自组织物联网动态服务的协同感知与调控策略研究

This project focuses on the construction of biological intelligence algorithms for Internet of Things (IoT) services, which revolves around the long-term goals of the field of artificial intelligence. According to the characteristics and requirements of IoT services, such as large-scale, heterogeneous and dynamic, a set of evolutionary algorithms will be proposed, which has the capabilities of collaborative awareness, discovery and deployment of services. First, a neural network model with dynamic adaptability is to be designed for the intelligent scenario of large-scale IoT. Second, an event-driven dynamic discovery mechanism for IoT collaborative services will be designed. Then, we will explore advanced awareness-based multi-objective evolutionary algorithms and develop a novel intelligent algorithm inspired by biology. The ultimate goal is to realize the environment adaptability of the dynamic adaptive services in IoT. The exploration of this project conforms to the current research demand and development trend of IoT services. It will lay a solid foundation for further exploring the theory of IoT based on biological intelligence, and has important theoretical significance and application value.

本项目紧紧围绕构建生物智能算法应用于物联网服务这个人工智能领域的长远目标而开展应用基础研究。根据物联网服务的大规模、异构性、动态性等特征和需求，拟实现一套具有协同感知、发现和调配服务能力的进化算法。首先，针对大规模物联网智能化场景，设计具有动态适变能力的神经元网络模型；其次，设计基于事件驱动的物联网协同服务动态发现机制；然后拟逐步探讨基于感知的先进的多目标进化算法，进而开发新颖的生物启发的智能算法，实现物联网动态自适应服务的环境适配性。本项目的探索符合当前物联网服务的研究需求及发展趋势，将为进一步探索基于生物智能的物联网服务理论打下坚实基础，具有重要理论意义和应用价值。

本项目根据物联网服务的大规模、异构性、动态性等特征和需求，构建自组织物联网服务模型；研究了人脑视觉方向敏感性机制，分析了它与物联网服务感知之间的映射关系；建立了物联网服务节点协同交互模式，实现了基于方向敏感性机制的自组织物联网服务感知算法。在此基础上，研究和构建了大规模物联网服务感知模型，设计了基于卷积的分区协同感知算法，实现了面向大规模物联网服务的高效能感知算法。基于农业物联网服务场景，提出了基于自适应免疫追尾算法的多区域农机智能优化调度，解决了农业机械调度效率不高等物联网动态服务调控问题。为进一步探索基于生物智能的物联网服务理论提供新的思路和解决方案，具有重要理论意义和应用价值。