Разработка системы сбора данных о перемещении людей внутри помещения

Main Article Content

Чингиз Ирекович Фатихов
Карен Альбертович Григорян

Аннотация

Пандемия COVID-19 обуславливает рост актуальности проблемы мониторинга и анализа перемещений людей внутри помещений с целью своевременного выявления контактировавших с заболевшими и пресечения дальнейшего распространения инфекции.


В статье предложен один из способов решения данной проблемы – разработка системы определения и сохранения истории местоположения людей внутри помещения. Также в статье рассмотрены методы, параметры и технологии, которые могут быть использованы для решения задачи локализации внутри помещений.

Article Details

Как цитировать
Фатихов, Ч. И., & Григорян, К. А. (2022). Разработка системы сбора данных о перемещении людей внутри помещения. Электронные библиотеки, 25(1), 87-102. https://doi.org/10.26907/1562-5419-2022-25-1-87-102

Библиографические ссылки

1. Tsai H.-C., Chiu C.-J., Tseng P.-H., Feng K.-T. Refined Autoencoder-Based CSI Hidden Feature Extraction for Indoor Spot Localization // IEEE Vehicular Technology Conference, VTC-Fall. 2018. P. 1–5. https://doi.org/10.1109/VTCFall.2018.8690917
2. Kawdungta R., Kawdungta S., Torrungrueng D., Phongcharoenpanich C. Switched Beam Multi-Element Circular Array Antenna Schemes for 2D Single-Anchor Indoor Positioning Applications // IEEE Access. 2021. V. 9. P. 58882–58892. https://doi.org/10.1109/ACCESS.2021.3072951
3. Indoor Location Market global forecast to 2026. URL: https://www.marketsandmarkets.com/Market-Reports/indoor-location-market-989.html, last accessed 2021/10/15
4. Spachos P., Plataniotis K. BLE Beacons for Indoor Positioning at an Interactive IoT-Based Smart Museum // IEEE Systems J. 2020. P. 3483–3493. https://doi.org/10.1109/JSYST.2020.2969088
5. Dong Y., Shan F., Dou G., Cui Y. The Research and Application of Indoor Location Algorithm Based on Wireless Sensor Network // IEEE 3rd International Conference Communication Software and Networks. 2011. P. 719–722. https://doi.org/10.1109/ICCSN.2011.6014369
6. Bharadwaj R., Parini C., Alomainy A. Experimental Investigation of 3-D Human Body Localization Using Wearable Ultra-Wideband Antennas // IEEE Trans. Antennas Propagation. 2015. P. 5035–5044. https://doi.org/10.1109/TAP.2015.2478455
7. Chen R.A. Novel Method for Indoor Location Identification. // 2nd International Symposium on Aware Computing. 2010. P. 257–262. https://doi.org/10.1109/ISAC.2010.5670486
8. Методы локального позиционирования. URL: https://habr.com/ru/company/realtrac/blog/301706/, last accessed 2021/11/02.
9. Yassin A., Nasser Y., Awad M., Al-dubai A. Simultaneous Context Inference and Mapping using mm-Wave for Indoor Scenarios // IEEE International Conference on Communications (ICC). 2017. https://doi.org/10.1109/ICC.2017.7996976
10. Zafar F., Gkelias A., Leung K.K. A Survey of Indoor Localization Systems and Technologies // IEEE Communications Surveys Tutorials. 2019. P. 2568–2599. https://doi.org/10.1109/COMST.2019.2911558
11. Laoudias C., Moreira A., Kim S., Lee S., Wirola L., Fischione C. A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation // IEEE Communications Surveys & Tutorials. 2018. P. 3607–3644. https://doi.org/10.1109/COMST.2018.2855063
12. Wang X., Gao L., Mao S., Pandey S. CSI-based Fingerprinting for Indoor Localization: A Deep Learning Approach // IEEE Transactions on Vehicular Technology. 2016. P. 763–776. https://doi.org/10.1109/TVT.2016.2545523
13. Hsieh H.-Y., Prakosa S.W. Towards the Implementation of Recurrent Neural Network Schemes for WiFi Fingerprint-Based Indoor Positioning // IEEE Vehicular Technology Conference. 2018. https://doi.org/10.1109/VTCFall.2018.8690989
14. Ding N., Wagner D., Chen X., Pathak A., Hu Y.C., Rice A. Characterizing and modeling the impact of wireless signal strength on smartphone battery drain // ACM Sigmetrics Perform. 2013. P. 29–40. https://doi.org/10.1145/2494232.2466586
15. Cidronali A., Maddio S., Giorgetti G., Manes G. Analysis and Performance of a Smart Antenna for 2.45-GHz Single-Anchor Indoor Positioning // IEEE Transactions on Microwave Theory and Tech. 2010. P. 21–31. https://doi.org/10.1109/TMTT.2009.2035947
16. Rusli M.E., Ali M., Jamil N., Din M.M. An Improved Indoor Positioning Algorithm Based on RSSI-Trilateration Technique for Internet of Things (IOT) // International Conference on Computer and Communication Engineering. 2016. P. 72–77. https://doi.org/10.1109/ICCCE.2016.28
17. Ren J., Wang Y., Niu C., Song W., Huang S. A Novel Clustering Algorithm for Wi-Fi Indoor Positioning // IEEE Access. 2019. P. 122428–122434. https://doi.org/10.1109/ACCESS.2019.2937464
18. Shi S., Sigg S., Chen L., Ji Y. Accurate Location Tracking from CSI-Based Passive Device-Free Probabilistic Fingerprinting // IEEE Transactions on Vehicular Technology. 2018. P. 5217–5230. https://doi.org/10.1109/TVT.2018.2810307
19. Yu N., Zhan X., Zhao S., Wu Y., Feng R. A Precise Dead Reckoning Algorithm Based on Bluetooth and Multiple Sensors // IEEE Internet Things Journal. 2018. P. 336–351. https://doi.org/10.1109/JIOT.2017.2784386
20. Sadowski S., Spachos P. RSSI-Based Indoor Localization with the IoT // IEEE Access. 2018. P. 30149–30161. https://doi.org/10.1109/ACCESS.2018.2843325
21. Dong Y., Shan F., Dou G., Cui Y. The Research and Application of Indoor Location Algorithm Based on Wireless Sensor Network // IEEE 3rd International Conference Communication Software and Networks. 2011. P. 719–722.
22. Lo L., Li C. Passive UHF-RFID Localization Based on the Similarity Measurement of Virtual Reference Tags // IEEE Trans. Instrum. Meas. 2018. P. 2926–2933. https://doi.org/10.1109/TIM.2018.2869408
23. Cha J.H., Kim Y.J. A Dual-Band Low-Power-Consumption Active RFID Tag Based on a Meander FPCB Antenna for Subway Vehicle Management // J Electromagn. Eng. Sci. 2021. P. 71–77. https://doi.org/10.26866/jees.2021.21.1.71
24. Škiljo M., Šolić P., Blažević Z., Perković T. Analysis of Passive RFID Applicability in a Retail Store: What Can We Expect? // Sensors. 2020. https://doi.org/10.3390/s20072038
25. Li J.-Q., Feng G., Wei W., Luo C., Cheng L., Wang H., Song H., Ming Z. PSOTrack: A RFID-Based System for Random Moving Objects Tracking in Unconstrained Indoor Environment // IEEE Internet Things J. 2018. P. 4632–4641. https://doi.org/10.1109/JIOT.2018.2795893
26. Hanssens B., Plets D., Tanghe E., Oestges C., Gaillot D.P., Lienard M., Li T., Steendam H., Martens L., Joseph W. An Indoor Variance-Based Localization Technique Utilizing the UWB Estimation of Geometrical Propagation Parameters // IEEE Transactions on Antennas and Propagation. 2018. P. 2522–2533. https://doi.org/10.1109/TAP.2018.2810340
27. Nemer I., Sheltami T., Shakshuki E. Performance evaluation of range-free localization algorithms for wireless sensor networks // Personal and Ubiquitous Computing 25. 2021. P. 177–203. https://doi.org/10.1007/s00779-020-01370-x
28. Betti Sorbelli F., Pinotti C.M., Silvestri S., K. S. Measurement Errors in Range-based Localization Algorithms for UAVs: Analysis and Experimentation // IEEE Transactions on Mobile Computing. 2020. P. 1291–1304. https://doi.org/10.1109/TMC.2020.3020584
29. Pakanon N., Chamchoy M., Supanakoon P. Study on Accuracy of Trilateration Method for Indoor Positioning with BLE Beacons // 6th International Conference on Engineering, Applied Sciences and Technology (ICEAST). 2020. https://doi.org/10.1109/ICEAST50382.2020.9165464
30. Yandex IoT Core. URL: https://cloud.yandex.ru/services/iot-core last accessed 2022/02/19.
31. Yandex Cloud Functions. URL: https://cloud.yandex.ru/services/functions last accessed 2022/02/25.