Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API

Rakesh Kumar; Meenu Gupta; Dhruv Kinger; Sayanto Roy

doi:10.1007/978-981-19-9858-4_78

Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API

Rakesh Kumar
, Meenu Gupta
, Dhruv Kinger
, Sayanto Roy

Chandigarh University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A forest fire has a profound impact on wildlife, atmospheric, economic and ecosystem structure. The ever-increasing average global temperature and climate change have increased the frequency and magnitude of forest fires. The cause of forest fires can be natural as well as human-caused. This research focuses on the detection technique through which a wildfire incident can be reported as early as possible. In this work, an alert about a forest fire/wildfire is created as soon as it takes place and then spread the news to the world. This aims to solve the negligence of the forest fires taking place and the lack of any specific alerting mechanism of the same. In result analysis, the study proves that the system works with good accuracy once the image has been uploaded by a user. This work only focuses on the detection mechanism of forest fires/wildfires by creating alerts of those incidents and uploading them to Twitter.

Original language	English
Title of host publication	Soft Computing
Subtitle of host publication	Theories and Applications - Proceedings of SoCTA 2022
Editors	Rajesh Kumar, Ajit Kumar Verma, Tarun K. Sharma, Om Prakash Verma, Sanjay Sharma
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	913-923
Number of pages	11
ISBN (Print)	9789811998577
DOIs	https://doi.org/10.1007/978-981-19-9858-4_78
State	Published - 2023
Externally published	Yes
Event	8th International Conference on Soft Computing: Theories and Applications, SoCTA 2023 - Una, India Duration: 21 Dec 2023 → 23 Dec 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	627 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	8th International Conference on Soft Computing: Theories and Applications, SoCTA 2023
Country/Territory	India
City	Una
Period	21/12/23 → 23/12/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

Azure cognitive services
Forest fire
Microsoft azure
NET
Twitter API

Access to Document

10.1007/978-981-19-9858-4_78

Cite this

Kumar, R., Gupta, M., Kinger, D., & Roy, S. (2023). Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API. In R. Kumar, A. K. Verma, T. K. Sharma, O. P. Verma, & S. Sharma (Eds.), Soft Computing: Theories and Applications - Proceedings of SoCTA 2022 (pp. 913-923). (Lecture Notes in Networks and Systems; Vol. 627 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-9858-4_78

Kumar, Rakesh ; Gupta, Meenu ; Kinger, Dhruv et al. / Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API. Soft Computing: Theories and Applications - Proceedings of SoCTA 2022. editor / Rajesh Kumar ; Ajit Kumar Verma ; Tarun K. Sharma ; Om Prakash Verma ; Sanjay Sharma. Springer Science and Business Media Deutschland GmbH, 2023. pp. 913-923 (Lecture Notes in Networks and Systems).

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title = "Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API",

abstract = "A forest fire has a profound impact on wildlife, atmospheric, economic and ecosystem structure. The ever-increasing average global temperature and climate change have increased the frequency and magnitude of forest fires. The cause of forest fires can be natural as well as human-caused. This research focuses on the detection technique through which a wildfire incident can be reported as early as possible. In this work, an alert about a forest fire/wildfire is created as soon as it takes place and then spread the news to the world. This aims to solve the negligence of the forest fires taking place and the lack of any specific alerting mechanism of the same. In result analysis, the study proves that the system works with good accuracy once the image has been uploaded by a user. This work only focuses on the detection mechanism of forest fires/wildfires by creating alerts of those incidents and uploading them to Twitter.",

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Kumar, R, Gupta, M, Kinger, D & Roy, S 2023, Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API. in R Kumar, AK Verma, TK Sharma, OP Verma & S Sharma (eds), Soft Computing: Theories and Applications - Proceedings of SoCTA 2022. Lecture Notes in Networks and Systems, vol. 627 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 913-923, 8th International Conference on Soft Computing: Theories and Applications, SoCTA 2023, Una, India, 21/12/23. https://doi.org/10.1007/978-981-19-9858-4_78

Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API. / Kumar, Rakesh; Gupta, Meenu; Kinger, Dhruv et al.
Soft Computing: Theories and Applications - Proceedings of SoCTA 2022. ed. / Rajesh Kumar; Ajit Kumar Verma; Tarun K. Sharma; Om Prakash Verma; Sanjay Sharma. Springer Science and Business Media Deutschland GmbH, 2023. p. 913-923 (Lecture Notes in Networks and Systems; Vol. 627 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API

AU - Kumar, Rakesh

AU - Gupta, Meenu

AU - Kinger, Dhruv

AU - Roy, Sayanto

PY - 2023

Y1 - 2023

N2 - A forest fire has a profound impact on wildlife, atmospheric, economic and ecosystem structure. The ever-increasing average global temperature and climate change have increased the frequency and magnitude of forest fires. The cause of forest fires can be natural as well as human-caused. This research focuses on the detection technique through which a wildfire incident can be reported as early as possible. In this work, an alert about a forest fire/wildfire is created as soon as it takes place and then spread the news to the world. This aims to solve the negligence of the forest fires taking place and the lack of any specific alerting mechanism of the same. In result analysis, the study proves that the system works with good accuracy once the image has been uploaded by a user. This work only focuses on the detection mechanism of forest fires/wildfires by creating alerts of those incidents and uploading them to Twitter.

AB - A forest fire has a profound impact on wildlife, atmospheric, economic and ecosystem structure. The ever-increasing average global temperature and climate change have increased the frequency and magnitude of forest fires. The cause of forest fires can be natural as well as human-caused. This research focuses on the detection technique through which a wildfire incident can be reported as early as possible. In this work, an alert about a forest fire/wildfire is created as soon as it takes place and then spread the news to the world. This aims to solve the negligence of the forest fires taking place and the lack of any specific alerting mechanism of the same. In result analysis, the study proves that the system works with good accuracy once the image has been uploaded by a user. This work only focuses on the detection mechanism of forest fires/wildfires by creating alerts of those incidents and uploading them to Twitter.

KW - Azure cognitive services

KW - Forest fire

KW - Microsoft azure

KW - NET

KW - Twitter API

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A2 - Kumar, Rajesh

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A2 - Sharma, Tarun K.

A2 - Verma, Om Prakash

A2 - Sharma, Sanjay

PB - Springer Science and Business Media Deutschland GmbH

T2 - 8th International Conference on Soft Computing: Theories and Applications, SoCTA 2023

Y2 - 21 December 2023 through 23 December 2023

ER -

Kumar R, Gupta M, Kinger D, Roy S. Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API. In Kumar R, Verma AK, Sharma TK, Verma OP, Sharma S, editors, Soft Computing: Theories and Applications - Proceedings of SoCTA 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 913-923. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-19-9858-4_78

Incident Reporting of Forest Fire with Azure Cognitive Services and Twitter API

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this