Crop pests and crop losses are constant problems in agriculture. The whole crop inspection is a time-consuming activity if it is performed manually for each plant. The implementation of an automated system would imply an integration between current technologies in precision agriculture. However, some aspects of adopting new technologies present difficulties. For example, many options regarding cameras, metrics and software are available, and choosing the right combination for each application requires research. Currently, using different cameras interchangeably is not simple. The objective of this research is to find the most used technologies for current precision agriculture with drones. In this context, a systematic review of the literature on drone precision agriculture technologies was conducted based on four research questions using the PRISMA methodology. The research method may help clarify the procedure that would be necessary to follow a project on drone design for plant health focused on multispectral and thermal cameras. This meta-analysis retrieved 5292 articles from Scopus, Taylor and Francis, Web of Science and IEEE databases. The number of articles used to answer the research questions was 75. In the end, analyzing the most frequent cameras and indices, Multispectral cameras and the Normalized Difference Vegetation Index (NDVI) were the most referenced, with 41 and 22 mentions, respectively.