Forest Fire Forecasting System in Permanent Reserves Forest (PRF) in Peninsular Malaysia using Big Data Analytics (BDA) to assist Forestry Department Peninsular Malaysia (FDPM) on analyzing and forecasting forest fire incidents that occur in PRF of Peninsular Malaysia. The system will enable FDPM to 1) forecast the areas of potential forest fires as early as seven days; 2) locate the relevant agencies to deal with forest fires close to the site of the fire incident that can be identified; 3) locate the nearest water resources; and 4) estimate the cost of the firefighting operations. The impacts of forest fire can be minimized by having an early detection system. The essence of a good early detection system is quick detection of forest fire and the response of forest fire suppression team to put out the forest fire. This system will further enhance and complement the capability of FDPM to suppress early stage of forest fire more effectively. When a forest fire prediction can be implemented, resources of the related agencies can be planned in mitigating the process of suppressing and curbing the fire from getting into an uncontrollable size. At the same time, the cost of the forest fire operation can be predicted depending on the area of the effected location. Finally, the water source can be planned for arrangements before going to a site for a forest fire operation.

https://bda.ketsa.gov.my

• Malaysia

• Remote and rural communities
• National citizens

The platform of this project is based on big data analytic tools including data automation and data acquisition modules and develop mostly using Open Source technologies. Overall architecture has been automated and designed to be integration ready to ensure the replicability. The framework can be replicable at the national level in any country. It also can be extended to add on some of the machine learning and Internet of Things (IOT) devices for monitoring and surveillance the forest fire.

Continuously training to the officer-in-charged of forest fire monitoring and reporting will help them understand better on the results from the system so that they could respond quickly. Integrating new technologies like cloud technology and big data will allow organizations to gather data in the cloud, analyze it in real-time and use this information to obtain insights to improve product and service quality and efficiency. This project can be expanded to other natural disasters such as accumulation of driftwood and debris, landslides, and water surges due to heavy rain and floods. Therefore, the use of BDA system in monitoring high slope data, rainfall data distribution, forest cover that will involve various agencies in assisting FDPM to overcome the matter

Respect for nature - Weather variations such as heat waves are among the causes of forest fire incidents in Peninsular Malaysia. The phenomenon has left adverse effects on forest ecology such as habitat loss and loss of biodiversity. Early and preventive information that can be gained from this project is vital to avoid such incident.