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Survey on functions, competencies and training needs
Roles: R1 · Marine IoT,Sensor & Autonomous Systems Engineer R2 · Marine Robotics & Computer Vision Engineer
Sectors: Aquaculture & Fisheries · Ocean Monitoring · OceanRenewables · Port Activities
Primary Sector
*
Aquaculture & Fisheries
Ocean Monitoring
Ocean Renewables (offshore wind, wave, tidal)
Port Activities
Other:
Primary Rol
*
Marine IoT, Sensor &Autonomous Systems Engineer (R2)
Marine Robotics & Computer Vision Engineer (R3)
Both roles
Type of organisation
*
Research Center / Technology or R&D centre
Small Company (<50 employees)
Medium Company (50–250 employees)
Large Company (>250 employees)
Port Authority
Country
*
Ireland
France
Portugal
Spain
Years of experience
*
0-2 years
3-5 years
6-10 years
> 10 years
Sección 1
Main functions of the role (Marine IoT, Sensor &Autonomous Systems Engineer ).
Rate each function and indicate whether a competency gap exists in your organisation. Rating scale: 1 = Very low · 2 = Low · 3 = Medium · 4 = High · 5 = Very high Gap: Yes / No
*
Rows
Importance
GAP
Gap description (free text)
Design, configure and deploy
marine sensor networks (water quality, acoustic, optical, meteorological)
1
2
3
4
5
Yes
No
Develop and integrate IoT
systems for real-time aquaculture monitoring (dissolved oxygen, temperature,
biomass)
1
2
3
4
5
Yes
No
Program embedded systems and
firmware for marine sensor platforms (microcontrollers, SBCs, low-power
devices)
1
2
3
4
5
Yes
No
Deploy and maintain autonomous
sensing platforms: AUVs, ASVs, smart buoys and mooring systems
1
2
3
4
5
Yes
No
Configure LPWAN, LoRaWAN,
underwater acoustic and satellite communication links for offshore assets
1
2
3
4
5
Yes
No
Build data acquisition
pipelines from sensor to cloud (edge processing, MQTT, OPC-UA, REST APIs)
1
2
3
4
5
Yes
No
Calibrate, validate and
maintain marine hardware in field conditions (corrosion, biofouling, pressure)
1
2
3
4
5
Yes
No
Integrate heterogeneous sensor streams into unified marine monitoring platforms (FIWARE, EMODnet)
1
2
3
4
5
Yes
No
Develop autonomous mission
planning and control software for marine vehicles and buoy arrays
1
2
3
4
5
Yes
No
Apply energy harvesting and
ultra-low-power design principles to extend offshore sensor autonomy
1
2
3
4
5
Yes
No
Other functions not listed above:
Sección 2
Main functions of the role (Marine Robotics & Computer Vision Engineer (R3)).
Rate each function and indicate whether a competency gap exists in your organisation. Rating scale: 1 = Very low · 2 = Low · 3 = Medium · 4 = High · 5 = Very high Gap: Yes / No
*
Rows
Importance
GAP
Gap description (free text)
Design and develop underwater and offshore robotic platforms (ROVs, AUVs, surface drones)
0
1
2
3
4
5
Yes
No
Build computer vision and
image processing pipelines for marine video, sonar and multispectral imagery
0
1
2
3
4
5
Yes
No
Program robotic control
systems using ROS / ROS2 (navigation, localisation, task execution)
0
1
2
3
4
5
Yes
No
Design and conduct autonomous
inspection missions for subsea structures, aquaculture nets and offshore assets
0
1
2
3
4
5
Yes
No
Develop object detection and
classification models for marine species, debris, structural defects and port
objects
0
1
2
3
4
5
Yes
No
Process and analyse marine
imagery datasets (annotation, training, validation) for AI/ML model development
0
1
2
3
4
5
Yes
No
Integrate robotics systems
with IoT sensor networks, SCADA and cloud data platforms
0
1
2
3
4
5
Yes
No
Apply SLAM (Simultaneous Localisation
and Mapping) techniques in GPS-denied underwater environments
0
1
2
3
4
5
Yes
No
Develop acoustic and optical
positioning systems for underwater robotic navigation
0
1
2
3
4
5
Yes
No
Test, validate and document
robotic systems against offshore and maritime safety standards
0
1
2
3
4
5
Yes
No
Functions not listed above
Technical competencies
Current level . Required future level . Gap . Training need
For each technical competency, indicate your current level, the level you consider necessary in the next 3 years, whether a gap exists and whether you need training. Scale : 1 = Beginner · 2 = Basic · 3 = Intermediate · 4 = Advanced · 5 = Expert
*
Rows
Current level (1–5)
Required future level (1–5)
GAP?
Training needed?
Embedded systems programming —
C/C++, Python, RTOS, microcontrollers (Arduino, STM32, Raspberry Pi)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
IoT protocols and
architectures — MQTT, OPC-UA, LoRaWAN, LPWAN, CoAP, Zigbee
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Marine sensor technologies — acoustic (ADCP, sonar),
optical (lidar, camera), electrochemical, MEMS
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Underwater acoustic
communication and positioning (USBL, LBL, modems)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Satellite and radio communication
for offshore assets (Iridium, AIS, VHF, LoRa, VSAT)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
ROS / ROS2 — robot
programming, navigation stacks, middleware
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Computer vision and image
processing — OpenCV, deep learning models (YOLO, SegFormer, SAM)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Machine learning for marine
data — anomaly detection, classification, regression on sensor data
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
AUV / ROV / ASV design,
simulation and control — hydrodynamics, thrusters, DVL, IMU integration
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
SLAM and autonomous navigation
in GPS-denied underwater environments
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Edge computing for marine
environments — Jetson, Coral, edge AI inference
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Cloud-IoT platforms — AWS IoT, Azure IoT Hub, GCP IoT,
FIWARE/NGSI-LD
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Marine data pipelines —
time-series (InfluxDB, TimescaleDB), streaming (Kafka), ETL
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Power systems for offshore
deployment — energy harvesting, battery management, low-power design
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Cybersecurity for marine IoT
and robotics systems (IEC 62443, maritime OT security)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Additional technical competencies not included
Transversal competencies
ESCO classification . Current level . Required future level . Gap
Rate your level in the key transversal competencies identified in the ESCO framework for these roles Scale : 1 = Beginner · 2 = Basic · 3 = Intermediate · 4 = Advanced · 5 = Expert
*
Rows
Current level (1–5)
Required future level (1–5)
GAP?
Training needed?
Technical communication
(reports, documentation, briefings for operators and non-specialists)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Interdisciplinary collaboration (marine biologists,
oceanographers, port engineers, data scientists)s
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Field operations planning and
logistics (offshore deployments, dive operations, vessel campaigns)
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Technical leadership and
coordination of engineering teams
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Adaptability to extreme
environmental conditions and rapid technological change
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Innovation and creative
engineering applied to marine robotics and sensing challenges
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Data-driven decision making
for system design and operational optimisation
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Safety, environmental
awareness and responsible innovation in marine operations
1
2
3
4
5
1
2
3
4
5
Yes
No
Yes
No
Additional transversal competencies:
Technologies and tools · Current use · Training need
Priority . Format . Duration
Indicate whether you currently use each technology and/or whether you would like to receive training in it.
*
Rows
Currently in use
Would like training
ROS / ROS2 (Robot Operating
System — navigation, control, middleware)
OpenCV / PyTorch / TensorFlow
(computer vision and deep learning)
ArduPilot / PX4 / Mission Planner
(autopilot for AUV/ASV/drones)
MATLAB / Simulink (system
simulation and control design)
Gazebo / UUV Simulator /
Stonefish (underwater robotics simulation)
FIWARE / NGSI-LD / ThingsBoard
(IoT platform and data management)
InfluxDB / TimescaleDB /
Grafana (time-series data and dashboards)
Apache Kafka / MQTT brokers
(real-time sensor data streaming)
AWS IoT / Azure IoT Hub / GCP
IoT Core (cloud IoT platforms)
NVIDIA Jetson / Google Coral
(edge AI for robotics and vision)
SolidWorks / Fusion 360 /
FreeCAD (mechanical design for marine hardware)
EtherSense / Blueprint Subsea
/ WaterLinked (underwater acoustic/optical positioning)
VideoRay / BlueRobotics /
Ocean Modules (ROV platforms and components)
QGroundControl / Cockpit /
RViz (mission planning and robot visualisation)
PCB design tools — KiCad,
Altium (custom marine electronics development)
Other relevant technologies or tools you use or consider important forthese roles:
Training needs
Priority . Format . Duration
Indicate the priority of each training area for your professional development in the next 2 years (1 =no priority · 2= Low . 3= Medium . 4= High . 5 = very high / urgent). *
*
Rows
1
2
3
4
5
Marine IoT system design and
sensor network deployment
Underwater robotics — AUV/ROV
design, control and operation
Computer vision and AI for
marine imagery and video analysis
ROS / ROS2 programming, navigation and robotics middleware
Edge AI and embedded ML for
marine sensor platforms
Underwater acoustic
communication and positioning systems
Autonomous mission planning for marine vehicles (AUVs,
ASVs, drones)
Cloud-IoT integration and
real-time data pipelines for marine monitoring
Low-power and energy
harvesting design for offshore sensors
Marine field operations —
offshore deployment, dive operations, safety
Cybersecurity for marine IoT
and robotics (IEC 62443, IACS E26/E27)
Blue Economy applications —
aquaculture monitoring, port automation, offshore inspection
Other training needs, accesss barriers (cost, time, language) or comments
Final remarks
Open space — your expertopinion is especially valuable
Specific gaps or barriers inyour sector (Aquaculture & Fisheries, Ocean Monitoring, Ocean Renewables or Port Activities) not captured in the survey:
Send
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