• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Industrial Informatics, IEEE Transactions on >Smart Random Neural Network Controller for HVAC Using Cloud Computing Technology
【24h】

Smart Random Neural Network Controller for HVAC Using Cloud Computing Technology

机译：使用云计算技术的HVAC智能随机神经网络控制器

获取原文
获取原文并翻译 | 示例
       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Smart homes reduce human intervention in controlling the heating ventilation and air conditioning (HVAC) systems for maintaining a comfortable indoor environment. The embedded intelligence in the sensor nodes is limited due to the limited processing power and memory in the sensor node. Cloud computing has become increasingly popular due to its capability of providing computer utilities as internet services. In this study, a model for the intelligent controller by integrating internet of things (IoT) with cloud computing and web services is proposed. The wireless sensor nodes for monitoring the indoor environment and HVAC inlet air, and wireless base station for controlling the actuators of HVAC have been developed. The sensor nodes and base station communicate through RF transceivers at 915 MHz. Random neural network (RNN) models are used for estimating the number of occupants, and for estimating the predicted-mean-vote-based setpoints for controlling the heating, ventilation, and cooling of the building. Three test cases are studied (Case 1—Data storage and implementation of RNN models on the cloud, Case 2—RNN models implementation on base station, Case 3—Distributed implementation of RNN models on sensor nodes and base stations) for determining the best architecture in terms of power consumption. The results have shown that by embedding the intelligence in the base station and sensor nodes (i.e., Case 3), the power consumption of the intelligent controller was 4.4% less than Case 1 and 19.23% less than Case 2.
机译：智能家居可减少人工干预，以控制供暖通风和空调（HVAC）系统，以保持舒适的室内环境。由于传感器节点中有限的处理能力和内存，因此限制了传感器节点中的嵌入式智能。云计算由于能够提供计算机实用程序作为Internet服务而变得越来越流行。在这项研究中，提出了一种将物联网（IoT）与云计算和Web服务相集成的智能控制器模型。已经开发了用于监视室内环境和HVAC进气的无线传感器节点，以及用于控制HVAC执行器的无线基站。传感器节点和基站通过915 MHz的RF收发器进行通信。随机神经网络（RNN）模型用于估算居住人数，并估算基于预测平均投票的设定点，以控制建筑物的供暖，通风和制冷。为了确定最佳架构，研究了三个测试案例（案例1 –在云上存储和实现RNN模型，案例2 –在基站上实现RNN模型，案例3 –在传感器节点和基站上进行分布式RNN模型）在功耗方面。结果表明，通过将智能嵌入到基站和传感器节点（即案例3）中，智能控制器的功耗比案例1小4.4％，比案例2小19.23％。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号