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Item Cancer care : Predicting the likelihood of cancer(NHCE, 2023) Abhishek Esapnor 1NH20IS006 Gagan Rao P 1NH20IS051 Varshitha S 1NH20IS182The goal of this research is to create a predictive model that analyzes a person's genetic makeup and forecasts their risk of acquiring cancer using deep learning algorithms. Through analysis of a person's genetic makeup, the discipline of genomics has demonstrated enormous potential in improving cancer detection and therapy. In order to reduce the amount of human intervention, our method compares several deep learning models that don't require feature engineering and gathers an original dataset.Item PRO SHEILD PROTECT(NHCE, 2023) Vyshnavi .B 1NH20IS029 C.Raghu 1NH20IS032 P.Manikanta Kiran 1NH20IS103In modern computerized world android application plays an imperative role. Android platform because of open-source trademark also, Google backing has the biggest worldwide portion of the overall industry. Being the world's most well-known working framework, it has drawn the attractions of digital hackers working especially through the wide circulation of malevolent applicationsItem “Visionary Diagnosis: Exploring Cardiovascular Links in Retinal Imagery”(NHCE, 2023) Diwakar R V 1NH20IS046 Sravan Kumar T 1NH20IS181 B Jaffer Sadiq 1NH20IS194Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide. Early detectionand accurate diagnosis of CVDs are crucial for effective intervention and improved patientoutcomes. Retinal imaging has emerged as a non-invasive and cost-effective technique for CVD prediction. This study aims to develop a deep learning model using convolutionalneural networks (CNNs) and MobileNet architecture to predict CVDs from retinal images. The proposed model leverages the capabilities of CNNs to automatically learn relevant featuresfromretinal images and MobileNet'slightweight design for efficient deployment.A large dataset ofretinal images, including healthy individuals and CVD patients, is utilizedfor model training and evaluation.Item ChemCheck - An IoT based Device for Chemical Detection on Fruits and Vegetables(NHCE, 2023) Aishwarya D 1NH20IS008 Chandana Yuktha. S 1NH20IS030 Harshitha M1NH20IS058 Mamtha S 1NH20IS081Consumers’ growing concern for the safety of fruits and vegetables is driven by the potential health risks posed by harmful chemical residues, such as pesticides and heavy metals. Theproblem lies in the absence of accessible, real-time, and cost-effective solutions for individualsto assess the safety and quality of the produce they purchase. Existing methods, often limitedtoexpensive laboratory tests, are not practical for the average consumer. As a result, individualslack the means to make informed decisions about the safety of their food. This project aimstobridge this gap by developing a portable and user-friendly device that swiftly scans and analyzesfruits and vegetables, providing consumers with vital information on the safety of their producechoices. With the help of IoT sensors and embedded C programming, the project is beingbuilt.Item Yuj : Solace Amidst Distress(NHCE, 2023) Sachin Mengji 1NH20IS142 Satyajeet Kumar 1NH20IS150 Shashi Kant Kumar S 1NH20IS152 Shreyas N 1NH20IS160"Yuj: Solace Amidst Distress" is a comprehensive software designed to promote holistic well being through the ancient wisdom of yoga. The Sanskrit word 'Yuj,' meaning yoga, encapsulates the essence of this project, which comprises four transformative modules aimed at fostering physical, mental, and emotional balance. The "Yoga Postures" module serves as a foundational pillar, offering animated videos that guide users through basic yoga postures. This module is further tailored to address specific health concerns, including Orthopedic, Diabetes and BP, Oncology, and Women's Health, providing targeted practices for diverse needs.Item Smart Gas Leakage Detector Bot(NHCE, 2023) Ramagiri1NH20IS128 T R Pramod 1NH21IS411G S Vikas H S1NH2IIS417As we all know, industrial security is a key concern in today's world. The number of accidents is rising every day, and we have seen several examples in our daily lives of accidents caused by flammable gases. We frequently hear about home cylinders exploding, which are used for residential purposes, transportation, and a variety of sectors. Many individuals have beenseriously hurt and others have died as a result of explosions in some cases. In addition to being facilitated, the world has become more vulnerable to big blunders and disasters as a result of newbreakthroughs and technology. Similarly, Liquefied In most homes, petroleum gas (LPG) is usedin the kitchen and for gas geysers or heaters in the winter. Similarly, companies employ it for variety of reasons, such as furnaces, boiling, and increasing output at a lower cost. The goal of this project is to useItem CREDIT CARD SCORE PREDICTION(NHCE, 2023) CHIRAG M D A RITESH D SHIVKUMAR GOUD P NITHINCREDIT CARD SCORE PREDICTIONItem Cardiovascular Disease Prediction using Machine Learning(NHCE, 2023) Abhinav Kumar 1NH20IS200 Md Adil Anwar Khan 1NH20IS086 Vishal Kumar 1NH20IS185Cardiovascular diseases (CVDs) remain a leading cause of mortality worldwide. Early detection and timely intervention are crucial for preventing adverse outcomes. This research explores the application of machine learning (ML) techniques for the prediction of cardiovascular diseases, leveraging a dataset comprising diverse clinical parameters.Item STANFORD RIBONANZA FOLDING(NHCE, 2023) PANDURANGA A J 1NH20IS107 TEJAS MONDEERI 1NH20IS179 SWATI RAVISHYAM 1NH20IS191Understanding the intricate relationship between RNA structure and function is a fundamental challenge in computational biology. This project presents a novel approach that harnesses the power of transformer based modelsto predict RNA structures and incorporates experimental data, such as chemical mapping profiles, for enhanced accuracy and biological relevance.Item “MastroWorkforce – Securing Workforce Efficiency with HCM Excellence”(NHCE, 2023) Rudwaj SK 1NH20IS139 Sakshith C Billava 1NH20IS146 Sudarshan B1NH20IS169 Shivaraj CM 1NH20IS155In the dynamic and security-sensitive landscape of modern security agencies, efficient management of human capital is paramount. This abstract introduces a cuttingedge Human Capital Management (HCM) software tailored specifically for security agencies. This software offers a comprehensive suite of features, encompassing employee data management, attendance tracking, payroll management, duty scheduling, and work hour monitoring. Data security remains paramount, and the application addresses this by integrating a robust in-house authentication systemItem Votereum- Blockchain Based Secure Voting System(NHCE, 2023) Nitish Veni INH20IS101 Pranith Kumar M INH201S116 Manoj H INH20ISO83 Hrishikesh Purohit INH201S123This project aims to revolutionize traditional voting systems by implementing blockchain technology to enhance the security, transparency, and accessibility of elections. Through the use of decentralized and immutable ledgers, blockchain-based voting systems offer a tamperproof and auditable record of votes, ensuring the integrity of the electoral process. The project seeks to address concerns regarding electoral fraud, tampering, and manipulation by leveraging the transparency and cryptographic security of blockchain technologyItem Dam Montoring And Management System Using IoT(NHCE, 2023) AmeerN 1NH211S402 MohammedSayeed INH21IS406 Nahim A INH21IS407 Ramesh N 1NH21IS413In the realm of modern infrastructure, the integration of Internet of Things (IoT) technology has ushered in an era of unprecedented efficiency and precision. Nowhere is this more evident than in the domain of dam monitoring and management.Item CATTLE DISEASE PREDICTION USING MACHINE LEARNING(NHCE, 2023) M Parnika -1NH20IS082 Suraj Antony Raj A -1NH20IS173 T Pranay -1NH20IS176 K Harinath Reddy -1NH20IS193With the rapid development of big data and artificial intelligence, data analysis and mining are becoming more and more widely used in animal husbandry. In this system, a large number of multi-source cattle electronic medical record data are collected and used the data analysis and mining technology to realize the intelligent diagnosis system for cattle diseasesItem Urbanflow –Traffic Management System Using IOT(NHCE, 2024) P Bhargav Reddy1NH20IS120, Prajwal A S1NH20IS112, Praveen M1NH20IS119 Raghavendra S1NH20IS126Urbanflow –Traffic Management System Using IOTItem Deep Learning Agent For Traffic Signal Contro(NHCE, 2023) Praneeth Sanapala 1NH201S114 Punith C 1NH201S122 RahulG 1NH201S127 Rohith Rajendran 1NH201S136Getting stuck in traffic is a big headache in cities, causing delays and making everyone grumpy. Regular traffic lights try to help, but they have limits. The smart traffic lights, supercharged with Artificial Intelligence and Machine Learning, ready to transform how we get around. We will dive into the implementation of these intelligent systems, highlighting their benefits such as optimized traffic flow, reduced travel times, and improved fuel efficiency, all driven by the adaptive capabilities of AI and ML algorithms. Our project will address the hurdles of seamlessly integrating AI and ML into existing urban infrastructure, touching on issues such as data security and the coordination of diverse transportation modes.Item “PERCEPTI ALARM: A Beacon of Safety and Autonomy Leveraging OCR and ML”(NHCE, 2023) Jashwanth D S 1NH20IS065 Jayam Surendra Anil 1NH20IS066 K L Tejas 1NH20IS068Percepti-Alarm is a groundbreaking endeavor aimed at revolutionizing the lives of the visually impaired. It introduces a transformative solution by integrating a high-tech camera onto the conventional white cane, offering real-time environmental scanning and object recognition capabilities.Item Water Quality Monitoring System(NHCE, 2023) Khooshi Dutta1NH20IS073 Ritika Patil1NH20IS133 Presha Stephen1NH20IS121 S Shivani1NH20IS141Water Quality Monitoring SystemItem Micro Organism Image Recognition and Disease Prediction Based on DL(NHCE, 2023) Aakash.B 1NH20IS002 Saran.B.V.N 1NH20IS028 Vishnu.C 1NH20IS033 Abhi.K 1NH20IS067Despite tremendous recent interest, the application of deep learning in microbiology has still not reached its full potential. To tackle the challenges faced by human-operated microscopy, deep-learning-based methods have been proposed for microscopic image analysis of a wide range of microorganisms, including viruses, bacteria, fungi, and parasites. We believe that deep-learning technology-based systems will be on the front line of monitoring and investigation of microorganisms. Hence, here we are proposing a model that which can classify and detects the type of organism using the CNN based transfer learning algorithm of deep learning. Once after the detection of the organism, the spread of diseases are also predicted from the detected output.Item Online Analysis of Ingredient Safety, Leveraging OCR and Machine Learning for Enhanced Consumer Product Safety(NHCE, 2023) Adithya D 1NH20IS007 Dhyan D Kedilaya 1NH20IS044 Shreyas S Gondkar 1NH20IS161 Sourabh Halhalli 1NH20IS168Navigating the complex world of product ingredients can be a daunting task for healthconscious consumers. Often, ingredient labels are opaque and filled with jargon, hindering informed decision-making about product safetyItem DETECTION OF POVERTY USING DEEP LEARNING(NHCE, 2023) HARI KRISHNA M 1NH20IS054 C SAI SOURABH 1NH20IS034 BHARGAV M 1NH20IS023Poverty is always a big problem for any country, which needs to be taken care of, countries spend lot money and resources for eradicating the poverty. To eradicate we need to have a data about the regions which are under poverty, so that the money which has been allocated for poverty eradication goes to right region, To collect the data we need to spend a lot of money and human resource, to minimize that we propose a system which utilizes the satellite images to detect the necessary regions economic levels so that we determine if the region is under poverty or not ,we will be using 2 models, where one model is a convolutional neural network which feed with satellite images from which it would identifies the economic parameters and send the results to another model which would identify the relationship between these parameters and predict the economic level of that region.
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