GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants.

Area of Science:

• Energy Science
• Artificial Intelligence
• Agricultural Technology

Background:

• Depleting energy resources necessitate efficient energy utilization and reuse.
• Power plants (nuclear, thermal, carbon) generate substantial waste energy.
• This waste energy presents an opportunity for applications like greenhouse climate control.

Purpose of the Study:

• To develop GreenVMAS for maintaining greenhouse temperatures using waste energy from power plants.
• To create a context-aware and scalable system for greenhouse climate management.

Main Methods:

• Implementation of a case-based reasoning system.
• Integration of virtual organizations and data analysis algorithms.
• Utilization of an artificial neural network for context awareness and scalability.
• Efficient interaction with sensors and actuators.

Main Results:

• Empirical evaluation demonstrated the system's effectiveness.
• Significant reduction in energy bills for greenhouse users was observed.
• The system proved scalable and adaptable to varying greenhouse configurations.

Conclusions:

• GreenVMAS successfully repurposes waste energy for greenhouse heating.
• The system offers a cost-effective and sustainable solution for climate control in agriculture.
• Intelligent energy management is crucial for optimizing resource use in power generation byproducts.