Poster Abstract: Practical issues in image acquisition and transmission over wireless sensor network

Multimedia data have become an important objective in wireless sensor networks. Due to the node resource constraints (energy consumption, memory capacity, network latency and throughput) the incorporation of image sensor at the nodes is currently a challenge. In this paper, we study different node architectures, evaluating processing time, energy consumption, image quality and data delivery issues. The study shows that a specialized image co-processor is an optimal solutionJUnta de Andalucía P07-TIC-0247

A new CBIR technology to help reassembling moorish ornamental carvings (atauriques)

Este trabajo presenta una nueva tecnología de correspondencia de imágenes especialmente concebida para facilitar la reconstrucción de atauriques a partir las imágenes de sus fragmentos. El método localiza piezas similares en base a su contenido ornamental, ignorando la forma de su fractura. Para ello se propone una técnica de texturización que realza este contenido. Además, se propone una modificación del algoritmo de cálculo de características de Fourier clásico para mejorar la tasa de éxito y preservar la información de escala. Los resultados demuestran que esta tecnología es adecuada para filtrar o reducir el número de candidatos en un proceso de restauración basado en técnicas de reconstrucción por puzles.In this paper, we present a new Content Based Image Retrieval technology specially designed to help reassemble archaeological pieces. The method finds similar fragments based on the fragment content not the shape of the fracture. A texturization method is proposed to enhance this content. Furthermore, classic Fourier features computation is modified to increase the success matching, and preserve the scaling information. The results show that this technology is suitable to filter candidates in a puzzle-solving tool when the number of fragments is huge

Automatic Lesser Kestrel’s Gender Identification using Video Processing

Traditionally, animal surveillance is a common task for biologists. However, this task is often accompanied by the inspection of huge amounts of video. In this sense, this paper proposes an automatic video processing algorithm to identify the gender of a kestrel species. It is based on optical flow and texture analysis. This algorithm makes it possible to identify the important information and therefore, minimizing the analysis time for biologists. Finally, to validate this algorithm, it has been tested against a set of videos, getting good classification results.Junta de Andalucía P10-TIC-570

mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks

Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, experimental evaluation is a very time-consuming task. It depends on many factors, such as the use of the radio transceiver or the distance between nodes. Simulations reduce considerably this time. They allow the evaluation of the network behavior before its deployment. This article presents a simulation tool which helps developers to obtain information about battery state. This simulator extends the well-known TOSSIM simulator. Therefore it is possible to evaluate TinyOS applications using an accurate model of the battery consumption and its relation to the radio power transmission. Although an specific indoor scenario is used in testing of simulation, the simulator is not limited to this environment. It is possible to work in outdoor scenarios too. Experimental results validate the proposed model.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570

Implementing a distributed WSN based on IPv6 for ambient monitoring

Traditionally,Wireless SensorNetworks (WSNs) are used for monitoring an extensive area. In these networks, a centralized server is usually used to collect and store the sensor information.However, new distributed protocols allow connections directly to theWSN nodes without the need of a centralized server.Moreover, these systems are able to establish communications among heterogeneous networks.The new protocols strategy is focused on considering several WSNs as a unique distributed one.This way, a user of the system is able to analyze a process under study as a whole instead of considering it as a set of different subsystems. This is the case in the evaluation of migratory waterbirds’ environment. In this case, it is usual to deploy severalWSNs in different breeding areas. They are all interconnected and they measure different environmental parameters. However, this improvement in the data access flexibility may result in a loss of network performance and an increase in network power consumption. Focused on this problem, this paper evaluates different communication protocols: distributed and centralized, in order to determine the best trade-off for environmental monitoring in different migratory areas of waterbirds

Phase topology identification in low-voltage distribution networks: a Bayesian approach

Knowledge of customer phase connection in low-voltage distribution networks is important for Distribution System Operators (DSOs). This paper presents a novel data-driven phase identification method based on Bayesian inference, which uses load consumption profiles as inputs. This method uses a non-linear function to establish the probability of a customer being connected to a given phase, based on variations in the customer’s consumption and those in the phase feeders. Owing to the Bayesian inference, the proposed method can provide up-to-date certainty about the phase connection of each customer. To improve the detection of those customers that are more difficult to identify, after obtaining the up-to-date certainty for all users, the consumption of those who have an up-to-date certainty above a certain percentile compared with the rest of the substation (those that are more likely to be correctly classified) is subtracted from the phase in which they are classified. The performance of the proposed method was evaluated using a real (non-synthetic) low-voltage distribution network. Favourable results (with accuracies higher than 97 %) were obtained in almost all cases, regardless of the percentage of Smart Meter penetration and the size of the substation. A comparison with other state-of-the-art methods showed that the proposed method outperforms (or equals) them. The proposed method does not necessarily require previously labelled data; however, it can handle them even if they contain errors. Having previous information (partial or complete) increases the performance of phase identification, making it possible to correct erroneous previous labelling

Five years of designing wireless sensor networks in the Doñana Biological Reserve (Spain): an applications approach

Wireless Sensor Networks (WSNs) are a technology that is becoming very popular for many applications, and environmental monitoring is one of its most important application areas. This technology solves the lack of flexibility of wired sensor installations and, at the same time, reduces the deployment costs. To demonstrate the advantages of WSN technology, for the last five years we have been deploying some prototypes in the Doñana Biological Reserve, which is an important protected area in Southern Spain. These prototypes not only evaluate the technology, but also solve some of the monitoring problems that have been raised by biologists working in Doñana. This paper presents a review of the work that has been developed during these five years. Here, we demonstrate the enormous potential of using machine learning in wireless sensor networks for environmental and animal monitoring because this approach increases the amount of useful information and reduces the effort that is required by biologists in an environmental monitoring task