摘要：A scientific and reasonable recommendation algorithm for plant-protecting UAV (Unmanned Aerial Vehicle) operating helps UAV renters with optimal and economical solutions, as well improves the efficiency of plant protecting work and its management. This paper proposed a method of UAV operation recommendation for plant-protecting UAV users based on log data processing, and built a log data real-time analysis and calculation system using Apache Storm framework technology. According to the characteristics of the plant protection operations and the UAV users, two recommendation algorithms were designed and developed in this paper, one of them combined user feature and collaborative filtering and the other one was based on content filtering. In the former algorithm, the most similar neighbor users of the specific target user were investigated first, then the score of every similar neighbor’s each operation was calculated and an appropriate operation recommendation list was produced according to the calculation result of their weighted scores. The later recommendation algorithm took the target user’s interested operation location, spraying type and plant type into consideration, and it recommended the potential interested plant-protecting operations for the target user by analyzing his/her online search, browse history and records. These two algorithms were developed and integrated into an existing system we built earlier using Python. System test and analysis results showed that Storm framework could provide a real-time, low latency, high throughput and robust computing framework, and the log data processing based algorithms could give users the most meaningful plant-protecting operation recommendations according to the preset rules, which could potentially improve the system’s intellectuality, convenience and usability.
