## 2 Fireighting State
### Technology Survey  
Our second survey was focused on some technologies that can contribute to solving the reported problems. In this case, we performed this survey to obtain more information about the second research question. The objective was to collect opinions from professionals to estimate their predisposition to use these technologies. For this purpose, the survey included the target technologies of this study (drone swarms and immersive interfaces), together with some control technologies. These technologies were chosen after a review of research and the commercial literature and served as a reference in the evaluation of target technologies. Incentive systems  
* Prevention: The survey considers a solution of prevention on causes (incentive systems for farmers/ranchers to prevent their use of fire) and two solutions of prevention on combustibles (drone and satellite images to support the preparation of vegetation). In this way, two comparisons can be performed: one among the two strategies for prevention, and another between the two technologies that support the vegetation preparation. * Surveillance: The survey considers two detection systems: one with drones and another with fixed cameras. In this way, the target technology can be compared with a well-known and widely-used surveillance system. Additionally, it includes the use of artificial intelligence to predict the risk of fire, which allows performing this task over specific areas. * Extinguishing: The survey asks about the application of drones to monitor the evolution of fires. In addition, it considers three alternatives to receive the information during field operations: an immersive interface, a mobile device, and a voice assistant. In this way, the target technology can be compared to two common methods to receive information. We took the same measures as in the previous survey to ensure that questions and possible answers were understandable. The participants of the first survey who gave their emails were invited to fill the second survey. In this case, a total of 70 professionals submitted their responses in the first three weeks (again, the survey is still open to new responses (Forest fires in Spain: Technology survey ([[https://forms.gle/XV45](https://forms.gle/XV45) cxL9 jyCgr4f7]([https://forms.gle/XV45](https://forms.gle/XV45) cxL9 jyCgr4f7)) [in Spanish])). A summary of the results is shown in Figure 2.  
As seen in Figures 1 and 2, the survey samples are very similar, only presenting small variations in the professions and tasks. The professionals could evaluate the utility of the different technologies with five ratings: \"very high\", \"high\", \"average\", \"low\", and \"very low\". However, we analyze the results considering three evaluations: positive (including \"very high\" and \"high\" answers), neutral (equivalent to \"average\" answer), and negative (including \"low\" and \"very low\" answers). Figure 2: Results of the technology survey about forest fires in Spain. Three technological solutions for supporting prevention were evaluated: a system with incentives to avoid the use of fire in primary sector activities, satellite images to support the preparation of vegetation, and drone images for the same purpose. In this case, the professionals surveyed evaluate more positively the use of satellite and drone images (approximately, 60-70% positive, 20% neutral, and 10-20% negative). Another three technological solutions were presented for surveillance and detection tasks: a system with cameras to monitor large and/or remote areas, autonomous drones to cover hard-to-reach areas, and the use of artificial intelligence to predict the risk of fire in every location. This last system received the best rating with 48% positive, 20% neutral, and 32% negative, whereas the other two received ratings of 35-44% positive, 16-24% neutral, and 40-41% negative.