# Computer Vision for Fire Detection on UAVs--From Software to Hardware
## 4 Taxonomy
### Hardware
#### 4.1.2 Cameras  
Computer Vision in most applications and studies is based on the use of cameras. In some applications, more than one camera or even sensors were used to help capture images from the UAV. During the review of scientific studies, some categories of cameras emerged:  
_Visible Spectrum_: This category includes all those devices that have input images that are visible to the human eye. In the present review, this category includes RGB 4K, HD, monocular, 3D devices, CCD technology devices, panorama, stereo depth devices, webcams, mirrorless digital and optical cameras. Of course, all these cameras have different principles of operation and different results in terms of quality, but they all work in the visible light. _IR Systems_: The infrared waves can be displayed through the IR sensors. These systems can be categorized into three types: short-wave (SWIR), middle-wave (MWIR) and long-wave Infrared (LWIR). MWIR and LWIR sensors have the ability to integrate a passive temperature sensor which is able to detect the temperature difference in an environment and then displays the difference in an image (thermal cameras). Many devices of this type, including SWIR, can also present a black and white image. This makes it harder to detect temperature changes in the image but easier to recognize image features. As a result, in many cases, the image is not completely clear in terms of the morphology of its content compared to an RGB camera. Its operation is not limited only during the day, but it can also offer night vision capabilities. Most of the time, such a sensor is combined with a simple camera, so that the images that are taken are not limited only to thermal infrared radiation but also to visible light [35]. Additionally, the SWIR sensors do not need the use of an IR light source, unlike the MWIR and LWIR sensors which require such a light source. _Multispectral/Hyperspectral_: These types of cameras capture the information they receive using multiple wavelengths of light. They are devices for obtaining millions of spectral information for each pixel of the image [36; 37]. More specifically, multispectral cameras use 3-10 extended bands, while hyperspectral cameras use hundreds of narrow bands in wavelengths of light. Hyperspectral cameras consist of detailed spectral information and are used for image acquisition with high spatial and spectral resolutions [38]. In contrast, multispectral cameras, although not as detailed as their display due to their smaller pixel spectral distribution, are used in applications where real-time information exchange is required. This is achieved due to the smaller size of the information being processed [39], compared to the size of the hyperspectral camera information [38]. Figure 7: UAV type tree-map based on number of applications. Additional to the types of the previous cameras described, regarding Computer Vision, some detectors were included in some applications. More specifically, an ultraviolet (UV) detector was used to detect flames through smoke. Through this detector, the danger is identified from the ultraviolet radiation that is created during the fire [19]. Obviously, there are applications and equipment for ultraviolet, visible and also for short, middle and long infrared wavelengths. Figure 8 shows the total percentages of cameras per type used in the applications included in the review. Out of the total number of applications, 38 mentioned what type of camera was used. In addition to the above, other types of hardware were used in the applications included in the review. As shown in Table 2, the hardware that was implemented in each application, depended on the purpose of each mission. The most prevalent type of microprocessors was the ARM Cortex, while there were applications based on single- board computers and, more specifically, the Raspberry Pi. In addition, the on-board computers for drones DJI Manifold and Odroid-XU4 system were used. Finally, the type of the implemented integrated circuits (ICs) were Field-Programmable Gate Array (FPGA).