Article Code: 5243103
Authors: Deli, Mazzlida
Title: Forest Fire Incident Forecasting System In Permanent Reserved Forest In Peninsular Malaysia Using Big Data Analytics
Journal: SUSTAINABLE ENERGY AND ENVIRONMENT REVIEW
Volume: 1
Year: 2023
Issue: 1
Article Number: 5243103
URL: https://guinnesspress.org/publication/journal/seer/5243103
ISSN: 2996-1181
Abstract: Purpose – This Paper Summarized The Research Project On The Implementa- Tion Of Big Data Analytics To Forecast The Forest Fire Incident In Peninsular Malaysia. Design/Methodology/Approach – The Research Project Has Developed A Forest Fire Incident Forecast- Ing System In Permanent Reserves Forest (PRF) To Forecast Forest Fire Incidence In Peninsular Malaysia. This Project Was Conducted For The Forestry Department Peninsular Malaysia (JPSM) In Collaboration With The Ministry Of Natural Resources, Environment And Climate Change (NRECC) Using Big Data Analytics (BDA). Findings – The Results From The System Have Been Summarized Into Four Conclusions. Firstly, The Forecast Of Areas With Fire Potential Can Be Identified As Early As 7 Days; Secondly, The Location Of Relevant Agencies To Deal With Forest Fires Close To The Site Of The Fire Incident Can Be Identified. Third, The Water Source Close To The Fire Scene Can Be Located; And Finally, The Estimated Cost Of The Extinguishing Operation Can Be Determined In Advance. Practical Implications - To Overcome These Obstacles And Accomplish Wise For- Est Management, Modern Science, And Technology Must Be Improved. This Research Proj- Ect Has Successfully Implemented BDA Via The Forest Fire Incident Forecasting System In PRF. It Has Improved The Performance Of The JPSM For Its Forest Management System. Originality – The Project Is Originally Conducted With Collaborations Between The JPSM And NRECC In The Malaysian Federal Government And Has Been Successfully Implemented By The Forestry Department.
DOI: 10.59762/seer924712041120231103143053