Forest fires cause significant human losses and natural damage and threaten the biodiversity on our planet. Several researchers have studied the potential of wireless sensor networks (WSNs) to manage a forested area and have proven the real potential of this paradigm. Such systems generate a large amount of heterogeneous data in a short time, which may lead to network congestion and delay in data transmission. Processing such data in a short time frame is challenging for a traditional WSN. This article presents a multi-layered architecture for wildfire prevention, detection, and intervention based on WSN, IoT, cloud, and fog computing technologies. The proposed architecture is validated using the iFogSim simulation tool. Two models are compared, cloud-only and fog-cloud-based scenarios. The experimental results show that the cloud-fog model minimizes latency and significantly reduces bandwidth consumption compared to the cloud-only model. To bring fast fire extinguishing ability to the system, the authors recommend the employment of drones equipped with fire extinguishing balls.