# Industry 4.0 towards Forestry 4.0: Fire Detection Use Case +
## 1 Introduction
A big picture of the forest fire situation is depicted in Figure 1. As shown, the deployed IoT is used to monitor weather conditions (temperature, humidity, CO (Carbon Monoxide), and CO\({}_{2}\) (Carbon Dioxide)). The sensory weather data are collected and consumed by Apache Kafka as a scalable message queuing system. The collected data (i.e., potential fire events) is then sent to the query engine running on top stream processing platform. The number of possible fire events varies drastically during the day, which causes a delayed fire reporting to the forest department authority. The delay will also raise late alarms to the forest department authority to send its firefighters and drones to the burning forest. Therefore, the automation theme of Forestry 4.0 can lead to appropriate, timely action to be taken from the forest department authority side. Applying adaptive window-based streaming data analysis on forest fire data monitoring can provide early warning mechanisms to reduce fire risks by sending quick decision-making responses. Sustainable forestry focuses on three impacts, i.e., economic (timber supply), ecological (biological and resilience), and social sustainability (forests multiple-use and non-timber products). The forest operations challenges are finding optimal management strategies to predict the environmental, economic, and social performance of various services, processes and productions. The concept of sustainable forestry is based on sustainable development, which refers to maintaining biodiversity, capacity, productivity, vitality and relevant economic, ecological and social operations impacts [7]. Furthermore, the authors of [8] discussed the challenges of forest operations and the proposed Sustainability Impact Assessment (SIA) framework that analyses the social, economic and environmental. Sustainable forestry focuses on three impacts, i.e., economic (timber supply), ecological(biological and resilience), and social sustainability (forests multiple-use and non-timber products). Figure 2 illustrates the importance of forest sustainability management for economic, social, and environmental. Balancing these impacts is a challenge for improving sustainable forestry in terms of data availability, and quality [9; 10]. The authors of [8] summarized the forest operations sustainability impacts in details. Based on the above study, Figure 2 shows the effect and the importance of using techniques solutions for improving Forestry 4.0. Forestry 4.0 aims to bring forest value chain to work within Industry 4.0 parameters (connectivity, security, and productivity, processing remotely). The authors of [11] discussed challenges regarding wireless network availability and connectivity in forest in contrast to industries based on the advanced IoFT, robotics, automation and autonomous technologies. To the best of our knowledge, there is no dynamic stream processing system that has been studied concerning the forest fire management and detection to manage the unpredictable environmental conditions changes. The dynamic window-based selector is particularly important and relevant for forest fire management and detection use case because of its ability to adapt to the environmental changes in time. It can provide a timely warning about fires by real-time monitoring streaming IoT data to detect the dynamic environmental fire risks. To bring our research work to reality, we develop a data generator to generate IoFT-based forest fire streaming forestry data with fluctuated change rates simulated to rapidly changing in an ecological environment within forestry areas. Therefore, it is sensible to state that our work presents an adaptive stream processing prototype for Forestry 4.0 i.e., IoFT-based forest fire detection can automatically adapt the window size according to several parameters and, thus, improve the performance of the underlying IoFT. Figure 1: Forest fire monitoring use case using weather sensors data (temperature, humidity, CO and CO\({}_{2}\)).