Abstract: A multi-modal communication dynamic switching and adaptive compression system and a method thereof for low-altitude intelligent network are provided. The system includes an airborne terminal and a ground terminal; the airborne terminal comprises a NVIDIA Jetson Xavier NX embedded computing platform, an airborne Raspberry Pi CM4-5G expansion board, an airborne ad hoc network radio, a flight control computer and an optical pod camera; the ground terminal comprises a ground Raspberry Pi CM4-5G expansion board and a ground ad hoc network radio; the multi-modal communication dynamic switching and adaptive compression system and the method thereof for low-altitude intelligent network provided by the invention take advantage of the advantages of longer transmission distance, no dependence on ground infrastructure and flexible deployment of the ad hoc network radio, and use it as a supplementary communication means of 5G public network, so as to ensure the real-time online of UAV.

Abstract: An elastic cooperative inference architecture and method for UAV cluster can dynamically update the scheduling policy according to the status of each node, and can deal with the failure of some nodes. In addition, the elastic cooperative inference architecture and method can process larger scale complex models on the embedded devices with limited performance carried by UAVs by means of cooperative inference, so as to improve the accuracy of intelligent applications. At the same time, the elastic cooperative inference architecture and method can adaptively update the allocation strategy when some nodes are unavailable or recovered, and improve the survivability of UAV cluster through elastic coordination.

Abstract: An elastic cooperative inference architecture and method for UAV cluster can dynamically update the scheduling policy according to the status of each node, and can deal with the failure of some nodes. In addition, the elastic cooperative inference architecture and method can process larger scale complex models on the embedded devices with limited performance carried by UAVs by means of cooperative inference, so as to improve the accuracy of intelligent applications. At the same time, the elastic cooperative inference architecture and method can adaptively update the allocation strategy when some nodes are unavailable or recovered, and improve the survivability of UAV cluster through elastic coordination.