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Efficient and reliable public road transportation systems are essential for ensuring accessible and sustainable mobility for the vast population of India. With a rapidly growing population and increasing urbanization, India faces significant challenges in providing affordable, safe, and efficient road transportation services. This paper aims to analyze the key challenges and explore opportunities for improvement in the public road transportation sector in India. As the paper begins, it emphasizes the importance of public road transportation for both urban and rural populations. In addition to facilitating economic growth, it provides essential services. Despite this, India's public road transportation system faces several challenges. Furthermore, the lack of reliable and standardized public transportation is a major concern. Private buses and unregulated informal transport operators dominate the road transportation sector, leading to issues of overcrowding, irregular schedules, and inadequate passenger comfort and safety measures. To address these challenges and improve public road transportation in India, the paper explores potential opportunities and solutions. It highlights the need for increased investment in road infrastructure development, including the expansion of road networks, improved road design, and enhanced traffic management systems. Additionally, the integration of technology, such as intelligent transportation systems and realtime information systems, can optimize operations and enhance the overall passenger experience. [ABSTRACT FROM AUTHOR]

The objective of paper is to study a deep learning strategy for recognizing Indian Sign Language (ISL) using convolutional neural networks CNN. Sign language recognition has become a crucial tool for enhancing communication and accessibility for the deaf in India. ISL is a visual-gestural language used by the deaf population in India, and it is a visual-gestural language used by the deaf community in India. Gesture based communication Application is a characteristic language that involves various methods for articulation for correspondence in day-to-day existence. This paper presents a Programmed interpretation framework for token of manual letters in order in English communication via gestures. It manages pictures of uncovered hands, which permits the client to cooperate with the framework in a characteristic manner. In proposed system a deep learning model using CNN with ISL (Indian Sign Language) Dataset is used. The model consists of preprocessing the dataset to extract features from the image, then train a CNN to recognize the signs and gestures with audio. Experimental results show that the proposed approach is capable of achieving accuracy in recognizing ISL signs and gestures with accuracy of 0.868, recall 0.856, precision 0.863, and F-score is 0.884 respectively. [ABSTRACT FROM AUTHOR]

The die casting industry plays a vital role in the manufacturing sector and imagining our life without die casting sector is now next to impossible. In the last 2 decades, one more such technology is revolutionizing manufacturing and prototyping, that is 3D printing. 3D printing is much easier and involves fewer processes in comparison to die casting. This can make it a potential alternative to die casting in the future. Die casting and 3D printing, both in their own way, are unique and have different use cases. It is important to see what both of these technologies will look like in future and how they will revolutionize the manufacturing sector. Feasibility, Industry size, productivity and accuracy of both of these processes will also play a very important role in influencing the market. This paper compares both the technologies with help of a case study of producing 100000 “Frying pans” using both of them and analyzes Feasibility, Industry size, productivity and accuracy to prove monopolized supremacy of die casting over 3D printing. There are various ways in which 3D printing can evolve as a competition to Die casting industry. This paper at the end suggests some solutions to counter the challenges faced by 3D printing technology in order to evolve in Indian Markets. [ABSTRACT FROM AUTHOR]

The average annual income of farmers in India is well below the poverty line, primarily due to off-season agriculture and a lack of awareness about optimal farming techniques and crop management. This research paper presents an AI-based web application designed to address these challenges and improve farmers' financial and mental well-being. Our solution, comprised of a farming tools leverage system and a collaborative farming forum, empowers farmers with the knowledge and tools needed to make informed decisions and increase their income. The system leverages MongoDB, asynchronous calling, and Fast API for efficient data management and real-time interactions. AI/ML services assist with crop recommendations, crop disease detection, and price predictions. Load balancing ensures optimal performance, and Pusher JS enables real-time communication. Billing services and a dashboard provide income insights, while geographic data enhances machine learning recommendations. In conclusion, this research contributes to alleviating poverty and enhancing the livelihoods of farmers in India by providing a comprehensive solution to the challenges they face. [ABSTRACT FROM AUTHOR]

The Indian solid waste management sector is experiencing fast growth and transition as a result of rising urbanization and industrial activity. This research study examines the landscape of solid waste management in India, focusing on the informal sector's involvement, market size, and trends. It also looks into the possibility of creating an online solid waste marketplace with a progressive web app (PWA) with the goal of optimizing waste management processes, increasing resource efficiency, and contributing to environmental sustainability. The purpose of this study is to create a new waste management system that uses the YOLO v7 item recognition model andThe project concentrated on crafting design prototypes for a progressive web app (PWA) and an administrative web interface for a solid waste marketplace in India. Utilizing Figma, these designs aim to streamline waste management processes, engage users effectively, and advocate for recycling initiatives. This effort signifies a pivotal move towards closing the gap in India's waste management infrastructure. It highlights technology's role in promoting environmental sustainability and responsible waste management practices nationwide. [ABSTRACT FROM AUTHOR]

Pregnancy and fetus development is an incredibly intricate biological process that can go wrong when the health of fetus or the mother gets worse. Currently, India has the highest number of stillbirths, with an estimated 5,92,100 deaths per year, and a WHO estimated rate of 22 per 1000 total births. Cardiotocography is one procedure used to check whether the fetus is growing as expected. This diagnostic procedure measures the mother's uterine contractions and the fetus' heartbeat, usually in the third trimester of pregnancy when the fetus heart is fully developed. This paper aims to classify the results into one of three states (physiological, suspicious or abnormal) based on cardiotocographic data using machine learning algorithms and compare the accuracies of different ML classification models such as logistic regression, k-nearest neighbor, decision tree, random forest classifier and support vector machine. [ABSTRACT FROM AUTHOR]

In this paper, the Advaya Bot - Radiologist assistant robot development & its usage in healthcare applications is presented. The final year project under-taken by us consists of the designing & developing of a bot that can assist healthcare professionals, specifically in the Department of Radiology. It is a growing concern among the community of radiologists that radiation exposure, even under protocol scenarios, is causing harm to them in the form of cancers, tumors, cataracts, dry eye syndrome, etc. Also, in departments like that of Ultra Sonography imaging, the manual use of a transducer is something not looked forward to by the patients. We aim to build a bot that can reduce radiation exposure, workload, and uncomfortable interactions for the doctors in the department of radiology imaging. The use of such bots is strictly domain specific. For the purpose of our final project, we have chosen the domain to be that of Ultrasonography (USG). We aim at eliminating the manual use of the transducer and replacing it with a bot. The bot shall be capable of greeting the patient and adjusting the location of the end-effector with the help of a radiologist or specialist from a distance. The end edge of the bot will also be capable of placing the transducer with the required pressure on the required area of the patient’s body. In developing countries like India, the ratio of doctors to the number of patients is very low. We aim to unburden healthcare professionals and free them from harmful working conditions. The project undertaken represents the main project of the seventh semester by Electronics & Communication Engineering students, conducted under the guidance and supervision of faculty advisors. [ABSTRACT FROM AUTHOR]

Road crossing or at road side stray animals like cows and buffalos are usually observed in India. Such animals creates critical situations on roadways due to the collision. According to data obtained from the veterinary department of Nagpur municipal corporation approximately 3,127 cattle were injured and at least 30% of them died immediately and after a few days of hospitalization. This paper showcase a solar powered deep learning and IoT enabled early warning system which could detect the stray animals and send an alerts to the vehicles on road. The IoT cloud platform and dashboard delivers the information of accident prone zone. The trained stray animal detection model in the present system could predict 86% to 90% true positive results with 91% accuracy on real world camera feed. The 433 Mhz RF transmitter in the system is capable to send alert up to 110m. [ABSTRACT FROM AUTHOR]

Due to the increase in technology and the evolution of computers, speech recognition technology plays a vital role in our daily lives. Communicating with the computer through speech is more feasible than communicating through text. Speech recognition is the process of conversion of human speech to readable text to perform various operations. India has the most amazing diverse, multilingual community. Currently, there are 22 recognized languages with 12 scripts in the constitution. On the other hand, 1900+ dialects are divided into four language groups. This literature review aims to comprehensively analyse the automatic speech recognition system based on its history, types, application and problems in existing systems. Furthermore, the state-of-art speech recognition approaches are examined to lead a comparative study. As a result of an extensive literature review, future research directions are highlighted in terms of practical and relevant methods. [ABSTRACT FROM AUTHOR]

Farmers, notably in India, face challenges such as inadequate expertise in crop selection and crop failures due to disease. Deep Learning's untapped potential in agriculture, limited by data quality and processing constraints, presents an opportunity for enhancement. The objective is to give an open-source online application is developed using Flask to aid farmers in informed decision-making. Utilize Precision Agriculture principles to recommend crops based on soil types, features, and data-driven insights to boost productivity. The various methods based on a machine learning-based ensemble model is employed to suggest suitable crops based on soil data, focusing on accuracy and efficiency. The outcome of the developed system shows promise in enhancing input-output efficiency, improving decision-making, and reducing unsuitable crop choices, thereby boosting agricultural productivity and positively impacting India's economy. This approach demonstrates practical potential in resolving farming challenges by leveraging machine learning for crop recommendations, potentially revolutionizing agriculture in India and beyond. [ABSTRACT FROM AUTHOR]