parameters used in Analyzing and Designing of transmission towers.
Author's Name: Mangal Kalyani, Gupta Raju
Abstract— In this paper we are merely want to explore digital image processing which is a motivating field because it provides the higher image information for human understanding and process the image for storage, transmission, and illustration for machine perception. Image process could be a technique to reinforce raw pictures received from cameras/sensors placed on satellites, aircrafts or photos taken in traditional everyday life for varied applications. Pre-processing is the initial process applied on images which are at lowest level of abstraction. Also Shape analysis methods play an important role in systems for object recognition, matching, registration, analysis, accurate detection of image, Research in shape analysis has been motivated in part, for fast recognition of image from large data base. Accessing the desired and relevant image from large data base in an efficient manner is another motive for research. Various techniques of shape detection are based on shape boundary or interior.
Author's Name: Raju Patel, Rishil Mayank
Abstract— The use of different types of pavement block has been increased in India a decade ago. The specific requirements of paver block has been increased in the areas of footpaths and parking areas. Port land Cement Concrete and Asphalt Concrete are the most common roadway and highway construction material used. It is very necessary to use the materials which is durable and have the high compressive strength and can absorb the water to greater extent to have the greater water absorption value. In this project we have given greater stress on about the use of materials and machinery involved for the manufacture of different types of paver block in construction Purposes. For design of paver block the tests is to be performed is used to find the compressive strength and water absorption. The blocks having greater compressive strength and of less cost and can be used for much more time have been studied out in this project.
Author's Name: Gaurav Paniwal, Shruti Gupta
Abstract— This work explores the tools and technologies used in smart agriculture. Artificial Intelligence and Machine Learning techniques, including basic block models that are used to do smart agriculture. How can we use fuzzy logic and Artificial Neural Network, is also covered in this paper. We have explored some of the IOT based irrigation systems including crop prediction systems. The necessary hardware, software and sensors that can be used to make precision agriculture are also included. The main motto of this paper is to get a detailed literature review that is required for smart agriculture.
Author's Name: Aaditya Sharma, Aman Sharma, Punit Sharma, Punit Ekka
Abstract— Physically challenged people or the people with disabilities are those section of the society in which the society embarks no decision or gives any judgement about their physical abilities of the working body parts and the other requirements of them according to their physical fitness as well, the present generation has the awareness regarding keeping themselves fit and sportingly active but on the other hand the people who are physically challenged are unable to work on the same. The project hereby tries to implement the solution for the same by giving the various physical exercises that could be done by the physically challenges people according to their working body parts and according to their ability accordingly.
Author's Name: Santhosh, Sai Laxmi
Abstract— Identifying of the plant diseases is essential in prevention of yield and volume losses in agriculture Product. Studies of plant diseases mean studies of visually observable patterns on the plant. Health surveillance and detecting diseases in plants is essential for sustainable development agriculture. It is very difficult to monitor plant diseases manually. It requires a lot of experiences in work, expertise in these field plant diseases and also requires excessive processing time. Therefore; image processing is used to detect plant diseases. Disease detection includes steps such as acquisition, image Pre-processing, image segmentation, feature extraction and Classification. We describe these methods for the detection of plant diseases on the basis of their leaf images; automatic detection of plant disease is done by the image processing and machine learning. The different leaf images of plant disease are collected and feature extracted of the various machine learning methods
Author's Name: Shubham Kumar, Kanchan Bhatt
Abstract— Weather Forecasting is the attempt to predict the weather conditions based on parameters such as temperature, wind, humidity and rainfall. These parameters will be considered for experimental analysis to give the desired results. Data used in this project has been collected from various government institution sites. The algorithm used to predict weather includes Neural Networks(NN), Random Forest, Classification and Regression tree (C &RT), Support Vector Machine, KNN Nearest neighbor. The correlation analysis of the parameters will help in predicting the future values. This web based application we will have its own chat bot where user can directly communicate about their query related to Weather Forecast and can have experience of two-way communication.
Author's Name: P. Kavitha, S. Ramadevi
Abstract— Sentimental analysis is also called "opinion mining" analyses attitudes and classifies text views. It relates to the use of natural language processing, text, and linguistic processing. A huge amount of data is created with the rapid growth of web technologies. Social networking sites are now popular and normal places where feelings can be shared by short messages. These sentiments involve happiness, sadness, anxiety, fear, etc. The analysis of short texts tends to recognize the crowd's sentiment. Sentiment Analysis on IMDb moviereviews describes a reviewer's general feeling or impression of a movie. Since the perceptions of humans improve the effectiveness of products & since a movie'ssuccess or failure depending on its review, costs are rising, and a good sentiment analysis model needs to be developed, that classifies moviereviews. Machine learning methods use ML algorithms to carry out sentiment analysis as a standard classification problem using syntactic and language characteristics. There are some methods of machine learning used for sentiment analysis in this paper. Most of the sentiment analysis is performed using SVM, RF, ANN, and NB, Algorithms of DT, BN, & KNN.
Author's Name: Khaily Mohammed Shah, Sathyam Pandey
Abstract— A human brain responds at a much faster rate to images and the information it contains. An image is considered as proof of past events that have occurred, but in today's world where editing tools are made available so easily tampering of images and hiding the original content has become too mainstream. The identification of these tampered images is very important as images are considered as vital sources of information in crime investigation and in various other fields. The image forgery detection techniques check the credibility of the image. Various research has been carried out in dealing with image forgery and tampering detection techniques, this paper highlights various the type of forgery and how they can be detected using various techniques. The fusion of various algorithms so that a complete reliable type of algorithm can be developed to deal mainly with copy-move and image splicing forgery. The copy-move and image splicing method are main focus of this paper.
Author's Name: Tulshiram Bansod , Monali Shivram
Abstract— With the quick rise in living standards, people's shopping passion grew, and their desire for clothing grew as well. A growing number of people are interested in fashion these days. However, when confronted with a large number of garments, consumers are forced to try them on multiple times, which takes time and energy. As a result of the suggested Fashion Recommendation System, a variety of online fashion businesses and web applications allow buyers to view collages of stylish items that look nice together. Clients and sellers benefit from such recommendations. On the one hand, customers can make smarter shopping decisions and discover new articles of clothes that complement one other. Complex outfit recommendations, on the other hand, assist vendors in selling more products, which has an impact on their business. FashionNet is made up of two parts: a feature network for extracting features and a matching network for calculating compatibility. A deep convolutional network is used to achieve the former. For the latter, a multi-layer completely connected network topology is used. For FashionNet, you must create and compare three different architectures. To achieve individualised recommendations, a two-stage training technique was created.
Author's Name:Dipayan Kumar Ghosh,Tanmay Sharma,Rajeev Khatri,Rajat Sharma,Ramandeep Singh
Abstract— This Personality classification is a field of research that focuses on categorizing individuals based on their behavioral patterns, preferences, and traits. Leveraging advancements in psychology, machine learning, and natural language processing, personality classification enables deeper insights into human behavior. This study explores methodologies for personality classification using various models, including the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism). Data is analyzed from text, speech, or social media interactions to identify patterns that reflect individual personality types. The goal is to improve applications in recruitment, personalized marketing, mental health assessments, and social network analysis. Emphasis is placed on ethical considerations, including data privacy and the potential for bias. Findings demonstrate how integrating computational tools with psychological theories can enhance the accuracy and reliability of personality classification systems. Personality classification involves categorizing individuals based on traits like openness, extraversion, and agreeableness, often using models like the Big Five. By analyzing text, speech, or behavior through machine learning, it supports applications in recruitment, marketing, and mental health. This approach combines psychology and technology, emphasizing accuracy, ethical considerations, and data privacy.
Author's Name: Aditya Swami, shish Kumar
Abstract— By this research, we want to display the key factors of how effective blogging as technology is. We collected information curated by several researchers on the same for understanding their point of view as well. By doing this we found out what makes blogging the best way of sharing information online. We also analyzed the technological aspect of modern-day blogging which includes modern technologies being used, privacy rules and control as well as data analytics. By these approaches, we showed how blogging is not only the best medium for sharing information but can also help in other fields as well like marketing, education, data analysis, community development. With this research, we also wanted to highlight the downsides of using blogging or microblogging.
Author's Name:J. R. Arun Kumar , Aastha Sharma, Chirag Gupta, Karan Chawla, Garvit Kirodiwal
Abstract— This Personality classification is a field of research that focuses on categorizing individuals based on their behavioral patterns, preferences, and traits. Leveraging advancements in psychology, machine learning, and natural language processing, personality classification enables deeper insights into human behavior. This study explores methodologies for personality classification using various models, including the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism). Data is analyzed from text, speech, or social media interactions to identify patterns that reflect individual personality types. The goal is to improve applications in recruitment, personalized marketing, mental health assessments, and social network analysis. Emphasis is placed on ethical considerations, including data privacy and the potential for bias. Findings demonstrate how integrating computational tools with psychological theories can enhance the accuracy and reliability of personality classification systems. Personality classification involves categorizing individuals based on traits like openness, extraversion, and agreeableness, often using models like the Big Five. By analyzing text, speech, or behavior through machine learning, it supports applications in recruitment, marketing, and mental health. This approach combines psychology and technology, emphasizing accuracy, ethical considerations, and data privacy.
Author's Name: Shubham Patil, Saurav Daware, Ameya Bhagat
Abstract— This paper is aimed at developing an Online College Management System that is of importance to the educational institute or college. This system is named College ERP using MERN stack. This system may be used to monitor college students and their various activities. This application is being developed for an engineering college to maintain and facilitate ease of access to information. For this the users must be registered with the system. College ERP is an Internet based application that aims at providing information to all levels of management within an organization. This system is used as an information management system for the college. For a given student and staff (technical and nontechnical) can access the system to either upload and access some information from the database.
Author's Name:Dipayan Kumar Gosh, Khushi Jangid, Paridhi Vijay, Anjali Sharma
Abstract— This In an era of overwhelming digital content, choosing the right movie has become increasingly difficult for users. Traditional recommendation systems, primarily based on collaborative filtering or content-based filtering, often fail to capture the emotional nuance and real-time trends reflected in user-generated reviews. This project proposes a Sentiment AnalysisBased Movie Recommendation System that enhances the accuracy and personalization of movie suggestions by analysing public sentiment from user reviews. The system leverages Natural Language Processing (NLP) techniques to process and classify user sentiments into positive, negative, or neutral categories. Using a dataset containing movie details and corresponding user reviews, the system performs text pre-processing (tokenization, stop word removal, stemming/lemmatization) followed by sentiment scoring using machine learning or deep learning models like Logistic Regression, Naive Bayes, or LSTM-based neural networks. Once sentiment scores are computed, movies are ranked and recommended to users based on aggregated sentiment analysis and personal preferences such as genre, language, and release year. This hybrid approach allows the recommendation system to not only understand what users like based on ratings but also why they like it, offering a more human-centered and emotion-aware movie discovery experience. The final product is a web-based application with a clean and intuitive user interface, allowing users to input preferences, browse movie suggestions, and see why a movie is recommended through sentiment-based visual insights. The system demonstrates how integrating sentiment analysis with recommender systems can significantly improve user satisfaction, engagement, and trust.
Author's Name: Aditi Shedge , Shaily Shah
Abstract— Air pollution has become a major issue in large cities because increasing traffic, industrialization and it becomes more difficult to manage due to its hazardous effects on the human health and many air pollution-triggering factors. This paper puts forth a machine learning approach to evaluate the accuracy and potential of such mobile generated information for prediction of air pollution. Temperature, wind, humidity play a vital role in influencing the pollution dispersion and accumulation, majorly influencing the prediction of pollution levels. Thus, this paper includes the atmospheric condition information registered throughout the study period in order to understand the influence of these factors on air pollution monitoring. Data driven modelling is an efficient way of extracting valuable information from generated data sets, however it is less efficient when the data is incomplete or contains inaccuracies. This modelling approach has true potential for real time operations because it can detect non-linear spatial relationships between sensing units and could aggregate results for regional investigation. Neural networks comparatively showed good capability in air quality prediction than support vector regression.
Author's Name:Arun Kumar, Vanshita Jain, Kritika Kumari, Sarthak Vashishtha, Nikhil Kirodiwal, Shruti,
Abstract— This paper there are number of people who are relocating from their native place to some other place for their jobs. Their daily life balance gets disturbed. No proper access to home like foods, which can lead to their health deterioration. They unwantedly depend on the hotel and restaurant for their survival. So to overcome this problem The Food Station is a perfect platform for getting homely foods. The platform connects tenants, who seek affordable and healthy food options, with housewives and home cooks, who can offer their culinary services from the comfort of their own kitchens. Built using the MERN (MongoDB, Express.js, React.js, Node.js) stack, the website provides a seamless user experience, enabling tenants to browse, order, and rate meals, while housewives can manage their menus, set prices, and track orders. The platform emphasizes community-driven food services, fostering local connections and promoting homebased entrepreneurship. The ML system offers personalized meal recommendations to users based on their preferences, past orders, and ratings, improving customer satisfaction and helping home cooks optimize their offerings.
Author's Name: Rarishma Kaushik, Rahesh Parmar
Abstract— Air pollution and its harm to human health has become a serious problem in many cities around the world. In recent years, research interests in measuring and predicting the quality of air around people has spiked. Since the Internet of things has been widely used in different domains to improve the quality for people by connecting multiple sensors. In this work an IOT based air pollution monitoring with prediction system is proposed. The internet of Things is a action interrelated computing devices that are given unique identifiers and the capability of exchange information over a system without anticipating that human to human or human to machine communication. The deep learning algorithm approach is to evaluate the accuracy for the prediction of air pollution. The main objective of the project is used to predict the air Quality. The large dataset works with LSTM for better air quality prediction. The prediction accuracy of air quality with LSTM, the evaluation indicator Root means square error is chosen to measure performance.
Author's Name:Dipayan Kumar Ghosh, Priyansh Agarwal, Tushar Dixit, Ritik Saini, Rishi Gupta,Vansh Gill
Abstract— This paper This Most people tend to live a long and healthy life, but people are busy in their day-to-day life and it is not possible for everyone to visit doctors for minor symptoms of a disease. Many people do not know about medicines and to visit a doctor and consult for minor symptoms for medicines is a time consuming process. AI and machine learning like emerging technology can help us to create a recommended system that will prescribe medicine and this system can accurately predict a medicine to use. In this paper proposes the medicine recommendation system which will predict disease and medicine according to symptoms entered by patients/users. This paper presents a novel medical recommendation system utilizing deep learning techniques. The system employs a recurrent neural network (RNN) architecture to analyze longitudinal patient data, including medical history, vital signs, and medication records. The RNN model learns complex temporal patterns to predict future health states and recommend proactive interventions. Evaluation on a real-world dataset demonstrates the system's ability to accurately forecast health events and provide timely, personalized recommendations.
Author's Name: Dipayan Kumar Ghosh, Rahul Soni, Shivani, Yana Sharma, Kunal Tiwari, Riya Khandelwal
Abstract— This Students today often struggle with productivity due to the scattered nature of digital tools required for managing study schedules, tracking tasks, taking notes, and summarizing learning content. EduMate is an AI-powered all-in-one study companion designed to address these challenges by integrating essential learning tools into a unified platform. The system includes a Pomodoro Timer for focused study sessions, a Smart To-Do List to manage tasks efficiently, and a Note-Taking application for organized information storage. Additionally, EduMate integrates AI-based features such as a PDF Summarizer, Chat with PDF, and a Quiz Generator to help students interact with study materials in smarter ways. These AI tools accept user-uploaded PDFs or text inputs and provide summarized content or automatically generated quizzes for enhanced understanding. Developed using Python, Flask, and modern web technologies, EduMate creates a seamless and user-friendly environment for students to improve their learning productivity. This journal presents the system architecture, development process, implementation details, and key results from the working prototype of EduMate.
Author's Name: Bahubali A. Kaipale, V.R. Naik, Santosh
Abstract— In centrifugal pump, priming function plays a vital role. Priming means to remove the air from pump and its piping systems & to create vacuum so that pumping liquid will flood inside the pump. When water level is positive means above the center line of pump then priming is not required but in case of negative water level means water level is below the pump center line, priming is required. There are some conventional methods exist like use of foot valve, use of priming pots etc. which requires more time & human efforts during every start of pump which is not possible. To avoid the more initial time & efforts, some self-priming systems & mechanism
Author's Name:Nigamh Kumar Tiwari, Akhilesh Pandey
Abstract— Our economy is extremely relying on agriculture production. One of the recent research topics is recognition, classification and detection of diseases from the leaf image of a plant. Plants are affected by various kinds of diseases, which causes great harm to the agricultural plant production. Today artificial intelligence and machine learning techniques is capable enough to detect and identify the plant disease. One of the biggest advantages of using AI and ML in agriculture is to reduce the hectic work of constant monitoring of crops field spread over hundreds of acres. Machine learning algorithms detect diseases in early stages as soon as they emerge on the plant surface. The aim of this research is to develop a software system that mechanically finds and classify diseases. The techniques like “image acquisition, pre-processing, segmentation, extraction and classification” are used in it. The leaves picture is captured to detect the plant disease. Thus, use of image processing techniques to detect and classify diseases in agricultural application is useful
