## 6 Discussion of the Results  
The results coming out from the experimentation are very promising. First, the ADR-Det algorithm provides an 87-94% accurate detection of trucks during stage 1 of the algorithm. Then during the detection process of ADR signs, the ADR-Det algorithm scores an accuracy score of up to 96%. Finally, the authors executed several experimental scenarios at the ADR-Det stage 2 part and validated their approach, providing 92% mean accuracy in most cases of both ADR-Det stages 1 and 2. Regarding OCR, the ADR-Det algorithm does produce significant results. It correctly recognizes the digits in ADR signs in more than 90% of the images in the upper part of the sign and more than 97% in the lower part. However, because the numbers used are \begin{table}
\begin{tabular}{l l l l l l l l} \hline
**Toll** & **Total** & **Processed** & **Total** & **No. Stage 2** & **No. ADR** & **No of Success** & **Execution Time** \\
**Station** & **Photos** & **Photos** & **Size** & **Truck Photos** & **Photos** & **OCR Photos** & **hh:mm:ss (s)** \\ \hline MAL-1H & 36,739 & 18,369 & 1.1 GB & 12,986 (70.7\%) & 670 (3.65\%) & 347 (1.89\%) & 02:32:42 (8622) \\ MAL-1K & 49,892 & 24,946 & 1.6 GB & 15,099 (60.5\%) & 547 (2.19\%) & 384 (1.54\%) & 02:59:50 (10,790) \\ \hline Total & 86,631 & 43,315 & 2.7 GB & 28,085 (64.8\%) & 1217 (2.81\%) & 731 (1.69\%) & 05:23:32 (19,412) \\ \hline \end{tabular}
\end{table} 
Table 6: Results of the ADR-Det detection execution performance on a realistic dataset, using a 6-core/12 threads i7-8700 - 3.2 GHz system with 32 GB RAM (2 \(\times\) 2666 MHz DDR4), under Ubuntu Linux 20.04.3 LTS, without GPU support. \begin{table}
\begin{tabular}{c c c} \hline
**No of Recognized Digits** & **ADR Sign Upper Part** & **ADR Sign Lower Part** \\ \hline
0 & 1\% & 2\% \\ \hline
1 & 9\% & 1\% \\ \hline
2 & 89 \% & 0\% \\ \hline
3 & 1\% & 15\% \\ \hline
4–5 & 0\% & 82\% \\ \hline
6+ & & 0\% \\ \hline \end{tabular}
\end{table} 
Table 5: Results of the software’s optical character recognition capabilities on the same dataset of 100 photographs of ADR vehicles, after artificially increasing resolution and applying bicubic interpolation. specific, the success rate of recognizing the digit that leads to the correct identification of the hazardous substance transported is more than 95% (as not every combination of digits is used), as explained below. In the results, we do not expect to see all ten digits, particularly in the lower part of the sign (e.g., all possible combinations for ADR hazardous substances up to now start with 0, 1, 2, and 3 (2.9, X) as the first digit). However, even if the algorithm is unable to recognize all of the digits, this type of encoding greatly simplifies the recognition of the hazard substance; for example, if the algorithm recognizes three out of four digits of the lower part of the sign and these digits are 965, the missing number is undoubtedly the first one. It must be either 1 or 2, as these are the only available UN numbers at the moment (UN 1965: Hydrocarbon gas mixtures, UN 2965: Boron trifluoride diethyl etherate). The upper part of the ADR sign is the hazard identifier number. It usually consists of two digits (but may contain three digits in some cases). The lower ADR sign part describes the substance carried with at least three digits (maximum of 4). Therefore, it is sufficient to ensure 100% successful recognition of the upper part, if the hazardous substance transported with the specific ADR vehicle (lower part) is detected. That is, if at least three out of four or two out of three consecutive lower part digits of the carried substance are recognized. The combination of the upper part of the sign with the lower part results in only one substance. More specifically, if the upper part of the sign includes digit number two, it refers to gases (therefore, it can only have hydrocarbon gas mixture as a hazardous substance). If it includes the digit number four, it refers to solids (therefore, it can only have boron).