-22b9b34417bc6092a74-232f 20211126012837507 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 11 30 2021 11 1 10.35940/ijitee.11.1 https://www.ijitee.org/download/volume-11-issue-1/ B.Tech. Student, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai (Tamil Nadu), India. Abishek R Dr. D. Vaishali Assistant Professor, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai (Tamil Nadu), India. Adhitya Narayan R B.Tech. Student, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai (Tamil Nadu), India. Vignesh Sundar M B.Tech. Student, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai (Tamil Nadu), India. IoT has become an integrated part of our lives changing ways in which we operate our everyday appliances. In addition to making our home appliances smart, it has become a common trend for companies to adopt industry 4.0, which uses various sensors to monitor the equipment, machinery, and the work environment. We often come across multiple brands which make smart appliances but each brand comes with its separate mobile application for the appliance's operation. This requires us to switch between Apps to control these appliances if we at all remember which App controls which appliance. We intend to solve these two major inconveniences by creating a single mobile application that can control all these appliances using Augmented Reality technology. All we have to do is point our camera at the appliance that we need to operate and the App will display control options in real-time AR. This paper produces five important contributions: 1) An AR-based mobile application to control IoT devices and monitor the environment. 2) Implementing the mobile application using Unity 3D engine and Vuforia SDK. 3) Integrating a commercially available IoT device with the mobile application. 4) Integrating custom-made hardware IoT device with mobile application. 5) Integrating this combination to make our industries and homes smarter Keywords: 11 30 2021 35 40 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.A9598.1111121 https://www.ijitee.org/wp-content/uploads/papers/v11i1/A95981111121.pdf Department of Computer Science and Engineering, PES University, Bengaluru (Karnataka), India. Sandhya Vidyashankar Rakshit Vahi Department of Computer Science and Engineering, PES University, Bengaluru (Karnataka), India. Yash Karkhanis Department of Computer Science and Engineering, PES University, Bengaluru (Karnataka), India. Gowri Srinivasa Department of Computer Science and Engineering, PES University, Bengaluru (Karnataka), India. We present an automated, visual question answering based companion – VisQuelle - to facilitate elementary learning of word-object associations. In particular, we attempt to harness the power of machine learning models for object recognition and the understanding of combined processing of images and text data from visual-question answering to provide variety and nuance in the images associated with letters or words presented to the elementary learner. We incorporate elements such as gamification to motivate the learner by recording scores, errors, etc., to track the learner’s progress. Translation is also provided to reinforce word-object associations in the user’s native tongue, if the learner is using VisQuelle to learn a second language. 11 30 2021 41 49 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.A9599.1111121 https://www.ijitee.org/wp-content/uploads/papers/v11i1/A95991111121.pdf Department of Computer Science, Al al-Bayt University, Jordan Maria Mohammad Yousef Generally, medical dataset classification has become one of the biggest problems in data mining research. Every database has a given number of features but it is observed that some of these features can be redundant and can be harmful as well as disrupt the process of classification and this problem is known as a high dimensionality problem. Dimensionality reduction in data preprocessing is critical for increasing the performance of machine learning algorithms. Besides the contribution of feature subset selection in dimensionality reduction gives a significant improvement in classification accuracy. In this paper, we proposed a new hybrid feature selection approach based on (GA assisted by KNN) to deal with issues of high dimensionality in biomedical data classification. The proposed method first applies the combination between GA and KNN for feature selection to find the optimal subset of features where the classification accuracy of the k-Nearest Neighbor (kNN) method is used as the fitness function for GA. After selecting the best-suggested subset of features, Support Vector Machine (SVM) are used as the classifiers. The proposed method experiments on five medical datasets of the UCI Machine Learning Repository. It is noted that the suggested technique performs admirably on these databases, achieving higher classification accuracy while using fewer features. 11 30 2021 50 55 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.A9624.1111121 https://www.ijitee.org/wp-content/uploads/papers/v11i1/A96241111121.pdf Assistant Professor, Department of Commerce, CMS College of Science and Commerce (Autonomous), Coimbatore (Tamil Nadu), India. Dr. P. Mari Selvam Dr. A. Gomathi Assistant Professor & Head, Department of Psychology, CMS College of Science and Commerce (Autonomous), Coimbatore (Tamil Nadu), India The corona virus which causes a highly infectious of Corona virus disease (COVID-19) that has affected more than 4 lakh people in around the world. Since it has been increased during the pandemic period online shopping usage, rural, urban and globally. In the current scenario many youngster’s changing the attitude has purchased to online shopping because social distancing and self-quarantine efforts. Hence the online shopping promoters like Amazon, flip kart, Reliance digital and other agencies are for the time being too given the importance its available fulfilment and logistics facility to serve the basic needs such as household products, packaged food, health care, hygiene, personal safety and other high priority products. It is for the time being going to taking orders for lower-priority to high priority products. In this study to analyze the impact of online buying behaviour increased in after pandemic period. 11 30 2021 56 58 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.A9603.1111121 https://www.ijitee.org/wp-content/uploads/papers/v11i1/A96031111121.pdf Department of Ship Automation, Gdynia Maritime University, Gdynia, Poland. Monika Rybczak Dawid Trzcińśki Department of Ship Automation, Gdynia Maritime University, Gdynia, Poland. Natalia Wenta Department of Ship Automation, Gdynia Maritime University, Gdynia, Poland. The article contains an overview of articles related to the description of control process visualization. It provides short information on how to visualize the production line based on two programming environments: Factory IO and Inventor together with Matlab/Simulink. The analysis of these two environments concerns control of a virtual 3D object from a real PLC. Both virtual production line projects are based on control from the S7-1214 DC/DC/DC controller. Currently, there is a need to validate the program code or control process which has been done using several commercially available programs. 11 30 2021 59 63 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.A9590.1111121 https://www.ijitee.org/wp-content/uploads/papers/v11i1/A95901111121.pdf