Fire detection and prevention are essential to preventing fire spread and substantial loss or damage, especially in remote regions like lakes where traditional approaches are almost useless. This review covers fire alarm system advances, focusing on machine learning (ML) to improve detection. The paper also examines how these innovations improve remote fire alarm systems functioning and how they integrate with emerging IoT protocols, sensor networks, and radio technologies like LoRaWAN. It focuses on ML models like CNNs and deep learning to analyze sensor data and detect fires accurately and quickly. This paper discusses fire detection innovation and how ML can improve future systems’ coverage and accuracy.