In order to solve the dependence of the traditional integrated sensing, computing and communication(ISCC) network on the ground, and to address the problem of high power consumption of ISCC network in emergency response and intensive mission scenarios, a fusion system for collaborative sensing by unmanned aerial vehicle (UAV) and edge computing is proposed. The problem of minimizing the total energy consumption of the system is established under the strict constraints of sensing performance, delay and task offload rate. Meanwhile, the problem is solved with deep reinforcement learning(DRL) and federated learning(FL). Simulations show that the scheme proposed in this paper outperforms other comparative schemes in energy consumption.