Abstract
Günümüzde mobil teknolojiye sahip cihazlar sahip oldukları kamera, jiroskop, ivmeölçer, ısı, nem, GPS vb. sensörler ve 3G/WiFi/Bluetooth gibi kablosuz haberleşme teknolojileri sayesinde hayatımızın her noktasına temas etmektedir. Akıllı telefonlarda sunulan bu sensörler aracılığı ile toplanan verilerin işlenmesi ve analizi sayesinde bireylerin uzaktan izlenmesi mümkün olmaktadır. Bu çalışmada Android tabanlı akıllı telefona sahip bir bireyin GPS sensöründen elde edilen veriler ile konumunun ve ivmeölçer sensöründen elde edilen veriler ile de düşme, yürüme vb. vücut aktivitelerinin izlenebildiği bir web temelli uzaktan izleme sistemi sunulmaktadır.
Keywords
References
- Su, X., Tong, H. and Ji, P. (2014) ‘Activity Recognition with Smartphone Sensors’, Tsinghua Science and Technology, vol. 19, no. 3, June, pp. 235-249.
- Dai, J., Bai, X., Yang, Z., Shen, Z., Xuan, D. (2010) ‘Mobile phone-based pervasive fall detection’, Personal and Ubiquitous Computing, vol. 14, no. 7, April, pp. 633-643.
- Martin, E., Vinyals, O., Friedland, G., Bajcsy, R. (2010) ‘Precise Indoor Localization Using Smart Phones’, Proceedings of the international conference on Multimedia ACM MM'10, New York, USA, pp. 787 – 790.
- Habib, M. A., Mohktar, M. S., Kamaruzzaman, S. B., Lim, K. S., Pin, T. M. and Ibrahim, F. (2014) ‘Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues’, Sensor, vol. 14, no. 4, April, pp. 7181-7208.
- Zhang, R., Bannoura, A., Höflinger, F. (2013) ‘Indoor Localization Using A Smart Phone’, IEEE Sensors Applications Symposium (SAS)
- Yavuz G., Kocak M., Ergun G., Alemdar H., Yalcin H., Incel O.D., Akarun, L. and Ersoy C. (2010) ‘A smartphone based fall detector with online location support’, Proceedings of the International Workshop on Sensing for App Phones; Zurich, Switzerland, 2 November 2010, pp. 31–35.
- Bayıroğlu H., Ayan, K. (2014) ‘Android üzerinde web tabanlı çocuk takip sistemi’, SAÜ Fen Bilimleri Dergisi, vol. 18, no. 2, pp. 87-91
- Samsung GearFit, [Online], Avaliable: http://www.samsung.com/global/microsite/gear/gearfit_features.html, 2014.
- Jawbone, [Online], Available: https://jawbone.com/ , 2014.
- Hitachi, [Online], Available: http://www.hitachi-systems.com/eng/news_eng/2013/20130806.html, 2014.
Abstract
Today, the mobile devices supporting 3G/WiFi/Bluetooth wireless communication technology are in contact with every point of our daily life through advanced components and sensors such as camera, gyroscope, accelerometer, temperature, humidity, GPS and so on. These sensors placed in smartphones make the remote monitoring of individuals possible by the analysis and processing of the accumulated data. This study presents a web-based remote monitoring system that tracks body movements (fall, walking, etc.) and location data of the people equipped with Android-based smartphone using data gathered from GPS and accelerometer sensors. In the mobile application, while GPS sensor data are used to obtain personal location information, the data acquired from the accelerometer sensor are used to determine physical user activities such as walking and falling. However, the developed web interface benefiting from Google Maps API, monitors and visualizes mobile users’ physical activities (walking, falling etc.) graphically. It also gives useful information about the locational weather condition (temperature and humidity) where the users located in.
References
- Su, X., Tong, H. and Ji, P. (2014) ‘Activity Recognition with Smartphone Sensors’, Tsinghua Science and Technology, vol. 19, no. 3, June, pp. 235-249.
- Dai, J., Bai, X., Yang, Z., Shen, Z., Xuan, D. (2010) ‘Mobile phone-based pervasive fall detection’, Personal and Ubiquitous Computing, vol. 14, no. 7, April, pp. 633-643.
- Martin, E., Vinyals, O., Friedland, G., Bajcsy, R. (2010) ‘Precise Indoor Localization Using Smart Phones’, Proceedings of the international conference on Multimedia ACM MM'10, New York, USA, pp. 787 – 790.
- Habib, M. A., Mohktar, M. S., Kamaruzzaman, S. B., Lim, K. S., Pin, T. M. and Ibrahim, F. (2014) ‘Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues’, Sensor, vol. 14, no. 4, April, pp. 7181-7208.
- Zhang, R., Bannoura, A., Höflinger, F. (2013) ‘Indoor Localization Using A Smart Phone’, IEEE Sensors Applications Symposium (SAS)
- Yavuz G., Kocak M., Ergun G., Alemdar H., Yalcin H., Incel O.D., Akarun, L. and Ersoy C. (2010) ‘A smartphone based fall detector with online location support’, Proceedings of the International Workshop on Sensing for App Phones; Zurich, Switzerland, 2 November 2010, pp. 31–35.
- Bayıroğlu H., Ayan, K. (2014) ‘Android üzerinde web tabanlı çocuk takip sistemi’, SAÜ Fen Bilimleri Dergisi, vol. 18, no. 2, pp. 87-91
- Samsung GearFit, [Online], Avaliable: http://www.samsung.com/global/microsite/gear/gearfit_features.html, 2014.
- Jawbone, [Online], Available: https://jawbone.com/ , 2014.
- Hitachi, [Online], Available: http://www.hitachi-systems.com/eng/news_eng/2013/20130806.html, 2014.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | April 21, 2015 |
| Submission Date | November 17, 2014 |
| Acceptance Date | January 20, 2015 |
| Published in Issue | Year 2015 Volume: 19 Issue: 1 |
Cite
Cited By
Sanal Koşu: Pandemi’de Yeni Bir Akım
Balıkesır Health Sciences Journal
https://doi.org/10.53424/balikesirsbd.946762
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.