## 4 Results and Discussion
### Phase 1: Analysis of the current situation
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Metric** & **Stocking** & **Standard Deviation** \\ \hline Time Reduction (min) & 2.56 & 0.43 \\ Flow Increase (\%) & 69.73 & 13.08 \\ CO\({}_{2}\) reduction (kg) & 57.74 & 9.20 \\ Economic Savings (EUR) & 143.72 & 22.89 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Mean and standard deviation. * Low initial capacity: If manual operations are inefficient, with high times per vehicle, any significant improvement through automation can generate significant increases in vehicle flow. * Capacity of automated systems: AGVs (Automated Guided Vehicles) and other automated systems have much higher processing rates compared to manual processes. This can justify high increases if the infrastructure allows operation of these automated systems at their maximum. * Optimization of internal traffic: The implementation of IoV and scheduling algorithms can reduce bottlenecks and improve the utilization of terminal capacity, which also contributes to the increase in flow. This result reflects a significant increase due to the improvement in vehicle processing times, which go from 5.91 min to 3.07 min on average. If the initial rates of manual systems are low, this increase is consistent. The following metrics have also been calculated, the values of which are shown in the following figures:  
* Total Cost Per Hour: Manual and automated, adding labor and energy costs. * Hourly Operating Cost Savings: Difference between the total manual and automated cost. * Total Cost Per Vehicle: Calculated by dividing the total cost per hour by the number of vehicles processed in each system. * Percentage Reduction in Operating Costs: Percentage of savings when moving from manual to automated systems. * Cost Per Vehicle Increased (%): Changes in the average cost per vehicle processed between both systems. Automation also allows for a more efficient redistribution of human resources. The system requires fewer direct operational staff and prioritizes supervisory roles, which implies a transformation of the profile of required skills. Managers should consider training and capacity-building programs to facilitate this transition (Figures 4 and 5). Automation has been shown to result in a substantial reduction in vehicle waiting times. This implies an improvement in operational efficiency, reducing congestion in waiting areas and allowing a more continuous flow. For managers, this result highlights the importance of investing in automated systems to improve the user experience and reduce bottlenecks at peak times (Figure 6). Figure 4: Comparison of operational costs per hour. Source: own elaboration. Automated terminals show up to an 80% increase in vehicle processing capacity per hour compared to manual operations. This not only improves the operational capacity of the terminals, but also reduces the costs associated with the need to physically expand the facility. Managers can use this information to plan endpoint growth without compromising service quality (Figures 7 and 8). Figure 5: Percentage reduction in operational costs. Source: own elaboration. Figure 6: Reduction in waiting times. Source: own elaboration. Figure 7: Comparison of vehicle flow. Source: own elaboration. Data show that automation contributes to a significant decrease in CO2 emissions, up to 25 kg less per hour per terminal. This finding is critical in a global context that demands more sustainable operations. Managers can prioritize automation as a strategy to meet sustainability goals and improve public perception of terminals as environmentally responsible infrastructure (Figures 9 and 10). Figure 8: Increase in vehicle flow. Source: own elaboration. Figure 10: CO2 reduction emissions: manual vs. automated. Source: own elaboration. Figure 9: Reduction in CO2 emissions. Source: own elaboration. The application of IoV and blockchain directly contributes to sustainability goals at Ro-Ro terminals. By reducing waiting times and optimizing internal routes, emissions associated with fuel consumption are reduced.