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
ZigBee无线通信技术在智能家居组网中具有重要的应用。为了探究其使用场景和方法,文章首先分析了基于ZigBee的智能家居网络组网方式,其次介绍了接收信号强度指示(Received Signal Strength Indicator,RSSI)算法的测距原理和DV-Hop算法...ZigBee无线通信技术在智能家居组网中具有重要的应用。为了探究其使用场景和方法,文章首先分析了基于ZigBee的智能家居网络组网方式,其次介绍了接收信号强度指示(Received Signal Strength Indicator,RSSI)算法的测距原理和DV-Hop算法的测点原理,最后针对两种算法的局限性,提出基于阈值的改进定位算法。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
The topology of in-home power line communication(PLC) networks varies frequently, which makes traditional routing algorithms failure. To solve this problem, an end-to-end transmission time for remaining path(TTRP) met...The topology of in-home power line communication(PLC) networks varies frequently, which makes traditional routing algorithms failure. To solve this problem, an end-to-end transmission time for remaining path(TTRP) metric-based opportunistic routing(TTRPOR) is proposed. Since a local broadcasting scheme is adopted, the algorithm can find the optimal path for forwarding packets in a dynamic PLC network. The closed-form of the outage probability for a PLC channel is derived to estimate the TTRP. It is proved that the average throughput can achieve maximum as the metric TTRP is utilized to sort candidate forwarding nodes.Numerical results show that the end-to-end throughput of networks with TTRPOR, outperforms that of the network adopting DSR and EXOR, especially for the case of varying-topology in-home PLC networks.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ZigBee无线通信技术在智能家居组网中具有重要的应用。为了探究其使用场景和方法,文章首先分析了基于ZigBee的智能家居网络组网方式,其次介绍了接收信号强度指示(Received Signal Strength Indicator,RSSI)算法的测距原理和DV-Hop算法的测点原理,最后针对两种算法的局限性,提出基于阈值的改进定位算法。
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.
基金supported in part by Open Research Fund of National Key Laboratory of Electromagnetic EnvironmentChina Research Institute of Radiowave Propagation (Grant No. 201500013)+3 种基金Open Research Fund of National Mobile Communications Research LaboratoryJiangsu Provincial Science Foundation Project (Grant No. BK20150786)Southeast University (Grant No. 2013D02)National Natural Science Foundation of China (Grants Nos. 61501238, 61271230, 61472190)
文摘The topology of in-home power line communication(PLC) networks varies frequently, which makes traditional routing algorithms failure. To solve this problem, an end-to-end transmission time for remaining path(TTRP) metric-based opportunistic routing(TTRPOR) is proposed. Since a local broadcasting scheme is adopted, the algorithm can find the optimal path for forwarding packets in a dynamic PLC network. The closed-form of the outage probability for a PLC channel is derived to estimate the TTRP. It is proved that the average throughput can achieve maximum as the metric TTRP is utilized to sort candidate forwarding nodes.Numerical results show that the end-to-end throughput of networks with TTRPOR, outperforms that of the network adopting DSR and EXOR, especially for the case of varying-topology in-home PLC networks.
