2023-24

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http://192.168.75.5:4000/handle/123456789/16223

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Browsing 2023-24 by Title

Now showing 1 - 20 of 47
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    Agripulse - Revolutioning Agriculture through Wireless Sensor Networks and Machine Learning
    (NHCE, 2023) Nikhil Kamate 1NH20IS094 Pinaki Sankar Matruprasad 1NH20IS109 Om Gawade 1NH21IS409 Vamsi Krishna Sai1NH20IS088
    The introduction of cutting-edge, intelligent medical equipment into the virtual doctor system is orchestrating a remarkable transformation within community healthcare. Research in the healthcare sector has unveiled promising developments in extending human lifespan. However, obtaining healthcare services in remote areas remains a formidable challenge as patients often have to endure long journeys for treatment
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    Arduino-Based Air Quality Monitoring Robot with ML Analysis
    (NHCE, 2023) SantoshReddy1NH20IS148 Yuktha S1NH20IS186 Darshini R1NH20IS040 Monisha R1NH20IS124
    As everyone is aware, many dangerous gasses are emitted from automobiles and industry, which can lead to a range of health issues such as lung cancer, asthma, and a range of heart-related complications, or even lead to premature death if the ambient pollution is severe
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    “Automated Navigation systems for job portals- A report on multilingualchatbots, resume builders and parsers”
    (NHCE, 2023) LISHA RANGANTH1NH20IS077 SHREERAKSHA P BHAT 1NH20IS158 RADHIKA AJITH1NH20IS125 SWATHI MENON 1NH20IS079
    In today's dynamic job market, which is susceptible to economic downturns and recessions, there'sapressing need for a central online platform that caters to professionals and non-professionalsalike. Gone are the days when job opportunities were confined to traditional sectors like medicineor engineering. Now, with the world going digital, having an online job portal has become essential.
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    Cancer care : Predicting the likelihood of cancer
    (NHCE, 2023) Abhishek Esapnor 1NH20IS006 Gagan Rao P 1NH20IS051 Varshitha S 1NH20IS182
    The 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.
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    Cardiovascular Disease Prediction using Machine Learning
    (NHCE, 2023) Abhinav Kumar 1NH20IS200 Md Adil Anwar Khan 1NH20IS086 Vishal Kumar 1NH20IS185
    Cardiovascular 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.
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    CATTLE DISEASE PREDICTION USING MACHINE LEARNING
    (NHCE, 2023) M Parnika -1NH20IS082 Suraj Antony Raj A -1NH20IS173 T Pranay -1NH20IS176 K Harinath Reddy -1NH20IS193
    With 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 diseases
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    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 1NH20IS081
    Consumers’ 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.
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    “Chronic Obstructive Pulmonary Disease Prediction System”
    (NHCE, 2023) Inchara K 1NH20IS064 Kondapalli Vyshnavi 1NH20IS075 Kusum V 1NH20IS076 Sabah Fatima 1NH17IS086
    Chronic obstructive pulmonary disease (COPD), is defined by a persistent restriction in airflow in the lungs and airways due to toxic gases such as tobacco smoke. COPD poses a threat to people's physical and mental health due to its high rate of illness, disability, and death. This disease is anticipated to be in third rank by 2030 as the world's leading cause of death.
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    CREDIT CARD SCORE PREDICTION
    (NHCE, 2023) CHIRAG M D A RITESH D SHIVKUMAR GOUD P NITHIN
    CREDIT CARD SCORE PREDICTION
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    Dam Montoring And Management System Using IoT
    (NHCE, 2023) AmeerN 1NH211S402 MohammedSayeed INH21IS406 Nahim A INH21IS407 Ramesh N 1NH21IS413
    In 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.
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    Deep Learning Agent For Traffic Signal Contro
    (NHCE, 2023) Praneeth Sanapala 1NH201S114 Punith C 1NH201S122 RahulG 1NH201S127 Rohith Rajendran 1NH201S136
    Getting 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.
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    DETECTION OF POVERTY USING DEEP LEARNING
    (NHCE, 2023) HARI KRISHNA M 1NH20IS054 C SAI SOURABH 1NH20IS034 BHARGAV M 1NH20IS023
    Poverty 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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    “Engine Locking System for Drunken Drivers”
    (NHCE, 2023) Anish Prasad Gupta 1NH20IS192 Tanusha P Hiredesai 1NH20IS177 Rohit Raj 1NH20IS135 Chayan Paikara 1NH20IS199
    Drowsy driving poses a significant risk to road safety, leading to numerous accidents, injuries, and fatalities worldwide. In response to this pressing issue, we present a novel drowsiness monitoring and accident detection system designed to mitigate the risks associated with driver fatigue. Leveraging infrared (IR) sensors integrated into the driver's eyewear, our system offers a non-intrusive and portable solution for real-time monitoring of eyelid movement, a key indicator of drowsiness.
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    FlexOS – The OS of the Future
    (NHCE, 2023) Chinmaya C B1NH20IS036 Kamboji Akhliesh1NH20IS070 Karthik E1NH20IS071 Saket Kumar 1NH20IS145
    On a computer or other device, an operating system offers a platformfor the use of otherapplications and programs. However, it might be difficult for those with physical disabilitiesto use their devices, which support the current OS. It becomes quite challenging for themtonavigate the screen without having access to a mouse pointer.
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    “Gesture Guided Interaction using CNN”
    (NHCE, 2023) Siddharth Singh 1NH20IS163 Yukthaa A Shreeniwas 1NH20IS187 Samit Mohan 1NH20IS147 Rishabh Preethan 1NH20IS131
    This research introduces an innovative Gesture Guided Model (GGM) designed to significantly enhance accuracy and efficiency in sign language interpretation. Hearing impaired people and the deaf community use sign language as their only means of communication.
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    Green House Monitoring System
    (NHCE, 2023) Harshitha Mahapatra1NH20IS057, Sharddha C K 1NH20IS157, Sukriti Sneha1NH20IS171, Vidhushi Shrivastava1NH20IS183
    Green House Monitoring System
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    “Harmony in Wild”
    (NHCE, 2023) M MOHAMED KHALID 1NH20IS080, ROHAN NAGARKATTE 1NH20IS134, MUHAMMED SHAREEF 1NH20IS090, LOKESH PRASAD 1NH20IS078
    Forests, one of the Earth's vital ecosystems, are grappling with significant challenges, including wildlife extinction, conflicts between animals and humans, and issues such as trespassing hunters, human-wildlife vehicle encounters, and pilgrims going missing due to animal attacks. These problems not only threaten biodiversity but also endanger human lives and livelihoods. Addressing these challenges promptly is of paramount importance. The major project is centered on providing a solution by monitoring the movements of humans and animals to prevent them from encroaching on each other's territories.
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    Hepatitis Detection: Leveraging Logistic Regression, SVM and Decision Trees for Early Detection
    (NHCE, 2023) Khushb00 INH20IS074 Manoj S INH20IS084 ManyaAdhikari INH201SO85 P Jaya Veer INH201S102
    Hepatitis is a global public health issue that affects individuals of all age groups. This project focuses on the early detection of hepatitis in both young and elderly populations using machine learning (ML) techniques. The study aims to address the unique challenges posed by hepatitis detection in these age groups and develop a robust and accurate diagnostic tool
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    Innovation For Inclusive Living Sign Language Translator
    (NHCE, 2023) Abu Talib 1NH21IS400S A Nashaath1NH20IS174 Aastha Priya1NH20IS004 Shamael Hashm1NH20IS151
    Innovation For Inclusive Living Sign Language Translator
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    “Insight Stream: A Real-Time Perspective on Classroom Environment”
    (NHCE, 2023) Abdul Manan1NH20IS005 Akshith Krishnan1NH20IS011 Arvinda H B1NH20IS018 Aslam Asgar Khan 1NH20IS020
    “Insight Stream: A Real-Time Perspective on Classroom Environment”