Managing open loop water resource value chain through IoT focused decision and information integration (DII)...

Area of Science:

• Environmental Science
• Computer Science
• Engineering

Background:

• Global water crisis due to unregulated use necessitates sustainable, data-driven solutions in the water industry.
• The Internet of Things (IoT) offers innovative strategies for decision and information integration to enhance water management.
• Shifting to sustainable practices is crucial for addressing water concerns and improving public health.

Purpose of the Study:

• To identify and prioritize the key enablers for implementing the Internet of Things (IoT) in an open-loop Water Value Chain (WVC).
• To analyze factors influencing IoT adoption in the water and wastewater industry for improved resource management.

Main Methods:

• Examined 25 factors for IoT implementation in open-loop WVC.
• Clustered factors into seven enablers using Principal Component Analysis (PCA).
• Applied Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) and fuzzy set theory to prioritize enablers and handle uncertainty.

Main Results:

• Identified the IoT network's ecosystem, configuration, adaptation, and data mobility as the most prominent enablers.
• The Fuzzy DEMATEL approach clarified cause-effect relationships among enablers for prioritization.
• Fuzzy set theory effectively addressed data deficiencies and expert opinion vagueness.

Conclusions:

• The study highlights critical IoT enablers for advancing open-loop WVC management.
• Findings can guide regulatory agencies and water enterprises in prioritizing IoT adoption for efficient water distribution and processing.
• Implementing these enablers can lead to more sustainable and effective water resource management.