As the smart home is the end-point power consumer, it is the major part to be controlled in a smart micro grid. There are so many challenges for implementing a smart home system in which the most important ones are th...As the smart home is the end-point power consumer, it is the major part to be controlled in a smart micro grid. There are so many challenges for implementing a smart home system in which the most important ones are the cost and simplicity of the implementation method. It is clear that the major share of the total cost is referred to the internal controlling system network; although there are too many methods proposed but still there is not any satisfying method at the consumers＇ point of view. In this paper, a novel solution for this demand is proposed, which not only minimizes the implementation cost, but also provides a high level of reliability and simplicity of operation; feasibility, extendibility, and flexibility are other leading properties of the design.展开更多
With the emerging of sensor networks, research on sensor-based activity recognition has attracted much attention. Many existing methods cannot well deal with the cases that contain hundreds of sensors and their recogn...With the emerging of sensor networks, research on sensor-based activity recognition has attracted much attention. Many existing methods cannot well deal with the cases that contain hundreds of sensors and their recognition accuracy is requisite to be further improved. A novel framework for recognizing human activities in smart home was presented. First, small, easy-to-install, and low-cost state change sensors were adopted for recording state change or use of the objects. Then the Bayesian belief network (BBN) was applied to conducting activity recognition by modeling statistical dependencies between sensor data and human activity. An edge-encode genetic algorithm (EEGA) approach was proposed to resolve the difficulties in structure learning of the BBN model under a high dimension space and large data set. Finally, some experiments were made using one publicly available dataset. The experimental results show that the EEGA algorithm is effective and efficient in learning the BBN structure and outperforms the conventional approaches. By conducting human activity recognition based on the testing samples, the BBN is effective to conduct human activity recognition and outperforms the naive Bayesian network (NBN) and multiclass naive Bayes classifier (MNBC).展开更多
Smart home is a promising solution to improving the quality of people＇s life. Much work has been done in the field, but most of these solutions are just based on home gateway, leaving much to be improved. One of its ...Smart home is a promising solution to improving the quality of people＇s life. Much work has been done in the field, but most of these solutions are just based on home gateway, leaving much to be improved. One of its defects is the relatively high energy consuming and its radiation, and the other is that it is not available to the old home appliances which fail to access the internet. Full use of the low energy consuming characteristic of the Zigbee wireless sensor network, a completely new smart home solution is put forward in this paper. Without need of a home gateway and any modification for the currently used family appliances, the method uses the Zigbee coordinator as the central controller and the controllers of appliances as the end devices of Zigbee. It can realize a comfortable and smart home. Experiments show that the scheme proposed is feasible and it will be no doubt to be able to improve the quality of people＇s daily life.展开更多
The wireless sensor network （WSN） consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potenti...The wireless sensor network （WSN） consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potential deployments is in the form of smart home and ambient assisted living （SHAAL）to measure patients or elderly physiological signals, control home appliances, and monitor home. This paper focuses on the development of a wireless sensor node platform for SHAAL application over WSN which complies with the IEEE 802.15.4 standard and operates in 2.4 GHz ISM （industrial, scientific, and medical） band. The initial stage of SHAAL application development is the design of the wireless sensor node named TelG mote. The main features of TelG mote contributing to the green communications include low power consumption, wearable, flexible, user-friendly, and small sizes. It is then embedded with a self-built operating system named WiseOS to support customized operation. The node can achieve a packet reception rate （PRR） above 80% for a distance of up to 8 m. The designed TelG mote is also comparable with the existing wireless sensor nodes available in the market.展开更多
Boolean control network consists of a set of Boolean variables whose state is determined by other variables in the network. Boolean network is used for modeling complex system. In this paper, we have presented a model...Boolean control network consists of a set of Boolean variables whose state is determined by other variables in the network. Boolean network is used for modeling complex system. In this paper, we have presented a model of a context-aware system used in smart home based on Boolean control networks. This modeling describes the relationship between the context elements (person, time, location, and activity) and services (Morning Call, Sleeping, Guarding, Entertainment, and normal), which is effective to logical inference. We apply semi tensor matrix product to describe the dynamic of the system. This matrix form of expression is a convenient and reasonable way to design logic control system.展开更多
文摘As the smart home is the end-point power consumer, it is the major part to be controlled in a smart micro grid. There are so many challenges for implementing a smart home system in which the most important ones are the cost and simplicity of the implementation method. It is clear that the major share of the total cost is referred to the internal controlling system network; although there are too many methods proposed but still there is not any satisfying method at the consumers＇ point of view. In this paper, a novel solution for this demand is proposed, which not only minimizes the implementation cost, but also provides a high level of reliability and simplicity of operation; feasibility, extendibility, and flexibility are other leading properties of the design.
基金National Natural Science Foundation of China(No. 70971021)
文摘With the emerging of sensor networks, research on sensor-based activity recognition has attracted much attention. Many existing methods cannot well deal with the cases that contain hundreds of sensors and their recognition accuracy is requisite to be further improved. A novel framework for recognizing human activities in smart home was presented. First, small, easy-to-install, and low-cost state change sensors were adopted for recording state change or use of the objects. Then the Bayesian belief network (BBN) was applied to conducting activity recognition by modeling statistical dependencies between sensor data and human activity. An edge-encode genetic algorithm (EEGA) approach was proposed to resolve the difficulties in structure learning of the BBN model under a high dimension space and large data set. Finally, some experiments were made using one publicly available dataset. The experimental results show that the EEGA algorithm is effective and efficient in learning the BBN structure and outperforms the conventional approaches. By conducting human activity recognition based on the testing samples, the BBN is effective to conduct human activity recognition and outperforms the naive Bayesian network (NBN) and multiclass naive Bayes classifier (MNBC).
基金Project supported by the Shanghai Leading Academic Discipline Project (Grant No.J50103)the Innovation Project of Shanghai Universitythe Research Project of Excellent Young Talents in the Universities in Shanghai
文摘Smart home is a promising solution to improving the quality of people＇s life. Much work has been done in the field, but most of these solutions are just based on home gateway, leaving much to be improved. One of its defects is the relatively high energy consuming and its radiation, and the other is that it is not available to the old home appliances which fail to access the internet. Full use of the low energy consuming characteristic of the Zigbee wireless sensor network, a completely new smart home solution is put forward in this paper. Without need of a home gateway and any modification for the currently used family appliances, the method uses the Zigbee coordinator as the central controller and the controllers of appliances as the end devices of Zigbee. It can realize a comfortable and smart home. Experiments show that the scheme proposed is feasible and it will be no doubt to be able to improve the quality of people＇s daily life.
基金supported by the Ministry of Higher Education,Malaysia under Grant No.R.J130000.7823.4L626
文摘The wireless sensor network （WSN） consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potential deployments is in the form of smart home and ambient assisted living （SHAAL）to measure patients or elderly physiological signals, control home appliances, and monitor home. This paper focuses on the development of a wireless sensor node platform for SHAAL application over WSN which complies with the IEEE 802.15.4 standard and operates in 2.4 GHz ISM （industrial, scientific, and medical） band. The initial stage of SHAAL application development is the design of the wireless sensor node named TelG mote. The main features of TelG mote contributing to the green communications include low power consumption, wearable, flexible, user-friendly, and small sizes. It is then embedded with a self-built operating system named WiseOS to support customized operation. The node can achieve a packet reception rate （PRR） above 80% for a distance of up to 8 m. The designed TelG mote is also comparable with the existing wireless sensor nodes available in the market.
文摘Boolean control network consists of a set of Boolean variables whose state is determined by other variables in the network. Boolean network is used for modeling complex system. In this paper, we have presented a model of a context-aware system used in smart home based on Boolean control networks. This modeling describes the relationship between the context elements (person, time, location, and activity) and services (Morning Call, Sleeping, Guarding, Entertainment, and normal), which is effective to logical inference. We apply semi tensor matrix product to describe the dynamic of the system. This matrix form of expression is a convenient and reasonable way to design logic control system.
文摘在全屋智能系统中,各类设备通过互联互通实现对家居环境的协同调节。然而现有的智能家居领域知识分散于各个产品的说明文档中,难以满足用户对智能家居领域复杂问答需求。针对这一挑战,提出了一种基于图神经网络(Graph Neural Networks,GNN)和大语言模型(Large Language Models,LLM)的智能家居产品知识问答系统构建方法。具体而言,首先利用LLM结合提示词工程,从产品说明文档中自动抽取实体和关系,构建全面的智能家居产品知识图谱。然后采用Leiden算法对知识图谱进行高效社区划分,以提高后续推理的效率和准确性。当用户提交查询请求时,系统利用GNN在划分后的子图中进行深度推理,识别问题实体并寻找最优答案路径。最后将路径信息转换为提示词,输入LLM生成自然语言形式的精准回答。实验结果表明,提出的方法能够有效整合和管理智能家居领域的知识,显著提升问答系统生成答案的准确性和相关性,为用户提供更加智能化和个性化的服务体验,具有较高的实用价值。
