## 5 Discussion  
A total of 2050 hash writing requests were confirmed on the Ethereum Sepolia blockchain, spanning various days of a week and several time slots of a day. The time-based strategy executed 144 daily transactions, whereas the threshold-based strategy ranged from 140 to 281 daily writings, depending on threshold values (see Table 6). Consequently, the experiments covered over two weeks of operation for the time-based strategy and one to two weeks for the threshold-based strategy. This transaction volume, designed to assess the performance, timing, and cost efficiency of blockchain-based hash writing under realistic conditions, provides a sufficient basis for meaningful economic feasibility estimates. The combined strategy was evaluated using comprehensive data spanning an entire month, ensuring a more extensive analysis of its adaptability and cost efficiency under varying operational conditions. This broader timeframe allowed us to assess long-term performance trends, capturing fluctuations in data volume and evaluating threshold configurations accordingly. Our experimental results indicate that nearly half (47.17%) of the total transactions were written on the blockchain in less than 13 s (see Table 4), with a mean confirmation time of 9.18 s and a median of 9.16 s. Moreover, the vast majority of transactions (93.61%) were confirmed within 30 s, with overall mean and median confirmation times of 14.83 s and 15.88 s, respectively. The confirmation time boxplots in Figure 5 show that transactions were confirmed more rapidly between 08:00 and 16:00, with a mean time of 13.29 s and a median of 9.56 s (see Table 5). In contrast, slower confirmation times were observed during the 00:00-08:00 and 16:00-00:00 timespans, with median values of 16.23 s and 16.01 s, respectively. This represents an increase of approximately 67-70% compared to the 08:00-16:00 timespan. Furthermore, the integration of blockchain technology significantly augments the system by providing a verifiable timeline of events. By permanently recording event hashes on the blockchain, any change to events stored in the database would be detected; hence, a dispute on recorded timestamps would be resolved. A match of the hash computed on recorded timestamps with the blockchain hash would demonstrate that timestamps were unaltered, while a difference would show that they were altered. This is vital for accountability and legal verification in emergency response scenarios. Notably, in our experiments, all blockchain transactions were confirmed, underscoring the reliability of established platforms such as Ethereum for secure data storage. In cases where a transaction is not confirmed, the affected data remain securely stored in the local database and the hash writing request is reissued, leveraging the inherent resilience of blockchain technology to ensure reliable completion. Collectively, these features enhance data integrity and fault tolerance and provide an indisputable record of incident timelines. In every strategy we tested, the data aggregation performed by the HEA prevents congestion by avoiding overly frequent writing requests on the blockchain. In the transaction fee distributions (Figure 4), we observed that 83.61% transactions incurred costs below USD 0.50. The difference between the Gwei and USD distributions is due to the actual fee in Gwei, which depends on the congestion of the blockchain network at the time of the transaction, and the ETH/USD exchange rate, which is subject to continuous fluctuations. To handle price \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Thresholds** & **Mean Daily Cost (USD)** & **Mean Daily Writings** & **Max Daily Writings** \\ \hline
125-175 & 44.37 & 153 & 163 \\
115-190 & 42.45 & 146.4 & 158 \\
135-195 & 40.23 & 138.7 & 147 \\
145-205 & 38.19 & 131.7 & 138 \\ \hline Time strategy & 41.76 & 144 & 144 \\ \hline \hline \end{tabular}
\end{table}