The Concept of a Multi-Agent System in Environmental Monitoring
DOI:
https://doi.org/10.31649/1997-9266-2025-181-4-49-57Keywords:
multi-agent system, mobile agent, monitoring, control algorithms, energy efficiency, IoT, UAVAbstract
This article provides a comprehensive analysis of modern multi-agent systems for monitoring, focusing on their architectural solutions, control algorithms, and key functional capabilities. Multi-agent systems, which consist of autonomous agents interacting with each other and their environment to achieve individual or collective goals, have become a promising paradigm for monitoring complex and distributed environments. These systems offer a decentralized and cooperative approach to data collection, processing, and decision-making, making them highly adaptable and efficient for dynamic applications.
The study systematically examines the latest advancements in multi-agent systems, particularly in communication protocols, agent coordination, and the integration of machine learning techniques. Coordination mechanisms, such as consensus algorithms and swarm intelligence, facilitate synchronized operations among distributed agents, improving system reliability and scalability. The incorporation of machine learning allows agents to adapt their behavior dynamically, optimizing monitoring strategies in unpredictable conditions.
Critical aspect of the research is the exploration of challenges hindering the effective deployment of multi-agent systems. Energy efficiency remains a significant concern, especially for mobile agents like unmanned aerial vehicles, necessitating innovative solutions such as hybrid power systems and optimized routing algorithms. Scalability issues arise as the number of agents increases, requiring robust communication frameworks and decentralized decision-making protocols. Additionally, ensuring data quality and system resilience in dynamic environments presents ongoing challenges, demanding advanced validation mechanisms and fault-tolerant architectures.
The article highlights diverse applications of multi-agent systems across various domains, including environmental monitoring, traffic management, industrial automation, and healthcare. In intelligent transportation systems, swarm-based algorithms enable adaptive traffic control, reducing congestion and improving efficiency. Industrial applications leverage multi-agent systems for equipment monitoring and failure detection, enhancing operational safety and productivity.
Future research directions emphasize the need for fully decentralized communication protocols, improved distributed decision-making algorithms and energy optimization techniques for mobile agents. Standardization of interoperability protocols and the development of secure, trust-based data processing frameworks are also identified as critical for broader adoption.
In conclusion, multi-agent systems represent a transformative approach to monitoring, offering scalability, adaptability and resilience. By addressing existing limitations and leveraging emerging technologies, multi-agent systems can unlock their full potential, becoming indispensable tools for managing complex, real-world environments with minimal human intervention.
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