Multifunctional Sensor to Detect Environmental Parameters

Pallaro, Nereo; Visintainer, Filippo; Darin, Marco; Mosca, Emilio

doi:10.1007/978-3-540-76989-7_18

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…In this regard, the appropriate sensor devices described in [38][39][40] were taken as prototypes during the development of the observer structure and consequent simulation. The fuzzy inference system "Environment" is intended for monitoring the already obtained friction coefficient to assess the possible changes in road parameters due to the current weather.…”

Section: Monitoring Of Road Parameters By Environmental Conditionsmentioning

confidence: 99%

Fuzzy evaluation of tyre–surface interaction parameters

Ivanov

Shyrokau

Augsburg

et al. 2010

Journal of Terramechanics

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Section: Monitoring Of Road Parameters By Environmental Conditionsmentioning

confidence: 99%

Fuzzy evaluation of tyre–surface interaction parameters

Ivanov

Shyrokau

Augsburg

et al. 2010

Journal of Terramechanics

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Modeling and analysis for time redundant systems with a given mission window

Cui

Shen

2019

Computers & Industrial Engineering

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Quasi-optimal scheduling algorithm for area coverage in multi-functional sensor networks

Molnár

Simon

Gönczy

2013

IJAHUC

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Wireless Sensor Networks (WSNs) are widely used to perform measurement and monitoring tasks in large sensing fields. Several applications require every point in the monitored area to be covered by at least k sensors (k-coverage problem) for measurement accuracy or robustness. In heterogeneous multi-functional sensor networks, p parallel observation tasks are performed with p types of sensors, each task having its own ki(i = 1, 2, . . . , p) coverage requirement, assuming that multi-functional sensors are used which may have multiple measurement capabilities (multi-k-coverage problem). In order to prolong the lifetime of the network, active and sleeping states of sensors can be altered while maintaining the required coverage for all sensing tasks. In this paper an efficient distributed sensor state scheduling algorithm for multi-functional WSNs is proposed to solve the multi-k-coverage problem. The proposed multi-functional controlled greedy sleep algorithm is the generalisation of a recently proposed quasi-optimal scheduling algorithm. It is easy to implement and solves the common scheduling problem of heterogeneous multi-functional sensor networks. It has low local communication overhead and can adapt to dynamic changes in the network, while the required network-wide coverage for all sensing tasks is guaranteed as long as it is physically possible. The performance and the fault tolerance of the algorithm are illustrated by simulation examples.

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Multifunctional Sensor to Detect Environmental Parameters

Cited by 3 publications

References 2 publications

Fuzzy evaluation of tyre–surface interaction parameters

Fuzzy evaluation of tyre–surface interaction parameters

Modeling and analysis for time redundant systems with a given mission window

Quasi-optimal scheduling algorithm for area coverage in multi-functional sensor networks

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