Digital system for remote environmental monitoring

University of Calabria

The course aims to provide an introductory overview of the fundamentals of remote-control systems, the different types of digital data to be acquired and processed, and their application in environmental monitoring science. Students will develop basic operational knowledge of various remote-operated platforms, including Remotely Operated Vehicles (ROVs), Autonomous Underwater Vehicles (AUVs), and Autonomous Surface Vehicles (ASVs). The course also covers the use of remote sensing tools, environmental sensors, and integrated technologies applied to the study of marine and coastal environments.

ECTS Credits

2

EQF

7

Languages

Italian

II Level Professional Master’s Program in Engineering geology for energy transition, infrastructures and protection of territory and water resources

Semester

N/A

Duration

16 hours

Location

University of Calabria, Rende (Italy)

D1. Knowledge and understanding

Understand the principles and technologies underlying remote control systems and their application in the field of environmental monitoring. Acquire knowledge about the main tools and platforms (e.g., ROVs, AUVs, drones, sensor networks, satellite systems) used to monitor seas and coastal environments. Comprehend the ecological and biological parameters measurable through remote sensing techniques.

D2. Applying knowledge and understanding

Apply remote sensing and control methodologies to real-world scenarios for monitoring and assessment of marine habitats and species. Operate and configure basic remote-control equipment and interpret data outputs from various remote systems. Integrate data from multiple platforms to support biodiversity mapping and marine resource evaluation.

D3. Making judgments

Critically assess the strengths and limitations of different remote technologies in various marine environments. Select appropriate tools and methodologies for specific biodiversity or resource assessment goals. Evaluate the quality and reliability of data collected remotely and its implications for marine conservation and management decisions. 

D4. Communication skills

Communicate the results of remote monitoring activities effectively through technical reports, visual data representations, and oral presentations. Collaborate in interdisciplinary teams involving marine biologists, engineers, and data analysts. Use appropriate terminology and language to convey technical and ecological concepts to both expert and non-expert audiences. 

D5. Learning skills

Develop the ability to autonomously explore emerging remote sensing technologies and methodologies. Strengthen problem-solving skills in designing and implementing remote-controlled observation strategies. Cultivate a critical and lifelong learning approach to technological innovation in marine biodiversity studies.

Basic knowledge of computer science and data analysis; Basic programming and data management skills. Use of software tools for data analysis and visualization (e.g., spreadsheets, GIS software).

The course includes a combination of lectures and seminars.

At the end of the course, a questionnaire will be administered to the students containing open-ended and closed-ended questions. Questions are addressed to evaluate the knowledge and skills acquired during the course.

The course provides students with the digital skills and technical knowledge required to understand and operate remote monitoring systems for environmental applications. Particular attention is given to the integration of sensors, communication networks, and autonomous platforms for the acquisition and processing of environmental data in marine and coastal ecosystems. The course highlights the role of digital technologies in supporting marine biodiversity conservation, pollution control, and sustainable management of natural resources. Students will also explore the potential of combining data from different platforms (ROVs, AUVs, UAVs, satellites) to create integrated monitoring frameworks.

The expected learning outcomes can contribute to the achievements  of Goal 14: Life below water – Conserve and sustainably use the oceans, seas and marine resources.

The “Digital system for remote environmental monitoring” course is among the teaching activities of the II Level Professional Master’s Programmes in Engineering geology for energy transition, infrastructures and protection of territory and water resources protection. Applicants must hold a Master’s degree (second-level) or an equivalent qualification. For detailed information and updates on how to apply, refer to the following link: https://www.unical.it/storage/higher-edu-training/133/?lang=en 
For further information or specific inquiries, you may contact the “Educational Services Area” of the University of Calabria using the contact details and methods provided at the following link: https://www.unical.it/didattica/iscriversi-studiare-laurearsi/contatta-i-servizi-didattici/?lang=en

The course is structured into four main modules:

Module 1: Fundamentals of remote environmental monitoring (4 hours)

– Overview of remote control and monitoring systems

– Introduction to marine and coastal environmental parameters

– Classification of monitoring platforms and sensors

Module 2: Digital platforms and sensing technologies (4 hours)

– Sensors for physical, chemical, and biological data collection

– Integration of IoT solutions and wireless communication networks

– Data acquisition pipelines and quality assurance

Module 3: Remote-operated and autonomous platforms (4 hours)

– ROVs, AUVs, and ASVs: architecture, operation, and applications

– UAVs (drones) for environmental monitoring of coastal areas

– Satellite-based remote sensing and GIS integration

Module 4: Data processing and applications (4 hours)

– Data analysis and visualization tools (e.g., GIS, dashboards, modeling)

– Case studies on marine biodiversity mapping and pollution monitoring

– Future trends in digital monitoring: AI, cloud platforms, and real-time decision support

  • Teaching material and tutorials will be provided by the lecturers.