Robotic arm to pick and place
Robotics has emerged as a more important area in the current technological era. When compared to human labor, robots are more precise. This study presents a method for replicating a human arm by using a smartphone to operate it. A robotic arm is a mechanical device that has been programmed to carry out certain activities. This paper describes the creation of a robotic arm that can pick and place objects and is controlled through Bluetooth. The Android application serves as a transmitter, sending commands to the receiver to control the robotic arm’s movement. The Bluetooth module establishes a connection between the phone and the robotic arm. After linking the robotic arm with the smartphone’s Bluetooth, different moments of the robotic arm may be controlled with a single tap on the android application.
Published by: Sai Krishna Aitha, Y. Deepthi Reddy, P. Mani Kumar
Author: Sai Krishna Aitha
Paper ID: V7I4-1491
Paper Status: published
Published: July 24, 2021
COVID-19 cases detection using deep neural networks with X-Ray images
Mysterious sickness with flu-like signs became first located in Wuhan town of China. This sickness became resulting from extreme acute respiration syndrome coronavirus 2 (SARSCoV-2). Covid-19 introduced havoc internationally affecting each public fitness and the economy globally. And inflicting the biggest worldwide recession because of the Great Depression. With the fundamental replica variety (R0) ranging from 2-2.5, it's far vital to become aware of the effective instances and deal with them. There is a demand for auxiliary diagnostic tools. The information amassed the usage of the radiology imaging strategies offers exceptional data about the COVID-19 virus. Radiological photographs and superior synthetic intelligence(AI) strategies can work withinside the choice of a brief analysis of the infection. In this we examine, an automated version for COVID-19 detection the usage of chest X-ray photographs is rendered. The rendered version is advanced to cater stable diagnostics for binary category and multi-class category. Our version gave a category accuracy of 98.08 percentage for binary classes and 87.02 percentage for multi-magnificence instances. In our investigation, the Darknet version was used as a classifier for a YOLO (you only look once) real-time object identification system. We are using VGG-sixteen architecture and added filtering on every layer. Our version can be engaged to support radiologists withinside the preliminary screening, and also can be hired through cloud to immediately screen patients.
Published by: Dr. S. Usha, Anjali Rani, Aparna Singh, Khushi Mathur
Author: Dr. S. Usha
Paper ID: V7I4-1493
Paper Status: published
Published: July 24, 2021
House Price Prediction using Machine Learning
Machine learning plays a major role in past years in image detection, spam reorganization, normal speech command, product recommendation, and medical diagnosis. Present machine learning algorithm helps in enhancing security alerts, ensuring public safety, and improve medical enhancements. Machine learning system also provides better customer service and safer automobile systems. Designing an effective machine learning model for the prediction of regression and classification problems is a tedious endeavor. Significant time and expertise are needed to customize the model for a specific problem. A significant way to reduce the complicated design is by using Automated Machine Learning (AML) that can intelligently optimize the best pipeline suitable for a problem or dataset. This study utilizes machine learning algorithms as a research method that develops housing price-prediction models. In that point, a housing cost prediction model to support a house vendor or a real estate agent for better information based on the valuation of the house is recommended.
Published by: Mayur Manohar Patil, Bhushan Ramkrushna Upasani, Anup Sanjay Patil, Janhavi Kailas Chaudhari, Priti R. Sharma
Author: Mayur Manohar Patil
Paper ID: V7I4-1498
Paper Status: published
Published: July 24, 2021
Campus Buddy
Every institute needs a place where everyone of their institute can communicate with each other so that while sharing some important information/data no one should be left behind. Thus, Making a web application and stand-alone application which can be used by every member of that education institute to get updated about institute activity and can share his/her opinion if required. Thus, binding everyone under one platform gives institute more boost and coordination among its members. Our Automation is accomplished through the medium of a Website and smart phone application. The front end of this system is built with Bootstrap. Bootstrap is the most popular HTML, CSS and JS framework which scales the website and application with a single code base, from phones to tablets to desktops with CSS media queries. The back end of this system is built with firebase. Fast, flexible and pragmatic, JAVA SCRIPT is a server scripting language that empowers some of the most popular websites. FIREBASE is the most popular database system used with JavaScript for storing information categorically. The whole project is also featured with the firebase services such as authentication, database, storage, hosting , messaging, etc.
Published by: Biswajit Sahoo, Bhagat Singh, Mishra Anupam Mukundkumar, Atul Singh, Abhijit Das
Author: Biswajit Sahoo
Paper ID: V7I4-1506
Paper Status: published
Published: July 24, 2021
Design and fabrication of jig for angular drilling
In drilling process the tool and work piece both are perpendicular to each other means the drilling axis parallel and horizontal to machine axis, but in Vertical machine centre (VMC) the radial and angular drilling is easy task but in small machine shop and workshop we can not afford the VMC machines. For that we are trying to design and fabrication a fixture for angular drilling. This proposed method has to design and fabricate the Multipurpose Jig and Fixture, for that component Which has been to reduce the manufacturing cycle time
Published by: Atharv Ajay Chikurdekar, Swaraj Suraj Pawar, Yash Sanjay Khulkarni, Shubham Dattatraya Mali, Kalyani Sudhir Kulkarni
Author: Atharv Ajay Chikurdekar
Paper ID: V7I4-1348
Paper Status: published
Published: July 23, 2021
Analysis of bank telemarketing data using Microsoft Azure machine learning
predict customers' responses to future marketing campaigns & increase the effectiveness of the bank's telemarketing campaign Here in this paper we will empower the bank to foster a more granular comprehension of its client base, foresee clients' reaction to its selling crusade and build up an objective client profile for future advertising plans. By investigating client highlights, like socioeconomics and exchange history, the bank will actually want to anticipate client saving practices and recognize which sort of clients is bound to set aside term installments. The bank would then be able to zero in its promoting endeavors on those clients. This won't just permit the bank to get stores all the more successfully yet in addition increment consumer loyalty by decreasing unwanted ads for specific clients.
Published by: Jaswanth Kankanala, Sravya Sri V., Venkatesh narahari
Author: Jaswanth Kankanala
Paper ID: V7I4-1484
Paper Status: published
Published: July 23, 2021
