Environmental Monitoring and Assessment for Sustainability
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".
Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 10047
Special Issue Editors
Interests: Industrial IoT; ship digitalization; digital twins; sustainable vessel operations; AI/ML applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the promising features of Industry 4.0 and artificial-intelligence-related methods for environmental monitoring and assessment in the industrial sector. The purpose of this Special Issue is to motivate research that links these two major areas and highlights their connection to the United Nations Agenda 2030 Sustainable Development Goals (SDGs).
The ability to utilize data to obtain knowledge, predictions, and today's insights give the tools for continuous process improvements and optimal performance throughout the lifetime of assets. By applying advanced analytics to new and historical data and using big data visualization techniques to present the insights, decisionmakers can assess the environmental status and make data-driven decisions that support sustainable growth.
The Special issue aims to highlight several issues both in the fusion and analysis of information, when it comes to industrial environmental monitoring and assessment network architectures, mainly (but not limited) due to:
- Adverse conditions within specific offshore /industrial environments,
- Wide geographical distribution of the signal acquisition nodes,
- Energy consumption of the monitoring network,
- Latency/bandwidth limitation on a satellite communication network,
- Cybersecurity issues,
- A variety of data analysis methods and technologies.
In addition, emphasis is given to the fulfillment of the requirements highlighted in the literature:
- The need for smart monitoring instruments with lower power requirements, higher accuracy, the ability for synchronization, and applicability in a variety of sensor types;
- The need for an efficient wireless communication network that allows multi-measurement acquisition and real-time data exchange between different structures and between structures and third parties (e.g., authorities);
- Advancements in edge, fog, and cloud computing that enhance industrial Internet of Things and artificial intelligence technology;
- Combination of low-power mesh networking and 5G protocols to allow communication over long distances in an efficient and energy-efficient way.
Dr. Christos Spandonidis
Dr. Fotis Giannopoulos
Guest Editors
Manuscript Submission Information
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Keywords
- environmental monitoring
- industrial Internet of Things
- artificial intelligence
- predictive analytics
- digital twins
- energy efficiency
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