A deep neural network (DNN) is a machine learning tool that mimics the functioning of the neurons in the human brain. DNN can detect smoke and thus provide early warnings regarding wildfires before they occur. In many cases, the initial response to wildfires is inadequate, which leads to large-scale fire damage. The goal of this study was to enable prompt response to wildfires. Unmanned aerial vehicles (UAV) are unmanned and fast and can efficiently reach the source of wildfire smoke. They can also fly for long periods to perform wildfire detection. The UAV platform is a combination of deep neural networks and cyber–physical systems. The platform enables nonspecialists to understand the underlying science and technology by interacting with the builtin mechanisms—deep neural networks and cyberphysical systems (CPS). The results of this study demonstrated the potential of the UAV platform as a tool to pre-empt wildfires. The findings can serve as an important reference for the advancement of wildfire response strategies.