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2020 | OriginalPaper | Chapter

Detection and Monitoring of Forest Fire Using Serial Communication and Wi-Fi Wireless Sensor Network

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Abstract

Enhancements in the communication technologies have led to the origin of Wireless Sensor Networks. They allow inter-transmission of the information with or without using the Internet facilities. The detection of forest fire is one of the crucial utilizations of WSN, and our matter of concern is to focus on the detection of fire and monitoring the transfer of information. In this regard, we design an efficient real-time setup which accumulates the information from various places, and uploads them on the remote web server. Through Wi-Fi, the information from numerous places having lack of Internet facility is transmitted to an intermediary server, and same is uploaded on the remote web server using the Internet. We employ NodeMCU micro-controller which has built-in ESP 8266 Wi-Fi module for establishing steadfast communication within the network. Moreover, we implement the proposed elucidation on the Arduino Integrated Development Environment (IDE).

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Literature
1.
go back to reference Wang, G., Zhang, J., et al.: A forest fire monitoring system based on GPRS and ZigBee wireless sensor network. In: 5th International Conference on Industrial Electronics and Applications, Taiwan, pp. 1859–1862. IEEE (2010) Wang, G., Zhang, J., et al.: A forest fire monitoring system based on GPRS and ZigBee wireless sensor network. In: 5th International Conference on Industrial Electronics and Applications, Taiwan, pp. 1859–1862. IEEE (2010)
2.
go back to reference Gislason, D.: Zigbee Wireless Networking, 1st edn. Elsevier, New York (2002) Gislason, D.: Zigbee Wireless Networking, 1st edn. Elsevier, New York (2002)
3.
go back to reference Zhang, J., Li, W., et al.: Forest fire detection system based on a ZigBee wireless sensor network. Front. For. China 3(4), 369–374 (2008)CrossRef Zhang, J., Li, W., et al.: Forest fire detection system based on a ZigBee wireless sensor network. Front. For. China 3(4), 369–374 (2008)CrossRef
5.
go back to reference Dener, M., Ozkok, Y., Bostancioglu, C.: Fire detection systems in wireless sensor networks. In: World Conference Procedia Social and Behavioral Sciences, Turkey, pp. 1846–1850. Elsevier (2015) Dener, M., Ozkok, Y., Bostancioglu, C.: Fire detection systems in wireless sensor networks. In: World Conference Procedia Social and Behavioral Sciences, Turkey, pp. 1846–1850. Elsevier (2015)
6.
go back to reference Ferreira, A., Pinto, P.: Wireless Sensor Network for Forest Fire Detection. FEUP, Portugal (2017) Ferreira, A., Pinto, P.: Wireless Sensor Network for Forest Fire Detection. FEUP, Portugal (2017)
7.
go back to reference Kumar, S., Chaudhary, A., et al.: Identification of fire prone forest areas based on GIS analysis of archived forest fire points detected in last thirteen years. Technical Information Series, India, vol. 1, no. 1 (2019) Kumar, S., Chaudhary, A., et al.: Identification of fire prone forest areas based on GIS analysis of archived forest fire points detected in last thirteen years. Technical Information Series, India, vol. 1, no. 1 (2019)
8.
go back to reference Ulucinar, A.R., Korpeoglu, I., Cetin, A.E.: A Wi-Fi cluster based wireless sensor network application and deployment for wildfire detection. Int. J. Distrib. Sens. Netw. 10(10) (2014). Article ID 651957 Ulucinar, A.R., Korpeoglu, I., Cetin, A.E.: A Wi-Fi cluster based wireless sensor network application and deployment for wildfire detection. Int. J. Distrib. Sens. Netw. 10(10) (2014). Article ID 651957
10.
go back to reference Zheng, Y., Zhao, Y., et al.: An intelligent wireless system for field ecology monitoring and forest fire warning. Sensors 18(12), 4457–4473 (2018)CrossRef Zheng, Y., Zhao, Y., et al.: An intelligent wireless system for field ecology monitoring and forest fire warning. Sensors 18(12), 4457–4473 (2018)CrossRef
11.
go back to reference Widodo, J., Izumi, Y., et al.: Detection of peat fire risk area based on impedance model and DInSAR approaches using ALOS-2 PALSAR-2 data. IEEE Access 7, 22395–22407 (2019)CrossRef Widodo, J., Izumi, Y., et al.: Detection of peat fire risk area based on impedance model and DInSAR approaches using ALOS-2 PALSAR-2 data. IEEE Access 7, 22395–22407 (2019)CrossRef
12.
go back to reference Yan, X., Cheng, J., et al.: Real-time identification of smoldering and flaming combustion phases in forest using a wireless sensor network-based multi-sensor system and artificial neural network. Sensors 16(8), 1228 (2016). PMC 5017393CrossRef Yan, X., Cheng, J., et al.: Real-time identification of smoldering and flaming combustion phases in forest using a wireless sensor network-based multi-sensor system and artificial neural network. Sensors 16(8), 1228 (2016). PMC 5017393CrossRef
13.
go back to reference Alkhatib, A.A.A.: A review on forest fire detection techniques. Int. J. Distrib. Sens. Netw. 10(3) (2014). Article ID 597368CrossRef Alkhatib, A.A.A.: A review on forest fire detection techniques. Int. J. Distrib. Sens. Netw. 10(3) (2014). Article ID 597368CrossRef
14.
go back to reference Shi, W., Cao, J., et al.: Edge computing vision and challenges. Internet Things J. 3(5), 637–646 (2016)CrossRef Shi, W., Cao, J., et al.: Edge computing vision and challenges. Internet Things J. 3(5), 637–646 (2016)CrossRef
15.
go back to reference Neumann, G.B., de Almeida, V.P., Endler, M.: Smart forests fire detection service. In: Symposium on Computer and Communications, Brazil, pp. 1276–1279. IEEE (2018) Neumann, G.B., de Almeida, V.P., Endler, M.: Smart forests fire detection service. In: Symposium on Computer and Communications, Brazil, pp. 1276–1279. IEEE (2018)
16.
go back to reference Bhosle, A.S., Gavhane, L.M.: Forest disaster management with wireless sensor network. In: International Conference on Electrical, Electronics, and Optimization Technique, India, pp. 287–289. IEEE (2016) Bhosle, A.S., Gavhane, L.M.: Forest disaster management with wireless sensor network. In: International Conference on Electrical, Electronics, and Optimization Technique, India, pp. 287–289. IEEE (2016)
17.
go back to reference Ganesh, U.A., Anand, M., et al.: Forest fire detection using optimized solar powered ZigBee wireless sensor networks. Int. J. Sci. Eng. Res. 4(6), 586–596 (2013) Ganesh, U.A., Anand, M., et al.: Forest fire detection using optimized solar powered ZigBee wireless sensor networks. Int. J. Sci. Eng. Res. 4(6), 586–596 (2013)
18.
go back to reference Huh, Y., Lee, J.: Enhanced contextual forest fire detection with prediction interval analysis of surface temperature using vegetation amount. Int. J. Remote Sens. 38(11), 3375–3393 (2017)CrossRef Huh, Y., Lee, J.: Enhanced contextual forest fire detection with prediction interval analysis of surface temperature using vegetation amount. Int. J. Remote Sens. 38(11), 3375–3393 (2017)CrossRef
19.
go back to reference Chakraborty, S., Banerjee, A., et al.: Time-varying modelling of land cover change dynamics due to forest fires. J. Sel. Top. Appl. Earth Obs. Remote Sens. 11(6), 1769–1776 (2018)CrossRef Chakraborty, S., Banerjee, A., et al.: Time-varying modelling of land cover change dynamics due to forest fires. J. Sel. Top. Appl. Earth Obs. Remote Sens. 11(6), 1769–1776 (2018)CrossRef
20.
go back to reference Marchese, F., Mazzeo, G., et al.: Issues and possible improvements in winter fires detection by satellite radiances analysis: lesson learned in two regions of northern Italy. J. Sel. Top. Appl. Earth Obs. Remote Sens. 10(7), 3297–3313 (2017)CrossRef Marchese, F., Mazzeo, G., et al.: Issues and possible improvements in winter fires detection by satellite radiances analysis: lesson learned in two regions of northern Italy. J. Sel. Top. Appl. Earth Obs. Remote Sens. 10(7), 3297–3313 (2017)CrossRef
21.
go back to reference Dhief, F.T.A., Sabri, N., et al.: A review of forest fire surveillance technologies: mobile ad-hoc network routing protocols perspective. J. King Saud Univ. Comput. Inf. Sci. 31, 135–146 (2019) Dhief, F.T.A., Sabri, N., et al.: A review of forest fire surveillance technologies: mobile ad-hoc network routing protocols perspective. J. King Saud Univ. Comput. Inf. Sci. 31, 135–146 (2019)
22.
go back to reference Yuan, C., Liu, Z., Zhang, Y.: Aerial images-based forest fire detection for firefighting using optical remote sensing techniques and unmanned aerial vehicles. J. Intell. Robot. Syst. 88, 635–654 (2017)CrossRef Yuan, C., Liu, Z., Zhang, Y.: Aerial images-based forest fire detection for firefighting using optical remote sensing techniques and unmanned aerial vehicles. J. Intell. Robot. Syst. 88, 635–654 (2017)CrossRef
23.
go back to reference Polivka, T.N., Wang, J., et al.: Improving nocturnal fire detection with the VIIRS day-night band. Trans. Geosci. Remote Sens. 54(9), 5503–5519 (2016)CrossRef Polivka, T.N., Wang, J., et al.: Improving nocturnal fire detection with the VIIRS day-night band. Trans. Geosci. Remote Sens. 54(9), 5503–5519 (2016)CrossRef
24.
go back to reference Leal, B.E.Z., Hirakawa, A.R., Pereira, T.D.: Onboard fuzzy logic approach to active fire detection in Brazilian Amazon forest. Trans. Aerosp. Electron. Syst. 52(2), 883–890 (2016)CrossRef Leal, B.E.Z., Hirakawa, A.R., Pereira, T.D.: Onboard fuzzy logic approach to active fire detection in Brazilian Amazon forest. Trans. Aerosp. Electron. Syst. 52(2), 883–890 (2016)CrossRef
27.
go back to reference Benchoff, B.: A Dev Board for the ESP LUA Interpreter. Accessed 10 Feb 2019 Benchoff, B.: A Dev Board for the ESP LUA Interpreter. Accessed 10 Feb 2019
28.
go back to reference Saha, S., Majumdar, A.: Data center temperature monitoring with ESP8266 based wireless sensor network and cloud-based dashboard with real time alert system. In: Devices for Integrated Circuit, India, pp. 307–310. IEEE (2017) Saha, S., Majumdar, A.: Data center temperature monitoring with ESP8266 based wireless sensor network and cloud-based dashboard with real time alert system. In: Devices for Integrated Circuit, India, pp. 307–310. IEEE (2017)
29.
go back to reference Rajalakshmi, A., Shahnasser, H.: Internet of things using node red and alexa. In: 17th International Symposium on Communications and Information Technologies, Australia (2018) Rajalakshmi, A., Shahnasser, H.: Internet of things using node red and alexa. In: 17th International Symposium on Communications and Information Technologies, Australia (2018)
30.
go back to reference Poongothai, M., Subramanian, P.M., Rajeswari, A.: Design and implementation of IoT based smart laboratory. In: 5th International Conference on Industrial Engineering and Applications, Singapore, pp. 169–173. IEEE (2018) Poongothai, M., Subramanian, P.M., Rajeswari, A.: Design and implementation of IoT based smart laboratory. In: 5th International Conference on Industrial Engineering and Applications, Singapore, pp. 169–173. IEEE (2018)
31.
go back to reference Walia, N.K., Kalra, P., Mehrotra, D.: An IoT by information retrieval approach smart lights controlled using Wi-Fi. In: 6th International Conference Cloud System and Big Data Engineering, India, pp. 708–712. IEEE (2016) Walia, N.K., Kalra, P., Mehrotra, D.: An IoT by information retrieval approach smart lights controlled using Wi-Fi. In: 6th International Conference Cloud System and Big Data Engineering, India, pp. 708–712. IEEE (2016)
32.
go back to reference Barai, S., Biswas, D., Sau, B.: Estimate distance measurement using NodeMCU ESP8266 based on RSSI technique. In: Proceedings of Conference on Antenna Measurements and Applications, Japan, pp. 170–173. IEEE (2017) Barai, S., Biswas, D., Sau, B.: Estimate distance measurement using NodeMCU ESP8266 based on RSSI technique. In: Proceedings of Conference on Antenna Measurements and Applications, Japan, pp. 170–173. IEEE (2017)
33.
go back to reference Bhatnagar, H.V., Kumar, P., et al.: Implementation model of Wi-Fi based smart home system. In: International Conference on Advances in Computing and Communication Engineering, France, pp. 23–28. IEEE (2018) Bhatnagar, H.V., Kumar, P., et al.: Implementation model of Wi-Fi based smart home system. In: International Conference on Advances in Computing and Communication Engineering, France, pp. 23–28. IEEE (2018)
34.
go back to reference Schwartz, M.: Internet of Things with ESP8266. Packt Publishing Ltd., Birmingham (2016) Schwartz, M.: Internet of Things with ESP8266. Packt Publishing Ltd., Birmingham (2016)
36.
go back to reference Pereira, D.G., Afonso, A., Medeiros, F.M.: Overview of Friedman’s test and post-hoc analysis. In: Communications in Statistics – Simulation and Computation, pp. 2636–2653. Taylor & Francis (2015) Pereira, D.G., Afonso, A., Medeiros, F.M.: Overview of Friedman’s test and post-hoc analysis. In: Communications in Statistics – Simulation and Computation, pp. 2636–2653. Taylor & Francis (2015)
37.
go back to reference Fan, G.F., Peng, L.L., Hong, W.C.: Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model. Appl. Energy 224, 13–33 (2018)CrossRef Fan, G.F., Peng, L.L., Hong, W.C.: Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model. Appl. Energy 224, 13–33 (2018)CrossRef
38.
go back to reference Dong, Y., Zhang, Z., Hong, W.C.: A hybrid seasonal mechanism with a chaotic cuckoo search algorithm with a support vector regression model for electric load forecasting. Energies 11(4), 1009 (2018)CrossRef Dong, Y., Zhang, Z., Hong, W.C.: A hybrid seasonal mechanism with a chaotic cuckoo search algorithm with a support vector regression model for electric load forecasting. Energies 11(4), 1009 (2018)CrossRef
39.
go back to reference Mohapatra, S., Khilar, P.M.: Forest fire monitoring and detection of faulty nodes using wireless sensor network. In: TENCON Proceedings of the International Conference, Singapore, pp. 3232–3236, IEEE (2016) Mohapatra, S., Khilar, P.M.: Forest fire monitoring and detection of faulty nodes using wireless sensor network. In: TENCON Proceedings of the International Conference, Singapore, pp. 3232–3236, IEEE (2016)
Metadata
Title
Detection and Monitoring of Forest Fire Using Serial Communication and Wi-Fi Wireless Sensor Network
Authors
Harsh Deep Ahlawat
R. P. Chauhan
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-40305-8_23