1. Comprehensive Maritime Incident Management: protocols, roles, and chain of command for coordinated response
2. Operational Planning and Execution: briefing, routes, weather windows, and go/no-go criteria
3. Rapid Risk Assessment: criticality matrix, scene control, and decision-making under pressure
4. Operational Communication: VHF/GMDSS, standardized reports, and inter-agency liaison
5. Tactical Mobility and Safe Boarding: RHIB maneuvers, approach, mooring, and recovery
6. Equipment and Technologies: PPE, signaling, satellite tracking, and field data logging
7. Immediate Care of the Affected: primary assessment, hypothermia, trauma, and stabilization for evacuation
8. Adverse Environmental Conditions: swell, Visibility, flows, and operational mitigation

   Simulation and training: critical scenarios, use of VR/AR, and exercises with performance metrics

   Documentation and continuous improvement: lessons learned, indicators (MTTA/MTTR), and SOP updates

1. Introduction to Intelligent Systems Architecture: Layers, Components, and Data Flows.
2. Sensor Fundamentals: Types, Characteristics, Accuracy, Calibration, and Maintenance.
3. Motion and Orientation Sensors: IMU (Inertial Measurement Unit), Accelerometers, Gyroscopes, Magnetometers.
4. Global Positioning Systems (GNSS): GPS, GLONASS, Galileo, BeiDou; Architectures and protocols.

Indoor positioning: technologies (WiFi, Bluetooth, UWB, beacons), trilateration and fingerprinting methods.

SLAM (Simultaneous Localization and Mapping): algorithms, sensors used, applications in robotics and augmented reality.

Sensor fusion: filtering algorithms (Kalman, Particle Filter), integration of data from different sources.

Wireless communication for sensors: protocols (Zigbee, LoRaWAN, NB-IoT), security, and power management.

Sensor signal and data processing: filtering techniques, Fourier analysis, machine learning for pattern recognition.

Applications of architecture, sensors, and smart positioning: smart cities, precision agriculture, logistics, healthcare, and security.

‘

1. Introduction to Sensor System Architecture: Types, characteristics, and applications.
2. Fundamentals of Sensors for Environmental Perception: Physical principles, measurement ranges, and accuracies.
3. Position and Orientation Sensors: IMUs, GNSS, encoders, odometry.
4. Distance and Depth Sensors: LiDAR, stereo cameras, ultrasonic sensors, radar.
5. Image Sensors: RGB cameras, hyperspectral cameras, thermal cameras.
6. Sensor Signal Processing: Filtering, calibration, sensor fusion.
7. 3D Environmental Modeling: Point clouds, meshes, volumetric models.
8. Data Acquisition and Alignment Techniques: ICP, SLAM.
9. Environmental Knowledge Representation: Semantic Maps, Scene Graphs.
10. Environmental Modeling Applications: Robotics, Augmented Reality, Digital Twins.

‘

1. Introduction to Autonomous Navigation: History, Milestones, and Challenges
2. Environmental Perception Sensors: Cameras (RGB, Depth), LiDAR, Radar, Ultrasound
3. Image Processing: Object Detection, Semantic Segmentation, Pattern Recognition
4. SLAM (Simultaneous Localization and Mapping): Algorithms, Variants, and Limitations
5. Route Planning: Search Algorithms (A*, Dijkstra), Path Optimization
6. Control and Actuation: Motion Models, PID Controllers, MPCs
7. Localization and Odometry: GNSS, IMU, Encoders, Sensor Fusion
8. Artificial Intelligence and Machine Learning in Autonomous Navigation: Learning by reinforcement, neural networks.
9. Ethics and safety in autonomous navigation: legal considerations, liability, and failures.
10. Software and hardware architectures for autonomous navigation systems.

‘

1. Introduction to Autonomous Navigation: History, Levels of Autonomy, and Applications
2. Autonomous Systems Architecture: Perception, Planning, Control, and Actuation
3. Navigation Sensors: Classification, Operating Principles, and Specifications
4. Inertial Measurement Units (IMUs): Accelerometers, Gyroscopes, and Magnetometers
5. Global Positioning Systems (GNSS): GPS, GLONASS, Galileo, and BeiDou
6. LiDAR (Light Detection and Ranging): Principles, Types, Data Processing, and Applications
7. Cameras: Monocular, Stereo, and RGB-D Vision; Image processing and computer vision

   Radar: principles, types, signal processing, and obstacle detection

   Visual odometry and SLAM (Simultaneous Localization and Mapping)

   Sensor fusion: Kalman filters, Bayesian networks, and advanced techniques

   ‘

1. System Architecture and Components: Structural design, materials, and subsystems (mechanical, electrical, electronic, and fluid) with selection and assembly criteria for marine environments
2. Fundamentals and Principles of Operation: Physical and engineering foundations (thermodynamics, fluid mechanics, electricity, control, and materials) that explain performance and operating limits
3. Safety and Environmental (SHE): Risk analysis, PPE, LOTO, hazardous atmospheres, spill and waste management, and emergency response plans
4. Applicable Regulations and Standards: IMO/ISO/IEC requirements and local regulations;
5. Conformance criteria, certification, and best practices for operation and maintenance
6. Inspection, testing, and diagnostics: Visual/dimensional inspection, functional testing, data analysis, and predictive techniques (vibration, thermography, fluid analysis) to identify root causes
7. Preventive and predictive maintenance: Hourly/cycle/seasonal plans, lubrication, adjustments, calibrations, consumable replacement, post-service verification, and operational reliability
8. Instrumentation, tools, and metrology: Measuring and testing equipment, diagnostic software, calibration and traceability; selection criteria, safe use, and storage
9. Onboard integration and interfaces: Mechanical, electrical, fluid, and data compatibility; Sealing and watertightness, EMC/EMI, corrosion protection, and interoperability testing.

   Quality, acceptance testing, and commissioning: process and materials control, FAT/SAT, bench and sea trials, go/no-go criteria, and evidence documentation.

   Technical documentation and integrated practice: logs, checklists, reports, and a complete case study (safety → diagnosis → intervention → verification → report) applicable to any system.