Internet of Things: Enhancing small craft handling and rescue training

1. Context, definition of the problem

ENIDH is a higher education institution mainly focused on educating and training merchant marine officers. All aspects of maritime safety, such as survival at sea, search and rescue operations, firefighting, occupational safety, among others, are covered in the curricula of study programs. Part of the maritime safety training is carried out on a lifeboat and on a rescue boat, used to develop small craft handling skills and to allow students to experience the difficulties of rescuing people from the water and manoeuvring these vessels while affected by currents, wind and waves. Students’ performances are assessed during the exercises and corrections are suggested to improve the outcomes. However, currently there is no way to obtain an external perspective on the movement of the vessels and the dummy used for rescue training, which would be valuable to increase the students’ understanding of the effects of wind and current, as well as to aid the trainers in providing feedback and suggesting corrections to the students.


2. Challenge definition. Description of need

We propose the development of a solution to improve the real-time monitoring and the debriefing stage of the maritime safety training conducted in the training vessels, by being able to record and replay movements of both training vessels (the lifeboat and the rescue boat) and of the rescue dummy. The solution shall also be able to record and replay the measurements of an existing weather station. The objective is to have a graphical display of the movements of the vessels and the dummy, and a dashboard with numerical information of: the vessels’ speed, course, heading, roll angle, pitch angle and distance to dummy; the dummy’s course and speed (which can be used to estimate current); the wind direction and speed obtained from the weather station. By sharing and analysing this information with the students, both in real-time and during debriefings, trainers will be able to explain the causal relationships between environmental factors, the vessels’ paths and attitude, and the outcomes of the exercises, hopefully resulting in improved learning outcomes.

3. Requirements

The solution is required to collect data at least from the following IoT sensors:

3 GPS sensors, 1 in each vessel and 1 in the rescue dummy.
2 inertial movement sensors (or equivalent, to be defined), incorporating accelerometers and gyroscopes (and possibly magnetometer).
1 existing weather station
The solution is required to graphically display the positions of the vessels and of the dummy in a dedicated “chart like” environment and on google earth, additionally providing a dashboard with numerical information collected and sent by the sensors. The dashboard should be configurable by the user (regarding the placement and amount of information shown) and should allow the display of information of additional IoT sensors that are added to the system in the future. The graphical display solution should also be open to the incorporation of additional sensors in the future, through a configuration menu. A menu to start and stop data recording, as well as to start and stop replaying is required.

The following information shall be available to be incorporated in the dashboard:

From the vessels:
- Speed
- Course
- Heading
- Pitch angle
- Roll angle
- Rate of turn
- Distance to dummy
- Distance to other vessels

From the rescue dummy:
- Course
- Speed

From the weather station:
- Wind speed
- Wind direction

The solution is also required to enable the configuration of an UDP port to receive live AIS data in standard format. AIS data, if available, shall be recorded and the position of AIS equipped ships shall be shown in the graphical display when replaying the exercises.

A copy of all received data in its raw format shall be saved, to be used in research projects.

The graphical interface shall be available both on PCs and on mobile phones, for the debriefings and for real-time monitoring.


4. Expected Outcomes

The expected outcome is a user friendly, highly flexible and configurable solution to enhance the learning of small craft handling and search and rescue techniques, and to record data that may be used in future research projects. The use of IoT technology in the described maritime safety training activities is expected to have a positive impact on the proficiency level of students, once the training is completed, due to the possibility of performing more accurate analysis and corrections of their performance, both in real-time while in the vessels and in a classroom environment. IoT technology implemented in this solution will also provide tools for trainers to improve the way they transmit knowledge, and potentially increase the students’ interest in maritime safety related subjects.

5. Budget

The solution will have a 15,000€ budget to cover the proponent’s costs. The project will have a 3,000€ budget for hardware procurement, but this cost will be met by the tenderer independently of HR funding. The proponent will provide full details (brand, model, supplier and cost) of hardware procured for the project.

More information about the challenge: https://www.at-virtual.eu/events/infoday-3rd-call-vision-technologies-20220228114501