Lightweight method of shuffling overlapped data-blocks for data integrity and security in WSNs

Wireless Sensor Networks (WSN) consist of devices with limited resources to explore and sense the environment in a cooperative way. Security, mainly in terms of guaranteeing the data integrity, is a primary issue for many applications, but with an extra energy cost. Thus, trade-off is required between security level and energy consumption in real applications. First of all, a brief survey about security methods, focusing in data integrity, in WSN is implemented. The objective of this paper is to propose a new data integrity method with medium security levels and low energy cost. Therefore, we propose a new and lightweight mechanism for data integrity with overlapping blocks in WSNs. Hence, an attacker will spend much time and effort to interpret and alter the packets. The experiments were performed using TinyOS 2.1 operating system and TelosB nodes for measuring the overhead in terms of energy consumption, memory, and packet size. Moreover, the receiver is able to detect tampering packets and request those retransmission data. An attacker would require huge amounts of memory and processing time to extract the original information, even for small-sized data blocks. Thus, this fact makes this approach a simple, yet effective, mechanism to protect data whilst enhancing the data integrity

Homomorphic Filtering for Improving Time Synchronization in Wireless Networks

Wireless sensor networks are used to sample the environment in a distributed way. Therefore, it is mandatory for all of the measurements to be tightly synchronized in order to guarantee that every sensor is sampling the environment at the exact same instant of time. The synchronization drift gets bigger in environments suffering from temperature variations. Thus, this work is focused on improving time synchronization under deployments with temperature variations. The working hypothesis demonstrated in this work is that the clock skew of two nodes (the ratio of the real frequencies of the oscillators) is composed of a multiplicative combination of two main components: the clock skew due to the variations between the cut of the crystal of each oscillator and the clock skew due to the different temperatures affecting the nodes. By applying a nonlinear filtering, the homomorphic filtering, both components are separated in an effective way. A correction factor based on temperature, which can be applied to any synchronization protocol, is proposed. For testing it, an improvement of the FTSP synchronization protocol has been developed and physically tested under temperature variation scenarios using TelosB motes flashed with the IEEE 802.15.4 implementation supplied by TinyOS

mDARAL: A Multi-Radio Version for the DARAL Routing Algorithm

Smart Cities are called to change the daily life of human beings. This concept permits improving the efficiency of our cities in several areas such as the use of water, energy consumption, waste treatment, and mobility both for people as well as vehicles throughout the city. This represents an interconnected scenario in which thousands of embedded devices need to work in a collaborative way both for sensing and modifying the environment properly. Under this scenario, the majority of devices will use wireless protocols for communicating among them, representing a challenge for optimizing the use of the electromagnetic spectrum. When the density of deployed nodes increases, the competition for using the physical medium becomes harder and, in consequence, traffic collisions will be higher, affecting data-rates in the communication process. This work presents mDARAL, a multi-radio routing algorithm based on the Dynamic and Adaptive Radio Algorithm (DARAL), which has the capability of isolating groups of nodes into sub-networks. The nodes of each sub-network will communicate among them using a dedicated radio frequency, thus isolating the use of the radio channel to a reduced number of nodes. Each sub-network will have a master node with two physical radios, one for communicating with its neighbours and the other for being the contact point among its group and other sub-networks. The communication among sub-networks is done through master nodes in a dedicated radio frequency. The algorithm works to maximize the overall performance of the network through the distribution of the traffic messages into unoccupied frequencies. The obtained results show that mDARAL achieves great improvement in terms of the number of control messages necessary to connect a node to the network, convergence time and energy consumption during the connection phase compared to DARAL

Data communication optimization for the evaluation of multivariate conditions in distributed scenarios

The current technological landscape is characterized by the massive and efficient interconnection of heterogeneous devices. Sensor networks (SNs) are key elements of this paradigm; they support the local loop, the collection and early manipulation of information. Among the applications of SNs, event detection is a well-explored topic in which strategies such as collaboration, self-organization, and others have been developed in depth. In this topic, the simplest and also most used event concept approach is the threshold-based event, which is usually integrated as part of the local sensor process. This paper addresses a different perspective by discussing the evaluation of multivariate Boolean conditions with distributed variables. We propose a new algorithm (Data Retaining Algorithm for Condition Evaluation, DRACE) that reduces packet traffic while preserving time accuracy in event calculation on an adaptive approach. To facilitate understanding of DRACE, a case study is presented in the context of a logical simile titled The Problem of a Proper Defense. The algorithm supports parameters that affects the compromise between accuracy and traffic savings. To analyze its performance, 9000 executions of the algorithm have been performed. 9 configurations tested on a repository of 1000 triads of signals randomly generated. Focusing on the most accurate configuration, 99% of executions are error-free, and the number of packets is reduced by 40% on average, being between 30 and 50% in 68% of cases

License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours

This paper describes a new method for License Plate Detection based on Genetic Neural Networks, Morphology, and Active Contours. Given an image is divided into several virtual regions sized 10×10 pixels, applying several performance algorithms within each virtual region, algorithms such as edge detection, histograms, and binary thresholding, etc. These results are used as inputs for a Genetic Neural Network, which provides the initial selection for the probable situation of the license plate. Further refinement is applied using active contours to fit the output tightly to the license plate. With a small and well–chosen subset of images, the system is able to deal with a large variety of images with real–world characteristics obtaining great precision in the detection. The effectiveness for the proposed method is very high (97%). This method will be the first stage of a surveillance system which takes into account not only the actual license plate but also the model of the car to determine if a car should be taken as a threat

ALCOR Project: Contributions to Optimizing Remote Robot Guidance in Intelligent Spaces

The work shows the sensory, communication and control solutions for the remote guidance of robots in intelligent environments, as derived activity from the ALCOR project. In this type of applications, optimizing shared resources, especially those related to energy autonomy and the use of the wireless channel, remains a challenge. The main contributions of the project are: a) development of sensorial units based on infrared with centimeter accuracy in the location of the source and response times of milliseconds; b) wireless communication solutions that improve the information routing and homogenization in network traffic; and c) control and estimation solutions based on events with independent mechanisms of action on the mobile unit and request for measurements to the sensor module. The commercial robot P3-DX has been used for experimental tests

Digital Systems Laboratory for Visually Impaired Students

Comunicación presentada al 2nd ACM Workshop on Methods and Cases in Computing Education for the European Higher Education Area, celebrado en Barcelona el 22 de abril de 2009.This paper describes how the practical sessions of the Digital Systems Laboratory within the Computer Science Degree have been adapted to allow a visually impaired student to take part in the practical sessions. Regular students use a computer--aided design tool (OrCAD) for digital design in their practical assignments. This work shows how the use of special instrumentation allows visually impaired students to work with regular students in the same lab, where the CAD tool is installed. The teaching methodology and the obtained assessments are introduced here. Some specific practical materials have been designed and they are described in this work; the design of a special buzzer is also presente

Aplicación de PCA y técnicas bayesianas a la clasificación de píxeles basada en color

En este trabajo se propone un método para la clasificación de píxeles en base a su color. A partir de un conjunto de variables que caracterizan un píxel según su color se determinará cuáles de éstas son las más representativas y se realizará la clasificación propiamente dicha. Para ello nuestro método consta de dos fases: en la primera se aplica PCA para obtener el conjunto de variables características más informativas; en la segunda, dichas variables se utilizan como patrones de las clases de un clasificador bayesiano. El método se ilustra a través de varios experimentos

3D reconstruction system and multiobject local tracking algorithm designed for billiards

The use of virtual reality or augmented reality systems in billiards sports are useful tools for pure entertainment or improving the player’s skills. Depending on the purpose of these systems, tracking algorithms based on computer vision must be used. These algorithms are especially useful in systems aiming to reconstruct the trajectories followed by the balls after a strike. However, depending on the billiard modality, the problem of tracking multiple small identical objects, such as balls, is a complex task. In addition, when an amateur or nontop professional player uses low-frame-rate and low-resolution devices, problems such as blurred balls, blurred contours, or fuzzy edges, among others, arise. These effects have a negative impact on ball-tracking accuracy and reconstruction quality. Thus, this work proposes two contributions. The first contribution is a new tracking algorithm called “multiobject local tracking (MOLT)”. This algorithm can track balls with high precision and accuracy even with motion blur caused by low-resolution and low-frame-rate devices. Moreover, the proposed MOLT algorithm is compared with nine tracking methods and four different metrics, outperforming the rest of the methods in the majority of the cases and providing a robust solution. The second contribution is a whole system to track (using the MOLT algorithm) and reconstruct the movements of the balls on a billiard table in a 3D virtual world using computer vision. The proposed system covers all steps from image capture to 3D reconstruction. The 3D reconstruction results have been qualitatively evaluated by different users through a series of questionnaires, obtaining an overall score of 7.6 (out of 10), which indicates that the system is a promising and useful tool for training. Finally, both the MOLT algorithm and the reconstruction system are tested in three billiard modalities: blackball, carom billiards, and snooker