PEMODELAN SISTEM DETEKSI KEBAKARAN DENGAN MULTISENSOR BERBASIS MIKROKONTROLER

  • Fathur Zaini Rachman Politeknik Negeri Balikpapan
  • Nur Yanti Politeknik Negeri Balikpapan
  • Dwi Lesmideyarti Politeknik Negeri Balikpapan
  • Muchamat Ali Purwanto Politeknik Negeri Balikpapan
  • Abelia Abelia Politeknik Negeri Balikpapan
Keywords: kebakaran, sensor, logika fuzzy, fusion center

Abstract

Sistem deteksi dini akan potensi kebakaran dapat mengurangi dampak buruk dari lingkungan. Pada saat ini, keterbatasan sistem deteksi kebakaran adalah pada cakupan area dan letak pemasangan perangkat sehingga sensitivitas sensor di dalam ruangan menjadi berkurang. Pada penelitian ini, diajukan untuk mendeteksi fenomena dalam ruangan dengan memanfaatkan beberapa sensor. Metode logika fuzzy digunakan untuk pengabilan keputuan dalam proses data multisensor dan pada sebuah cluster head (CH), hasil dari proses data adalah level kondisi pada sebuah perangkat end device (ED) . Hasil pengujian menggunakan logika fuzzy menjadikan sistem deteksi terdistribusi pada setiap peragkat ED dan CH, sehingga dapat menghemat penyimpanan dan proses komputasi data pada fusion center (FC).

References

C. P. Rinsland et al., “Tropospheric emission spectrometer (TES) and atmospheric chemistry experiment (ACE) measurements of tropospheric chemistry in tropical southeast Asia during a moderate El Niño in 2006,” J. Quant. Spectrosc. Radiat. Transf., vol. 109, no. 10, pp. 1931–1942, 2008.

L. A. S. da Silva Júnior, R. C. Delgado, M. G. Pereira, P. E. Teodoro, and C. A. da Silva Junior, “Fire dynamics in extreme climatic events in western amazon,” Environ. Dev., no. June, pp. 1–12, 2019.

F. K. Dwomoh, M. C. Wimberly, M. A. Cochrane, and I. Numata, “Forest degradation promotes fire during drought in moist tropical forests of Ghana,” For. Ecol. Manage., vol. 440, no. November 2018, pp. 158–168, 2019.

S. Sloan, B. Locatelli, M. J. Wooster, and D. L. A. Gaveau, “Fire activity in Borneo driven by industrial land conversion and drought during El Niño periods, 1982–2010,” Glob. Environ. Chang., vol. 47, no. November 2016, pp. 95–109, 2017.

M. Jalalifar and G. S. Byun, “A Wide Range CMOS Temperature Sensor with Process Variation Compensation for On-Chip Monitoring,” IEEE Sens. J., vol. 16, no. 14, pp. 5536–5542, 2016.

I. Bosch, S. Gomez, R. Molina, and R. Miralles, “Object discrimination by infrared image processing,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 5602 LNCS, no. PART 2, pp. 30–40, 2009.

Z. D. Lin, S. J. Young, and S. J. Chang, “CO2 Gas Sensors Based on Carbon Nanotube Thin Films Using a Simple Transfer Method on Flexible Substrate,” IEEE Sens. J., vol. 15, no. 12, pp. 7017–7020, 2015.

A. Costea and P. Schiopu, “New design and improved performance for smoke detector,” Proc. 10th Int. Conf. Electron. Comput. Artif. Intell. ECAI 2018, no. 3, pp. 1–7, 2018.

J. Y. Jeong and H. S. Ryou, “A study on smoke movement in room fires with various pool fire location,” KSME Int. J., vol. 16, no. 11, pp. 1485–1496, 2002.

R. A. Aspey, K. J. Brazier, and J. W. Spencer, “Multiwavelength sensing of smoke using a polychromatic LED: Mie extinction characterization using HLS analysis,” IEEE Sens. J., vol. 5, no. 5, pp. 1050–1056, 2005.

L. Xu and Y. Yan, “A new flame monitor with triple photovoltaic cells,” Conf. Rec. - IEEE Instrum. Meas. Technol. Conf., vol. 3, no. 4, pp. 2253–2257, 2005.

A. De Iacovo, C. Venettacci, L. Colace, L. Scopa, and S. Foglia, “PbS colloidal quantum dot visible-blind photodetector for early indoor fire detection,” IEEE Sens. J., vol. 17, no. 14, pp. 4454–4459, 2017.

A. A. L’vov, V. V. Komarov, S. A. Kuzin, and P. A. L’vov, “Fire detection and alarm sensor for avionics based on current loop circuit,” Proc. 2018 IEEE Conf. Russ. Young Res. Electr. Electron. Eng. ElConRus 2018, vol. 2018-Janua, pp. 1109–1112, 2018.

P. Dvorak, M. Mazanek, and S. Zvanovec, “Fire Emissivity Detection by a Microwave Radiometer,” IEEE Geosci. Remote Sens. Lett., vol. 12, no. 11, pp. 2306–2310, 2015.

E. Blazquez and C. Thorn, “Fires and explosions,” Anaesth. Intensive Care Med., vol. 11, no. 11, pp. 455–457, 2010.

R. A. Sowah, A. R. Ofoli, S. N. Krakani, and S. Y. Fiawoo, “Hardware design and web-based communication modules of a real-time multisensor fire detection and notification system using fuzzy logic,” IEEE Trans. Ind. Appl., vol. 53, no. 1, pp. 559–566, 2017.

A. Kushnir and B. Kopchak, “Development of Intelligent Point Multi-Sensor Fire Detector with Fuzzy Correction Block,” 2019 IEEE XVth Int. Conf. Perspect. Technol. Methods MEMS Des., pp. 41–45, 2019.

Z. He, J. Pu, and Y. Cai, “Multi-sensor fire detection algorithm for ship fire alarm system using neural fuzzy network,” Process Saf. Sci. Technol. Part A, vol. 3, pp. 142–146, 2002.

A. Yoddumnern, “The WiFi Multi-Sensor Network for Fire Detection Mechanism using Fuzzy Logic with IFTTT Process Based on Cloud,” in International Conference on Electrical Engineering, 2017, pp. 785–789.

P. Bolourchi and S. Uysal, “Forest fire detection in wireless sensor network using fuzzy logic,” Proc. - 5th Int. Conf. Comput. Intell. Commun. Syst. Networks, CICSyN 2013, pp. 83–87, 2013.

B. Sarwar, I. S. Bajwa, N. Jamil, S. Ramzan, and N. Sarwar, “An Intelligent Fire Warning Application Using IoT and an Adaptive Neuro-Fuzzy Inference System,” Sensors (MDPI), vol. 19, no. 14, p. 3150, 2019.

Published
2024-08-10