Research Article A Real-Time Data Monitoring Framework for Predictive Maintenance Based on the Internet of Things Mudita Uppal, 1 Deepali Gupta , 1 Nitin Goyal, 2 Agbotiname Lucky Imoize , 3,4 Arun Kumar, 5 Stephen Ojo , 6 Subhendu Kumar Pani, 7 Yongsung Kim , 8 and Jaeun Choi 9 1 Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India 2 epartment of Computer Science and Engineering, School of Engineering and Technology, Central University of Haryana, Mahendragarh, Haryana 123031, India 3 epartment of Electrical and Electronics Engineering, Faculty of Engineering, University of Lagos, Akoka, Lagos 100213, Nigeria 4 epartment of Electrical Engineering and Information Technology, Institute of igital Communication, Ruhr University, Bochum 44801, Germany 5 Galgotias College of Engineering and Technology, Greater Noida, Uttar Pradesh 201310, India 6 epartment of Electrical and Computer Engineering, College of Engineering, Anderson University, Anderson, SC 29621, USA 7 Krupajal Engineering College, BPUT, Rourkela, Odisha 751002, India 8 epartment of Technology Education, Chungnam National University, aejeon 34134, Republic of Korea 9 College of Business, Kwangwoon University, Seoul 01897, Republic of Korea Correspondence should be addressed to Jaeun Choi; juchoi@kw.ac.kr Received 15 August 2022; Revised 10 January 2023; Accepted 19 January 2023; Published 13 March 2023 Academic Editor: Mojtaba Ahmadieh Khanesar Copyright © 2023 Mudita Uppal et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Te Internet of Tings (IoT) is a platform that manages daily life tasks to establish an interaction between things and humans. One of its applications, the smart ofce that uses the Internet to monitor electrical appliances and sensor data using an automation system, is presented in this study. Some of the limitations of the existing ofce automation system are an unfriendly user interface, lack of IoT technology, high cost, or restricted range of wireless transmission. Terefore, this paper presents the design and fabrication of an IoT• based ofce automation system with a user•friendly smartphone interface. Also, real•time data monitoring is conducted for the predictive maintenance of sensor nodes. Tis model uses an Arduino Mega 2560 Rev3 microcontroller connected to diferent appliances and sensors. Te data collected from diferent sensors and appliances are sent to the cloud and accessible to the user on their smartphone despite their location. A sensor fault prediction model based on a machine learning algorithm is proposed in this paper, where the k•nearest neighbors model achieved better performance with 99.63% accuracy, 99.59% F1•score, and 99.67% recall. Te performance of both models, i.e., k•nearest neighbors and naive Bayes, was evaluated using diferent performance metrics such as precision, recall, F1•score, and accuracy. It is a reliable, continuous, and stable automation system that provides safety and convenience to smart ofce employees and improves their work efciency while saving resources. 1. Introduction Te Internet of Tings (IoT) defnes a network of objects which can be identifed distinctively in virtual cyberspace. It has embedded sensors, software, and other technologies which communicate and exchange data with other appli• ances. It processes data and creates techniques incorporating smart technology, radio frequency identifcation (RFID) [1], sensing equipment, and other technology advancements. Some other complementary technological developments can be used with IoT to enrich its abilities to lower the gap between the physical and virtual world [2, 3]. IoT sensors have been used in various applications for the last few years, such as predicting natural disasters, home/ofce Hindawi Complexity Volume 2023, Article ID 9991029, 14 pages https://doi.org/10.1155/2023/9991029