# Sensing in Inland Waters to Promote Safe Navigation: A Case Study in the Aveiro's Lagoon
## 3 Low-Cost Maritime Data-Sharing System Design and Evaluation
### Techniques for Supporting Maritime Information Sharing and Visualization: A Benchmarking Analysis
The solutions found in this analysis are presented in Table 2, delineating the advantages and disadvantages of each approach, according to boat sensor connectivity; access to inland water data (i.e., the data from hydrodynamic models can be accessed in order to determine the height of the tide and to make predictions regarding the hourly sounding at a specific location and time) or hydrodynamic models; user interface design parameters that present the essential vessel data in a systematic and readily accessible layout, ensuring that the navigator can readily obtain the information they require; an evaluation of the user interface in an outdoor context (i.e., limited to projects with functional prototypes available); the possibility of sharing data to a community; free access for all application or systems functionalities; and finally, the cost. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Criteria**} & **Boot Sensor** & \multirow{2}{*}{**Inland Water Data**} & **Friendly UI** & **SVI-Friendly** & **Community** & **Free** & **Software Access** & **Price in Euros** \\  & & & & & & & \\ \hline Profumo [58] & ✓ & & & & & N/A \\ \hline Chartplotter (e.g., & & & & & & \\ \hline Smart & ✓ & & ✓ & ✓ & ✓ & & 872.32 EUR \\ GOY 2 SRP [60] & & & & & & \\ \hline Dynamo [53] & ✓ & & ✓ & & ✓ & N/A \\ \hline [PERSON]’s project [61] & ✓ & & & & & ✓ & 226.25 EUR \\ \hline Barbeau Necessies (BBN) [62] & ✓ & & ✓ & & ✓ & 348.33 EUR \\ \hline Raspberry Pi on boat & ✓ & & & & & ✓ & 138.91 EUR \\ project [63] & ✓ & & & & & ✓ & 344.80 EUR \\ \hline Le Diouris project [64] & ✓ & & & & ✓ & ✓ & 9999.00 EUR \\ \hline \multicolumn{6}{c}{Nautical applications to support navigation} \\ \hline Navionics & & & & & & & 230.68 EUR \\ Routing App [66] & ✓ & & & & & N/A \\ \hline AS-weather App [99] & ✓ & ✓ & & & N/A \\ \hline Savy Navy [67] & & & & & Free \\ \hline SmartBoat [68] & ✓ & & & N/A \\ \hline Wartsili Salifer [69] & ✓ & & & Free \\ \hline SailRacer [70] & ✓ & & & Free \\ \hline Routinav [12] & & ✓ & & N/A \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Presentation of a systematized comparison of the systems and applications that were subjected to analysis. One application was found that was capable of accurately simulating navigational conditions in inland waters, Routinav, although it is limited to a singular context (the Aveiro's Lagoon). Routinav has access to a sophisticated hydrodynamic model that enables the calculation of tidal heights at any point and time within the inland water plane of Ria de Aveiro. This unique feature enables Routinav to provide precise and reliable information on the observed depth, which is crucial for safe and efficient navigation in such complex environments. In this regard, services such as Navionics Sonar Map [66] and OpenSeaMap [73] have adopted data sharing based on routes acquired by users to enhance digital nautical charts with bathymetric information. Sharing such data aids in updating crucial information that is essential for navigation. However, validating shared information in both applications and navigation support systems is crucial, as these services lack a robust method to rectify shared data discrepancies. To address this, adjustments such as tidal corrections along the water plan are necessary, utilizing either tidal gauge information or the results of hydrodynamic models. The analysis of the electronic components and implemented interfaces used supports this research to create a solution that accurately represents and refines information before sharing it with the maritime community. Raspberry Pi emerges as a promising low-cost solution due to its ability to integrate various sensors and devices for maritime data collection, along with its low power consumption, making it ideal for maritime applications. Among the analyzed products and projects, BBN [62] stands out for its utilization of Raspberry Pi, enabling the aggregation of crucial navigation information into a single interface.