# Developing a Fire Monitoring System Based on MQTT, ESP-NOW, and a REM in Industrial Environments
## 1 Introduction  
Fire in high-risk industrial environments, such as chemical plants, manufacturing factories, and shipbuilding yards, poses serious threats to safety and operational continuity [1]. Traditional fire detection systems, relying on wired networks or human monitoring, are often slow to respond and difficult to maintain, particularly in large-scale environments [2]. As companies rely more and more on automation and technology for safety management, there is a growing need for a scalable and dependable fire monitoring system [3]. Fire detection systems fall into two categories: those that make use of multiple sensors to physically detect a fire and those that use an image to identify a fire. For example, an ion sensor can be used to detect smoke or an infrared sensor can be used to identify flame [4]. Wireless systems offer flexibility, ease of installation, and the ability to cover large areas without physical infrastructure constraints [5, 6]. This paper introduces the development and implementation of a wireless fire monitoring system specifically designed for industrialenvironments. The system utilizes Message Queue Telemetry Transport (MQTT) for efficient, low-latency message transmission; ESP-NOW for multi-hop wireless communication; and a radio environment map (REM) to optimize network coverage. The integration of ESP32-CAM sensors for data collection and anomaly detection provides a reliable and scalable solution for the real-time monitoring of fire. The development of fire monitoring systems has gained significant attention in recent years due to the increased risks posed by industrial environments and the need for early detection and rapid response. Various research efforts have explored the use of wireless technologies, lightweight protocols, and machine learning anomaly detection models in fire detection systems. Several studies have proposed the use of IoT-based systems for fire detection, focusing primarily on wireless technologies. For instance, [PERSON] and [PERSON] [7] developed a real-time monitoring system using IoT devices, integrating multiple sensors for fire and hazardous gas detection. Their work utilized Wi-Fi protocols, demonstrating the viability of wireless networks for monitoring large industrial areas. However, their system faced challenges related to signal interference and network reliability in environments with heavy machinery and metal structures, issues that remained unresolved. Similarly, [PERSON] et al. [8] investigated wireless sensor networks (WSNs) for detecting fires in industrial plants. Their study emphasized the flexibility and scalability of wireless solutions but noted significant issues with energy consumption and the stability of communications links in multi-hop networks. The authors suggested that low-power communication protocols, such as ESP-NOW, could be effective in addressing these issues, although they did not implement such a solution in their study. The lightweight MQTT messaging protocol has also been widely studied for fire detection and other industrial monitoring applications. For example, [PERSON] [9] demonstrated the effectiveness of MQTT in a sensor-based monitoring system for detecting fires and gas leaks. That work showed that MQTT is well-suited to environments with limited bandwidth and high latency because it enables reliable data transmission with minimal overhead. However, while that system successfully reduced transmission delays, it relied on a fixed infrastructure for network coverage, which limits its applicability in more complex or remote industrial environments. In recent years, there has been growing interest in the use of low-power, low-latency communication protocols, such as ESP-NOW, in industrial IoT applications. [PERSON] [10] explored the application of ESP-NOW for real-time sensor communication in industrial settings. His study demonstrated that ESP-NOW's peer-to-peer communications model allows multi-hop networking, significantly extending the range of sensor networks without the need for access points (APs).