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Actuator Networks
The Experts below are selected from a list of 4446 Experts worldwide ranked by ideXlab platform
Jose Rolim – 1st expert on this subject based on the ideXlab platform
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LCN – Indoor Location for Smart Environments with Wireless Sensor and Actuator Networks
2017 IEEE 42nd Conference on Local Computer Networks (LCN), 2017Co-Authors: Zhongliang Zhao, Stephane Kuendig, Blaise Carron, Torsten Braun, Jose Luis Carrera, Jose RolimAbstract:Smart environments interconnect indoor building environments, indoor wireless sensor and Actuator Networks, smartphones, and human together to provide smart infrastructure management and intelligent user experiences. To enable the “smart” operations, a complete set of hardware and software components are required. In this work, we present Smart Syndesi, a system for creating indoor location-aware smart building environments using wireless sensor and Actuator Networks (WSANs). Smart Syndesi includes an indoor tracking system and a WSAN for environmental monitoring and Actuator activation, interconnected via a gateway with mobile users. The indoor positioning system tracks the real-time location of occupants with high accuracy, which works as a basis for indoor location-based sensor actuation automation. To show how the multiple software/hardware components can be integrated, we implemented a system prototype and performed intensive experiments in indoor office environments.
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Indoor Location for Smart Environments with Wireless Sensor and Actuator Networks
2017 IEEE 42nd Conference on Local Computer Networks (LCN), 2017Co-Authors: Zhongliang Zhao, Stephane Kuendig, Jose Carrera, Blaise Carron, Torsten Braun, Jose RolimAbstract:Smart environments interconnect indoor building environments, indoor wireless sensor and Actuator Networks, smartphones, and human together to provide smart infrastructure management and intelligent user experiences. To enable the “smart” operations, a complete set of hardware and software components are required. In this work, we present Smart Syndesi, a system for creating indoor location-aware smart building environments using wireless sensor and Actuator Networks (WSANs). Smart Syndesi includes an indoor tracking system, a WSAN for indoor environmental monitoring and activation automation, and a gateway interconnecting WSAN, tracking system with mobile users.The indoor positioning system tracks the real-time location of occupants with high accuracy, which works as a basis for indoor location-based sensor actuation automation.To show how the multiple software/hardware components are integrated, we implemented the system prototype and performed intensive experiments in indoor office environments to automate the indoor location-driven environmental sensor monitoring and activation process. The tracked indoor location of a user’s smartphone triggers the retrieval of environmental measurements and activates the Actuators automatically (i.e. turn on/off lights, switch on/off fans) based on the location and correlated environmental sensor information.
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Indoor Location for Smart Environments with Wireless Sensor and Actuator Networks
2017 IEEE 42nd Conference on Local Computer Networks (LCN), 2017Co-Authors: Zhongliang Zhao, Stephane Kuendig, Jose Carrera, Blaise Carron, Torsten Braun, Jose RolimAbstract:Smart environments interconnect indoor building environments, indoor wireless sensor and Actuator Networks, smartphones, and human together to provide smart infrastructure management and intelligent user experiences. To enable the “smart” operations, a complete set of hardware and software components are required. In this work, we present Smart Syndesi, a system for creating indoor location-aware smart building environments using wireless sensor and Actuator Networks (WSANs). Smart Syndesi includes an indoor tracking system and a WSAN for environmental monitoring and Actuator activation, interconnected via a gateway with mobile users. The indoor positioning system tracks the real-time location of occupants with high accuracy, which works as a basis for indoor location-based sensor actuation automation. To show how the multiple software/hardware components can be integrated, we implemented a system prototype and performed intensive experiments in indoor office environments.
Jiro Nakamura – 2nd expert on this subject based on the ideXlab platform
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Autonomic Wireless Sensor/Actuator Networks for Tracking Environment Control Behaviors
, 2020Co-Authors: Masayuki Nakamura, Jiro Nakamura, Atsushi Sakurai, Morinosato WakamiyaAbstract:To develop energy-saving environment control systems, we propose autonomic wireless sensor/Actuator Networks that classify a user’s behaviors in relation to environment control such as lighting, and that configure themselves depending on sensor node selection. In our system, a wireless remote control node monitors a user’s actions with respect to environment control, and occupancy sensor Networks simultaneously detect the user’s movement. The system learns the relationship between the responses of the remote control node and the occupancy sensor Networks to classify the user’s behaviors with only the occupancy sensor Networks. The system chooses informative sensor nodes for this behavior classification based on an information gain criterion. These chosen nodes have a high sensing cost. Sensor network routing is controlled based on the sensing cost and communication cost metric. In the resultant sensor Networks, the sensing performance is the same as that in the original network, but the resources are successfully allocated to the nodes. In addition, less informative and redundant nodes are identified. We demonstrate tracking environment control behaviors and sensor node selection using the sensor/Actuator Networks testbed.
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distributed environment control using wireless sensor Actuator Networks for lighting applications
Sensors, 2009Co-Authors: Masayuki Nakamura, Atsushi Sakurai, Jiro NakamuraAbstract:We propose a decentralized algorithm to calculate the control signals for lights in wireless sensor/Actuator Networks. This algorithm uses an appropriate step size in the iterative process used for quickly computing the control signals. We demonstrate the accuracy and efficiency of this approach compared with the penalty method by using Mote-based mesh sensor Networks. The estimation error of the new approach is one-eighth as large as that of the penalty method with one-fifth of its computation time. In addition, we describe our sensor/Actuator node for distributed lighting control based on the decentralized algorithm and demonstrate its practical efficacy.
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CSTST – Adaptive sensor/Actuator Networks for tracking environment control behaviors
Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology – CSTST '08, 2008Co-Authors: Masayuki Nakamura, Atsushi Sakurai, Takumi Yamada, Jiro NakamuraAbstract:To develop an energy-saving environment control system, we propose wireless sensor/Actuator Networks which classify the user’s behaviors for environment control such as lighting and configure the network according to sensor node selection. In our system, a wireless remote control node monitors the user’s environment control actions and occupancy sensor Networks detect the user’s movement simultaneously. The system learns the relationship among the responses of the remote control node and the occupancy sensor Networks to classify the user’s behaviors only with the occupancy sensor Networks. The system chooses informative sensor nodes for the behavior classification based on the information gain criterion. These chosen nodes have high sensing cost. Sensor network routing is controlled based on the sensing cost and communication cost metric. In the resultant sensor Networks, the sensing performance is the same as that in the original network, but the resources are successfully allocated to the nodes. In addition, less informative and redundant nodes are identified. We demonstrate tracking environment control behaviors and sensor node selection using the sensor/Actuator Networks testbed.
Mohamed Eltoweissy – 3rd expert on this subject based on the ideXlab platform
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MASS – TARP: A Trust-Aware Routing Protocol for Sensor-Actuator Networks
2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems, 2007Co-Authors: Abdelmounaam Rezgui, Mohamed EltoweissyAbstract:Most routing protocols for sensor-Actuator Networks (SANETs) are built under the assumption that nodes normally cooperate in forwarding each other’s messages. In practice, this assumption is not realistic; SANETs are environments where nodes may or may not cooperate. For several reasons, a node may fail to operate as planned at deployment time. As a result, when actually deployed, protocols and applications may not be as efficient as expected. In this paper, we present TARP (Trust-Aware Routing Protocol), a routing protocol for sensor-Actuator Networks that exploits past nodes’ routing behavior and links’ quality to determine efficient paths. We implemented TARP in a TinyOS-based SANET and conducted several experiments to evaluate its performance. The obtained results confirmed that TARP achieves substantial improvements in terms of energy consumption and scalability.
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TARP: A Trust-Aware Routing Protocol for Sensor-Actuator Networks
2007 IEEE International Conference on Mobile Adhoc and Sensor Systems, 2007Co-Authors: Abdelmounaam Rezgui, Mohamed EltoweissyAbstract:Most routing protocols for sensor-Actuator Networks (SANETs) are built under the assumption that nodes normally cooperate in forwarding each other’s messages. In practice, this assumption is not realistic; SANETs are environments where nodes may or may not cooperate. For several reasons, a node may fail to operate as planned at deployment time. As a result, when actually deployed, protocols and applications may not be as efficient as expected. In this paper, we present TARP (Trust-Aware Routing Protocol), a routing protocol for sensor-Actuator Networks that exploits past nodes’ routing behavior and links’ quality to determine efficient paths. We implemented TARP in a TinyOS-based SANET and conducted several experiments to evaluate its performance. The obtained results confirmed that TARP achieves substantial improvements in terms of energy consumption and scalability.
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A service-oriented query architecture for sensor-Actuator Networks
2006 2nd IEEE Workshop on Wireless Mesh Networks, 2006Co-Authors: Abdelmounaam Rezgui, Mohamed EltoweissyAbstract:Current architecture and programming paradigms are not able to support the requirements of emerging sensor- Actuator applications. In this paper, we discuss those requirements and propose service-oriented sensor-Actuator Networks (SANETs) as a novel programming and querying paradigm that is able to cope with the requirements of future sensor-Actuator systems.