Surbakti, Eunike Endariahna and Suciani, Andes and Silaen, Philipus and Adibowo, Septian (2021) Pengenalan Aktivitas Manusia Melalui Analisis Data Gerakan Smartphone. Ultimatics: Jurnal Teknik Informatika, 13 (1). ISSN 2581-186X
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Abstract
Today's smartphones are not only a means of communication but now offer many features and deployment of sensors. Smartphones are also designed to track the user's daily activities, learn and then help the user to make better decisions about what the user will take in the future. Applications that utilize the movement of a smartphone to analyze human activity are used by the Moves app, Fitbit Charge, Nike Fuelband, Apple Watch Health app. To perform human motion recognition activities, data is generated and collected from smartphones such as iPhones and Androids, or wearables such as the Apple Watch smartwatch, Nike Fuelband, and Fitbit Charge. Sensors commonly used to collect data include an accelerometer, gyroscope, heart rate monitor, and thermometer. Another method also combines these sensors with a magnetometer and GPS. This study compares previous research to seek opportunities from the resulting benefits such as monitoring city prisoners, community grouping, city density detection and distribution maps whose data can be used by business opportunities.
| Item Type: | Article |
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| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 28 Sep 2021 09:55 |
| Last Modified: | 21 Jun 2023 01:54 |
| URI: | https://kc.umn.ac.id/id/eprint/18436 |
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