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We propose a novel vision for roadway safety warning based on sensor networks, aiming at providing user-friendly zero-delay safety warnings to motorists.
We conclude that roadway safety warning based on sensor networks is a promising idea for realizing ITS's "Zero Fatality, Zero Delay" roadway safety philosophy.
This work presents and validates a design model for monitoring and diagnosis systems based on sensor networks exploiting potentialities of the holonic approach.
Starting from three standard methods to implement the novel estimation algorithms based on sensor networks for distributed parameter systems, in the discretized version of them, we are showing what is the better method to increase the quality of estimation, related to the complexity of implementation.
The following applications and extensions are suggested: applications in fault detection and diagnosis of distributed parameter systems based on sensor networks and virtual instrumentation, allowing the treatment of large and complex systems with many variables, and also on learning and extrapolation.
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Fault tolerance is a key research area for many of applications such as those based on sensor network technologies.
In the third paper, "Determining localized tree construction schemes based on sensor network lifetime," Lee et al. study the network lifetime of different localized data gathering tree formation algorithms by considering the communication overhead due to imperfect link quality.
This project developed a wireless hybrid network testbed to assess cross-layer interactions in heterogeneous wireless systems based on sensor and mesh networks.
With the wireless sensor networks booming, various researches based on wireless sensor networks have made great progress [1 10], such as the physical sensors [11], architecture for the service computing [12], fault-tolerant optimization [13], data gathering and compression [14], and smart data analysis [15].
Payments and micropayments: Automated payments to business network participants based on sensor data (indicating, for example, service completion or product delivery), as well as micropayments between devices themselves in certain networks for functions and capabilities — all without human involvement.
A model for bacterial population evaluation was built by using a back propagation neural network (BPNN) based on sensor responses from the E-nose.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com