This paper builds an intelligent supervisory system for flooded plants in hydroelectric power plants using the LoRa technique to address the shortcomings of traditional safety supervision of flooded plants in hydroelectric power plants, such as inefficiency and lack of wireless data transmission. The upgraded particle swarm is used in conjunction with adaptive simulated annealing techniques to solve a multi-parameter objective optimum transmission model that aims to increase LoRa transmission performance. The study’s findings demonstrate that the best multi-parameter transmission strategy described in this work can be used to construct LoRa terminal transmission, which can both meet distance transmission requirements and lower power consumption during data transfer. The intelligent supervisory system’s packet loss rate in the open environment test was less than 33% within 2 km, and the LoRa module’s power consumption dropped by 33.33% to 94.75% when compared to the NDD86A. This demonstrates LoRa transmission’s supremacy. Both low-power transmission and accurate monitoring data collection are possible.
