# Colored Petri Net Modelling and Evaluation of Drone Inspection Methods for Distribution Networks
## 5 Discussion  
After the analysis of the state of the art, we can conclude that most of the existing solutions can be classified into one of three groups:  
* Conceptual design, which allows for selecting drone parameters for the task;
* Solving logistical problems, which allows for determining the cost of using certain equipment;
* Route-planning task, which finds the optimal route taking into account the UAV's characteristics. Our solution, on the other hand, addresses these tasks in an integrated way and allows us to solve them within a single model. For example, for the conceptual design of a drone, it is possible not only to take into account the technical characteristics required by the object but also to simulate the entire product life cycle at the early design stages. To solve logistical problems, we can offer an evaluation of different drone grouping and configuration options in terms of drone costs, maintenance as well as human resources. Therefore, our model allows for a more accurate and complete analysis of these parameters, based not only on the technical characteristics of drones but also on external factors. For the route-planning task, the model allows us to determine the most appropriate location of charging stations or take-off points, vary the number of drones and their parameters and optimise the route in case of intersection points. In addition to the basic route-planning tasks, we can also take into account the endurance of the UAV for the desired trajectory. This will be an advantage in the long-term perspective. In terms of practical applications, our methodology allows us to replicate mathematically the monitoring process, taking into account the UAV's characteristics and stochastic factors in UAV operation. We strongly believe that such a model can be used for a wide range of applications. For example, monitoring customers can select the monitoring strategy, type and UAV model for a particular object among the existing commercial solutions to meet their requirements. The result of the methodology will be a clear term of reference, based on the UAV's capabilities and which suits the customer's purpose. The organisation providing the monitoring can evaluate whether their resources are being used properly, adjust flight paths, select equipment, formulate a maintenance strategy, and find ways to improve their performance. Component and UAV manufacturers can quickly adjust their solutions and developments within the existing elemental base to meet specific practical challenges. Moreover, our model allows for the comparison of conceptually different types of drones, such as planes, multicopters and convertiplanes. The model can be scaled not only to the object of the drone application but also to the aircraft components. Thus, with this method, it is possible to consider the life cycles of all components and optimise the operating cost over the long term. At the concept stage, it can be assumed that such a method will allow the formulation and introduction of standards in the UAV field, which will increase drone engagement, the safeness of its application as well as the unification of technical solutions. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Component** & **Drone 0** & **Drone 1** & **Drone 2** \\ \hline Propellers & 176.56 & 184.36 & 187.01 \\ Batteries & 19.25 & 18.13 & 18.85 \\ Motors & 9.17 & 9.14 & 9.22 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Expected number of maintenance cycles for each module of UAV used. From a technical point of view, we consider the following ways of further developing this methodology:  
* To expand the number of factors taken into account in the monitoring modelling, e.g., to consider weather conditions;
* To automate the process of adding modules and to create a database of UAVs to simplify the research process;
* The model can be developed into a software product, which will be useful for consumers of facility monitoring services, as well as for UAV manufacturers and service providers to assess their competitiveness.