## 4 Discussion  
As noted throughout the text, the specific method or technology selected by researchers depends on the required forecast time. The all-sky cameras and regression methods have demonstrated a notable performance for the very short forecast time of up to one hour. In comparison, methods based on weather satellite imagery have been found to be more optimal for a time scale of up to 6 h. However, for a time scale of several hours, cloud dissipation and formation start to interfere with the methods' dynamics and growth. As such, in these cases, the cloud tracking methods are no longer comparable in accuracy to the numerical weather prediction models (NWP). The NWP models, in turn, start to decline at time horizons of several days. A major question that plagues solar forecasting research is the type of camera used for sky images. As shown, there are many types of cameras that can be used for solar forecasting. Some of the most common variants are professional imagers, cameras that record the reflection of a convex mirror oriented to the sky, shadow cameras, and conventional high-resolution cameras (usually security IP). As mentioned in Section 2, all-sky imagers are considerably more expensive than conventional cameras. In fact, all-sky imagers are more prepared for extreme weather conditions and have heating/ventilation for fog, condensation, and snow. Additionally, these cameras, as well as the cameras with a convex mirror, often have a solar tracking device to cover the solar disk. Though at an extra cost, this coverage extends the average life of the camera sensor and avoids possible image glare. Similarly, in terms of costs,shadow cameras require expensive masts. These masts are expensive because they must be sufficiently high enough to capture the shadows cast by clouds to be monitored on the surface. As such, in terms of cost, conventional high-resolution cameras are significantly easier to acquire. One advantage of using these cameras is that they do not record the robotic arms of the solar shading system, making it easier to track clouds as they pass through this area. However, when using this type of camera, the circum-solar regions of the images will appear saturated by the solar glare effect on the sensor. Furthermore, conventional high-resolution cameras will not be able to resolve the inclemency of adverse weather or seasonal conditions. Despite the drawbacks of using this type of camera, many researchers opt for using conventional high-resolution cameras to perform predictive studies. This is mainly due to their relative affordability and accessibility. Indeed, judging from the results analyzed in this article, the majority have been successful and comparable to the results obtained from studies applying more technologically sophisticated methods. Nevertheless, in terms of the sustainable generation of power, the assessment of hardware costs shows that all-sky cameras are more affordable than other technologies discussed in Section 2. Figure 1 highlights the effectiveness of combining all-sky cameras, satellites, and measuring sensors for nowcasting forecasts. Consequently, all-sky cameras are more appropriate for use in solar farms. Indeed, a solar farm requires cameras that have good spatio-temporal resolution and a sensor network of well-calibrated pyranometers and pyheliometers to cover a typical total area ranging from hundreds of meters to a few kilometers. Considering the cost of satellite image acquisition and the implementation of such sensor networks, all-sky cameras are the most economical choice. Figure 3 shows the distribution of all-sky camera surveys conducted. All-sky cameras are mainly deployed in countries with high technological development, such as the United States and Australia, which lead to investment and the use of this technology. Adoption is more incipient in regions between the subtropics, such as Uruguay, where the availability of resources and infrastructure limits their implementation.