6 resultados para Active pixel sensor

em Deakin Research Online - Australia


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An angle measuring device using a high performance and very compact accelerometer provides a new and exciting method for producing highly compact and accurate angle measuring devices. Accelerometers are micro-machined and are able to measure acceleration to a very high accuracy. By using gravity as a reference these compact devices can also be used for measuring angles of rotation. The inherent problem with these devices is that their response characteristic changes with temperature which is detrimental to measurement accuracy. This paper describes an effective method to overcome this problem using a temperature sensor and intelligent software to compensate for this drift characteristic. In order to demonstrate the effectiveness of this work, experiments have been developed and conducted with the results and analysis provided at the end
of this paper for discussion.

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Medium access control for wireless sensor networks has been an active
research area in the past decade. This chapter discusses a set of important medium access control (MAC) attributes and possible design trade-offs in protocol design, with an emphasis on energy efficiency. Then we categorize existing MAC protocols into five groups, outline the representative protocols, and compare their advantages and disadvantages in the context of wireless sensor network. Finally, thoughts for practitioners are presented and open research issues are also discussed.

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Wireless sensor networks (WSNs) are deployed in numerous mission critical applications in which the network needs to remain active for as long as possible while delivering quality information to a base station. However, WSNs suffer from a wide range of attacks due to their limited processing and energy capabilities. Their resiliency, however, depends on fast recovery from such attacks being achieved. In recent work, the authors developed and implemented clustering, reprogramming and authentication protocols involved in recovering stationary WSNs with low resources. In this paper, we determine the additional resources required in implementing these protocols in a mobile WSN.

We present recovery protocols on TinyOS motes for a low-resourced, mobile deployment. We describe the issues we encountered in the implementation. We present times, RAM and ROM needed to run the recovery protocols and compare these with the stationary case, demonstrating that the additional cost of reprogramming in a mobile WSN is less than 25% of that in a stationary WSN and the additional cost of re-clustering in a mobile WSN is less than 9% of that in a stationary WSN. Authentication has an insignificant cost increase.

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Maximum target coverage with minimum number of sensor nodes, known as an MCMS problem, is an important problem in directional sensor networks (DSNs). For guaranteed coverage and event reporting, the underlying mechanism must ensure that all targets are covered by the sensors and the resulting network is connected. Existing solutions allow individual sensor nodes to determine the sensing direction for maximum target coverage which produces sensing coverage redundancy and much overhead. Gathering nodes into clusters might provide a better solution to this problem. In this paper, we have designed distributed clustering and target coverage algorithms to address the problem in an energy-efficient way. To the best of our knowledge, this is the first work that exploits cluster heads to determine the active sensing nodes and their directions for solving target coverage problems in DSNs. Our extensive simulation study shows that our system outperforms a number of state-of-the-art approaches.

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Recognition of multiple moving objects is a very important task for achieving user-cared knowledge to send to the base station in wireless video-based sensor networks. However, video based sensor nodes, which have constrained resources and produce huge amount of video streams continuously, bring a challenge to segment multiple moving objects from the video stream online. Traditional efficient clustering algorithms such as DBSCAN cannot run time-efficiently and even fail to run on limited memory space on sensor nodes, because the number of pixel points is too huge. This paper provides a novel algorithm named Inter-Frame Change Directing Online clustering (IFCDO clustering) for segmenting multiple moving objects from video stream on sensor nodes. IFCDO clustering only needs to group inter-frame different pixels, thus it reduces both space and time complexity while achieves robust clusters the same as DBSCAN. Experiment results show IFCDO clustering excels DBSCAN in terms of both time and space efficiency. © 2008 IEEE.

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Traditional tracking solutions in wireless sensor networks based on fixed sensors have several critical problems. First, due to the mobility of targets, a lot of sensors have to keep being active to track targets in all potential directions, which causes excessive energy consumption. Second, when there are holes in the deployment area, targets may fail to be detected when moving into holes. Third, when targets stay at certain positions for a long time, sensors surrounding them have to suffer heavier work pressure than do others, which leads to a bottleneck for the entire network. To solve these problems, a few mobile sensors are introduced to follow targets directly for tracking because the energy capacity of mobile sensors is less constrained and they can detect targets closely with high tracking quality. Based on a realistic detection model, a solution of scheduling mobile sensors and fixed sensors for target tracking is proposed. Moreover, the movement path of mobile sensors has a provable performance bound compared to the optimal solution. Results of extensive simulations show that mobile sensors can improve tracking quality even if holes exist in the area and can reduce energy consumption of sensors effectively.