## 7 Conclusions  
Based on the real data of LHD vehicle operations and conducted research for NOx emission prediction, the following conclusions can be derived:  
1. **The MLP models analysed in this article were developed based on the selected input parameters. ** The decision was made to include 11 parameters that were measured using the SYNAPSA system. The selection of parameters was based on their impact on the emission of NOx. 2. **ANN-based models can be an efficient tool for NOx emission prediction of heavy-duty diesel engines installed in the powerful underground LHD vehicles working in transient modes of loading and speeds. ** The environmental conditions in which mining machinery operates are hard. The solution presented in the article aims to improve the safety of underground crews. Since most industrial vehicles with diesel engines are not equipped with sensors that measure the concentrations of harmful gases, the proposed solution for modelling NOx concentrations will provide a better understanding of the atmosphere of the working environment. The coefficient of determination is 0.86293, which the authors consider a satisfactory result for such complex industrial data. The ability to predict average exhaust emissions will allow for controlling gas hazards in underground mine work. 3. **The created ANN-based model should be tested and adapted over bigger datasets for different geological conditions (blasted material, road inclination, surface watering, and transportation distances) and operator experience with different driving manners. ** In further research, the model proposed in the article should be expanded to include more parameters. It is also necessary to test the operation of machines under different geological and hydrogeological conditions. This activity will make it possible to create appropriate models for predicting NOx from mining machines operating under specific geological and mining conditions. 4. **Data prediction values of NOx emission concentrations in mine work can be the basis for manoeuvring the ventilation airflow. ** By incorporating this information into the ventilation system power demand and capacity planning, the ventilation system can be optimized to ensure safe working conditions for the miners. The statistical method proposed in the article provides a way to estimate NOx concentrations that will be present in the mine atmosphere based on various factors such as production plans, a fleet of vehicles, and transportation routes. Knowing this information, ventilation services can adjust the ventilation system accordingly, which can help reduce the risk of health problems caused by high concentrations of NOx in the workplace. Increasing the air volume flow is just one example of how the ventilation system can be adjusted to manage NOx concentrations, and there may be other strategies that can be used as well. The aim of this study was to develop an ANN-based method (estimator or \"soft sensor\") applicable in practice for NOx emissions prediction based on LHD monitoring parameters. This aim was achieved, and the developed procedure is intended for implementation as an additional function (module) in the SYNAPSA system. Following studies will be devoted to the investigation of other underground vehicles (hauling trucks) equipped with different diesel engines and working in other mines and geological conditions. **Author Contributions:** Conceptualization, R.Z. and A.B. ; methodology, R.Z. ; software, F.M. and M.K. ; validation, P.K., P.S. and R.Z. ; formal analysis, P.S. and J.W. ; investigation, A.B. and P.S. ; resources, R.Z. ; data curation, F.M., M.K., P.K. and J.W. ; writing--original draft preparation, A.B., F.M. and P.K. ; writing--review and editing, A.B. and P.K. ; visualization, F.M., J.W. and M.K. ; supervision, R.Z. and P.S. ; project administration, A.B. ; funding acquisition, R.Z. All authors have read and agreed to the published version of the manuscript.