Formal Probabilistic Analysis of a Wireless Sensor Network for Forest Fire Detection

Wireless Sensor Networks (WSNs) have been widely explored for forest fire detection, which is considered a fatal threat throughout the world. Energy conservation of sensor nodes is one of the biggest challenges in this context and random scheduling is frequently applied to overcome that. The performance analysis of these random scheduling approaches is traditionally done by paper-and-pencil proof methods or simulation. These traditional techniques cannot ascertain 100% accuracy, and thus are not suitable for analyzing a safety-critical application like forest fire detection using WSNs. In this paper, we propose to overcome this limitation by applying formal probabilistic analysis using theorem proving to verify scheduling performance of a real-world WSN for forest fire detection using a k-set randomized algorithm as an energy saving mechanism. In particular, we formally verify the expected values of coverage intensity, the upper bound on the total number of disjoint subsets, for a given coverage intensity, and the lower bound on the total number of nodes.Comment: In Proceedings SCSS 2012, arXiv:1307.802

AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades

A wireless sensor network system deployment for detecting stick slip motion in glaciers

The behaviour of glaciers is an area in which only limited research has been carried out due to the difficulties of monitoring sub-glacial movements. The authors believe that this can be addressed by the deployment of a wireless sensor network, consisting of heterogeneous sensors to instrument this activity. By deploying a sensor network measurements can be taken for a longer period than would otherwise be possible. The initial designs for this sensor network are presented along with details of some of the challenges posed by the project

Optimizing Sensing: From Water to the Web

Where should we place sensors to quickly detect contamination in drinking water distribution networks? Which blogs should we read to learn about the biggest stories on the Web? Such problems are typically NP-hard in theory and extremely challenging in practice. The authors present algorithms that exploit submodularity to efficiently find provably near-optimal solutions to large, complex real-world sensing problems

Considering Pigeons for Carrying Delay Tolerant Networking based Internet traffic in Developing Countries

There are many regions in the developing world that suffer from poor infrastructure and lack of connection to the Internet and Public Switched Telephone Networks (PSTN). Delay Tolerant Networking (DTN) is a technology that has been advocated for providing store-and-forward network connectivity in these regions over the past few years. DTN often relies on human mobility in one form or another to support transportation of DTN data. This presents a socio-technical problem related to organizing how the data should be transported. In some situations the demand for DTN traffic can exceed that which is possible to support with human mobility, so alternative mechanisms are needed. In this paper we propose using live carrier pigeons (columba livia) to transport DTN data. Carrier pigeons have been used for transporting packets of information for a long time, but have not yet been seriously considered for transporting DTN traffic. We provide arguements that this mode of DTN data transport provides promise, and should receive attention from research and development projects. We provide an overview of pigeon characteristics to analyze the feasibility of using them for data transport, and present simulations of a DTN network that utilizes pigeon transport in order to provide an initial investigation into expected performance characteristics

Application of Computational Intelligence Techniques to Process Industry Problems

In the last two decades there has been a large progress in the computational intelligence research field. The fruits of the effort spent on the research in the discussed field are powerful techniques for pattern recognition, data mining, data modelling, etc. These techniques achieve high performance on traditional data sets like the UCI machine learning database. Unfortunately, this kind of data sources usually represent clean data without any problems like data outliers, missing values, feature co-linearity, etc. common to real-life industrial data. The presence of faulty data samples can have very harmful effects on the models, for example if presented during the training of the models, it can either cause sub-optimal performance of the trained model or in the worst case destroy the so far learnt knowledge of the model. For these reasons the application of present modelling techniques to industrial problems has developed into a research field on its own. Based on the discussion of the properties and issues of the data and the state-of-the-art modelling techniques in the process industry, in this paper a novel unified approach to the development of predictive models in the process industry is presented