AirSenseWare, a sensor-network middleware that provides abstraction models to user applications is described. The abstract modeling and its event-delivering mechanism let a user handle the real world model, instead of...
详细信息
ISBN:
(纸本)9781424415014
AirSenseWare, a sensor-network middleware that provides abstraction models to user applications is described. The abstract modeling and its event-delivering mechanism let a user handle the real world model, instead of a sensor node itself and hide its unexpected dynamic behaviour such as node adding, removing, and position changes. These abstraction models are shareable, which leads the cooperative construction of the real world model. AirSenseWare also serves the application independent maintenance services that lead the easy maintenance for large-scale sensor network infrastructure.
In this paper, we present a sensor Abstraction Layer (SAL) which provides instrument middleware architectures with a consistent and uniform view of heterogenous sensornetworks regardless of the technologies involved....
详细信息
ISBN:
(纸本)9781424415014
In this paper, we present a sensor Abstraction Layer (SAL) which provides instrument middleware architectures with a consistent and uniform view of heterogenous sensornetworks regardless of the technologies involved. SAL is designed to run on sensor gateways (also referred to as base stations) and aggregates multiple sensing technologies. The many hardware disparities and specificities related to accessing, probing and piloting heterogenous sensors are hidden and abstracted by SAL, which in turn offers a single, stable and hardware-independent interface to manage the entire network. The result is a single software library which aggregates multiple heterogenous sensornetworks, hides their disparities, provides consistent access and control functions, and allows middleware software to be technology-independent.
Event detection and monitoring is an important application class for wireless sensornetworks. Traditionally, sensory data are collected and processed at the base-station. Conveying large amounts of multidimensional s...
详细信息
ISBN:
(纸本)9781424415014
Event detection and monitoring is an important application class for wireless sensornetworks. Traditionally, sensory data are collected and processed at the base-station. Conveying large amounts of multidimensional sensory data is however impractical in resource-constrained sensornetworks. In this paper we propose to convert event detection into pattern recognition that is particularly suited for sensornetworks. Individual sensory measurements of sensor nodes are integrated into high-level event pattern, and used for recovering the state of the monitored environment. The pattern storage and pattern recognition operations are performed in a distributed manner within the network. Furthermore, a sleep mode strategy is incorporated for improving performance and prolonging the lifetime of the sensor network.
With the construction of economic and ecological zone around Poyang lake, aquatic vegetation monitoring plays an important role in promoting economic and ecological zone construction. Research on aquatic vegetation mo...
详细信息
With the growth and the development of new applications for Wireless sensornetworks (WSN), sensor nodes are able to handle more complex events that require higher processing performance and hardware flexibility. Thes...
详细信息
ISBN:
(纸本)9783642042836
With the growth and the development of new applications for Wireless sensornetworks (WSN), sensor nodes are able to handle more complex events that require higher processing performance and hardware flexibility. These new features intend to meet the requirements of various applications, as well as to provide customized platforms that have only the needed resources. WSNs often need a flexible architecture able to adapt to design and environment changes. The use of reconfigurable architectures is an alternative to bring more flexibility and more processing capability for the sensor node. This paper proposes a reconfigurable and customizable sensor node called FemtoNode which has a reconfigurable platform and a wireless module to support applications for WSNs, using an object-oriented language Java as specification language of its architecture. The proposed concepts were validated with a case study of an heterogeneous wireless sensor network composed of sensors nodes based on different platforms, whose results are described in this work.
Distributed scalable video coding (DSVC) has recently been gaining many attentions due to its benefits in terms of computational complexity, error resilience and scalability, which are important for emerging video app...
详细信息
ISBN:
(纸本)9781538679630
Distributed scalable video coding (DSVC) has recently been gaining many attentions due to its benefits in terms of computational complexity, error resilience and scalability, which are important for emerging video applications like wireless sensornetworks and visual surveillance system (VSS). In DSVC, the side information (SI) creation plays a key role as it directly affects the DSVC compression performance and the encoder/decoder computational complexity. However, for many VSS applications, the energy of each VSS node is usually attenuating along the time, making the difficulty in transmitting surveillance video in real time. To address this problem, we propose a complexity controlled SI creation solution for the newly DSVC framework. To achieve the flexible SI creation, the complexity associated with SI creation process is modeled using a linear model in which the model parameters are estimated from a fitting process. To adjust the SI complexity, a user parameter is defined based on the availability of the VSS energy resource. Experiments conducted for a rich set of video surveillance data have revealed the benefits of the proposed complexity control solution, notably in both complexity control and compression performance.
A Wireless sensor Network (WSN) is composed of distributed sensors with limited processing capabilities and energy restrictions. These unique attributes pose new challenges amongst which prolonging the WSN lifetime is...
详细信息
The accuracy of original data processing is one of the primary causes that lead to low reliability in detecting system. In this paper Artificial Neural networks (ANN) is studied in order to solve this problem. Aiming ...
详细信息
ISBN:
(纸本)9781424413119
The accuracy of original data processing is one of the primary causes that lead to low reliability in detecting system. In this paper Artificial Neural networks (ANN) is studied in order to solve this problem. Aiming at the limitation of ANN theory in multi-sensorinformation fusion, we propose an improved ART algorithm and use it in environmental detecting system. The experiment shows that it not only improves the reliability of the system, but also optimizes the handling of correlated information and contradictory information.
Minimizing energy consumption of network operations remain a major concern in wireless sensornetworks due to the limited energy capacity embedded in sensor nodes. Clustering has been proposed as a potential solution ...
详细信息
ISBN:
(纸本)0387231978
Minimizing energy consumption of network operations remain a major concern in wireless sensornetworks due to the limited energy capacity embedded in sensor nodes. Clustering has been proposed as a potential solution to address this issue, some nodes being responsible for the data gathering of nodes located in their vicinity. However, in order to avoid inter-cluster interference, neighboring clusters must acquire different frequencies. As the specific constraints of wireless sensornetworks favor a distributed approach, we analyze modified versions of distributed backtracking, distributed weak commitment and randomized algorithms with a focus on energy consumption. In this context. we find that a heuristic may achieve better results than backtracking-based algorithms.
Development of a robust technique for automatic detection of the epileptic seizures is an important goal in clinical neurosciences. In this paper support vector machines (SVM) has been used for this purpose. The syste...
详细信息
ISBN:
(纸本)0780382927
Development of a robust technique for automatic detection of the epileptic seizures is an important goal in clinical neurosciences. In this paper support vector machines (SVM) has been used for this purpose. The system presented detects and uses three features of the electroencephalogram (EEG), namely, energy, decay (damping) of the dominant frequency and cyclostationarity of the signals. The different types of epileptic seizures show some common characteristics in the feature space that can be exploited to distinguish them from normal activity in the brain or the nonepileptic abnormalities. The use of SVMs achieves high sensitivity and at the same time shows an improvement in terms of computational speed in comparison with other traditional systems.
暂无评论