The different spatial curvatures of the universe affect the measurement of cosmological distances, which may also contribute to explaining the observed dimming of type Ia supernovae. This phenomenon may be caused by the opacity of the universe. Similarly, the opacity of the universe can lead to a bias in our measurements of curvature. Thus, it is necessary to measure cosmic curvature and opacity simultaneously. In this paper, we propose a new model-independent method to simultaneously measure the cosmic curvature and opacity by using the latest observations of HII galaxies acting as standard candles and the latest Hubble parameter observations. The machine learning method-Artificial Neural Network is adopted to reconstruct observed Hubble parameter H(z) observations. Our results support a slightly opaque and flat universe at $$1\sigma $$ $1\sigma$ confidence level by using previous 156 HII regions sample. However, the negative curvature is obtained by using the latest 181 HII regions sample in the redshift range $$z\sim 2.5$$ $z\sim 2.5$ . More importantly, we obtain the simultaneous measurements with precision on the cosmic opacity $$\mathrm \Delta \tau \sim 10^{-2}$$ $\Delta \tau \sim {10}^{-2}$ and curvature $$\mathrm \Delta \Omega _K\sim 10^{-1}$$ $\Delta {\Omega }_K\sim {10}^{-1}$ . A strong degeneracy between the cosmic opacity and curvature parameters is also revealed in this analysis.