The D3S group at the University of Trento, Italy, invites applications for a post‐doctoral research position in wireless sensor networks.
In the context of WSNs, the D3S has been successful in bringing research results into real‐world, long‐term, operational deployments. Examples are the structural health monitoring of a medieval tower, and the closed‐loop control of lighting in a road tunnel. The scientific results of these projects received the Best Paper Award at IPSN (both in 2009 and 2011) and the Mark Weiser Best Paper Award at PerCom 2012. The WSN-based system deployed in the road tunnel has been granted an EU patent.
Other ongoing projects include: i) a project aimed at large-scale monitoring of the environment and the wildlife dwelling in it; ii) a cross-disciplinary project on smart spaces, iii) a follow-up project of the road tunnel deployment, investigating energy-harvesting devices and wireless actuation.
Although we emphasize real-world applications as a motivation and a concrete opportunity for the validation of our research, the latter is not limited to the immediate needs of WSN deployments. We perform a mix of curiosity-driven and application-driven research. The research challenges tackled by D3S span a broad set of topics, ranging from low-layer issues concerned with the characterization and design of communication protocols to higher-layer issues related with programming platforms and software achitectures for WSNs.
The successful candidate is expected to propose ideas and lead scientific efforts on ongoing research topics, and to coordinate the related activities of junior members of the team.
More information available here
The D3S group invites applications for two PhD positions in wireless sensor networks (WSNs). D3S is a cross-institution research group focusing on dynamic, decentralized, distributed systems.
In the context of WSNs, the D3S group has been particularly successful in bringing research results into real-world, long-term, operational deployments. Examples are the structural health monitoring of a medieval tower, and the closed-loop control of lighting in a road tunnel. The scientific results of these projects received the Best Paper Award at IPSN (both in 2009 and 2011) and the Mark Weiser Best Paper Award at PerCom 2012.
Other ongoing projects include: i) a project aimed at large-scale monitoring of the environment and the wildlife dwelling in it; ii) a cross-disciplinary project on smart spaces; iii) a follow-up project of the road tunnel deployment, investigating energy-harvesting devices and wireless actuation.
Although we emphasize real-world applications as a motivation and a concrete opportunity for the validation of our research, the latter is not limited to the immediate needs of WSN deployments. We perform a mix of curiosity-driven and application-driven research. The research challenges tackled by D3S span a broad set of topics, ranging from low-layer issues concerned with the characterization and design of communication protocols to higher-layer issues related with programming platforms and software architectures for WSNs.
New PhD students are invited to participate in ongoing projects to gain experience and insight into real systems, and to identify novel, challenging problems whose solutions break new grounds. The D3S group, and Trento at large, provide a fertile environment for high-quality research: two of our PhD students received the Best Ph.D. Thesis Award at the European Conference on Wireless Sensor Networks (EWSN) in 2009 and 2012.
More info about the positions here.
This book constitutes the refereed proceedings of the First International Conference on Wireless Sensor Networks for Developing Countries, WSN4DC 2013, held in Jamshoro, Pakistan, in April 2013.
The 10 revised full papers presented were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on WSN applications/services for developing countries; mobile WSN; underwater WSN; VANETS; body area networks; energy harvesting in WSN; WSN and cloud integration; WSN and IoT; QoS and Qot; WSN MAC, network and transport protocols; cross layer approaches; security aspects in WSN; WSN applications in smart grid and energy management; WSN in structural health monitoring.
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A team of researchers at National Taiwan University has developed a sensor for embedding in a single tooth. The sensor as the team explains in their study paper records movement using an accelerometer to identify different oral activities such as chewing, smoking, coughing, etc. The team presented their sensor at this year’s International Symposium on Wearable Computers held early this month in Switzerland.
As scientists develop ways to make electronics smaller, researchers find new ways to use them. In this new effort, the team in Taiwan has developed a sensor that is small enough to fit inside of an artificial tooth, or to sit astride a natural one. The current sensor developed by the team uses very tiny wires to carry data from the sensor to a computer—future versions will use Bluetooth to allow for a wireless implementation.
The sensor measures jaw movement, and because of that is able to identify different types of oral activities. Currently it is capable of recognizing (after calibration for each individual) the difference between chewing, smoking, coughing, eating and drinking. This, the researchers say, could be invaluable to dentists, doctors and other scientists. The device would allow a dentist, for example, to monitor teeth grinding, a doctor to verify how much a person is eating or smoking, and a behavioral scientist to measure stress levels.
To verify the accuracy of the device, the research team enlisted the assistance of eight volunteers—each had a sensor affixed to a tooth and then was asked to perform several different activities (cough, chew gum, etc.) for approximately 30 seconds each while the computer analyzed the data and made a personal profile for them. Afterwards, each of the volunteers was then asked to engage in the various oral activities and the researchers report that the sensor and computer were 93.8 percent accurate in determining which activity was being performed.
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Around the world, the increased use of sensors — and the data insights they provide — is leading to better management of resources and increased efficiency. A recent article on Forbes.com highlights how IBM is creating smarter cities with sensor technology. The article also discusses how advanced application of sensors can be used to address any number of everyday urban challenges from finding a parking space to increasing access to critical information in the wake of a natural disaster.
Unfortunately, the widespread use of sensors can still be cost-prohibitive. Few organizations can afford to spend hundreds or thousands of dollars per sensor and companies need to be working hard on the idea of bringing the cost down to an affordable level. The key is to make it easier and cheaper for everyone to gain access to the sensor space.
Besides cost, there are two other barriers hampering the widespread adoption of sensors. The first is that much of the sensor industry is focused on the sensor base or the sensors themselves rather than combining all the components to present a complete solution. In many cases the end user or system integrator must put together different components, write the software and then embed it with the sensor hardware.
The second area of focus for many vendors is the big push for cloud-based data collection systems. However, many of these are generic APIs that work with any platform that is configured to use them. By themselves they are good ways to visualize your data, but not in the context of any real analysis or domain-specific expertise.
The reality is the end user needs both preconfigured hardware and cloud-based monitoring combined to serve a specific purpose. Users want sensors solutions that are easy to install and setup with clear instructions that explain what they’re capable of doing. They also need sensors that are easy to connect to other software and can integrate seamlessly with sensors from multiple vendors.
To be successful, organizations need to provide cheap, easy, and complete solutions that are broad enough to work with other systems. Sensors and the valuable insights they provide could be the key to smarter, more efficient cities and societies. It’s vital to develop integrated systems that are more affordable and readily available.
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This presentation covers various characteristics of a wireless sensor network in monitoring an unattended area. Results of how wireless sensor network topologies can be effectively used for physically accessible areas are presented. Minimizing packet traffic by collecting data using a mobile Base Station is discussed, along with energy consumption. An innovative technique of distributing keys for shared secret key based communications is described, and various characteristics including resiliency, and monitoring a battle-field using wireless sensor networks are outlined. Analytical model is introduced and compared with simulation results. The need for layered sensing in secured communications is investigated.
Free access compliments of: Academic Press
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Researchers are developing a wireless sensor network (WSN) designed to spot faults in electricity sub-stations that can lead to power cuts. The EPSRC-funded team will develop a WSN capable of sensing partial discharge (PD) in electricity sub-stations, a situation that occurs when the insulation of cables and other power equipment becomes old or damaged. Left unchecked, partial discharge can lead to dangerous and destructive faults including explosions and power cuts. Designed to be monitored centrally, the new WSN will allow operators to replace planned maintenance with condition-based maintenance.
Ian Glover, the new Professor of Radio Science and Wireless Systems Engineering at Huddersfield University told The Engineer via email that the traditional approach to PD detection using free-standing radio receivers has been to measure the difference in time-of-flight from the PD source to a set of spatially separated receivers.
‘The difference in the times-of-flight are found by cross-correlating the noise-like time waveforms arriving at the different receivers with each other,’ he said. ‘The difference in the times-of-flight for a pair of receivers defines a locus of points on which the source of PD could lie. Multiple loci, resulting from multiple pairs of receivers, intersect which gives the location of the source.’ The 4.5 year project, which has received £670,000 in funding, aims to develop a system that relies principally on measurement of PD signal amplitude and does not rely on time measurements. One challenge, said Prof Glover, will be to make the sensors sensitive enough to detect PD at a useful range without requiring sophisticated signal processing, such as the cross-correlation used in the time-of-flight approach. He said, ‘Such signal processing is power hungry and these sensors will probably need to be powered using energy harvesting technologies – solar cells, vibration, stray electric and magnetic fields, for example – if they are not to require expensive maintenance.’
Another challenge, he said, is that the attenuation [loss] of the PD signal in propagating from source to receiver may vary significantly, even for paths of the same length due to the complex propagation environment of the substation.
‘This means that the location of the PD source is almost certainly not possible by simply inverting a path loss law since the path loss law will be unknown,’ said Prof Glover. ‘It may be that we have to ‘calibrate’ our sensors using an emulated PD signal. This itself will require power and may further challenge the energy harvesting solution to maintenance avoidance.’
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