International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

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DOI Prefix: 10.47001/IRJIET

Predicting and Analyzing Human Daily Routine Using Machine Learning

P.A.L.N. WeerasingheDepartment of Software Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri LankaM.A.P.H.N. MudannayakeDepartment of Software Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri LankaS.D. WijesingheDepartment of Software Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri LankaN.D. Malwenna HewageDepartment of Software Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka

Vol 7 No 10 (2023): Volume 7, Issue 10, October 2023 | Pages: 437-444

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 05-11-2023

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Abstract

Increasing productivity hinges on motivation, yet often individuals inadvertently lose productivity due to health issues and inefficient time management. In the tech domain, various wearable devices like watches, belts, and cameras have emerged to monitor and offer productivity recommendations. However, contemporary society calls for a more intelligent solution - a single mobile application capable of behavior monitoring without external devices. This research delves into such a solution, aiming to comprehend and predict daily human routines via a mobile app, eliminating the need for wearables. The central focus encompasses the detection of sleep patterns, location tracking, food consumption monitoring, and emotion tracking. The ultimate goal is to understand and forecast these facets of user behavior and evaluate their impact on productivity. Leveraging mobile phone sensors for data collection obviates the need for additional hardware. The accumulated data feeds into machine learning models to predict routines. The study's outcomes aspire to provide insights into individual daily behaviors and empower the application to encourage users to make adjustments that bolster productivity. This research contributes to the field by harnessing smartphone technology to enhance users' understanding of their behaviors and optimize their daily routines.

Keywords

productivity, daily routine predictor, machine learning, non-wearable monitor, mobile application


Citation of this Article

P.A.L.N. Weerasinghe, M.A.P.H.N. Mudannayake, S.D. Wijesinghe, N.D. Malwenna Hewage, “Predicting and Analyzing Human Daily Routine Using Machine Learning” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 10, pp 437-444, October 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.710058

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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