José Javier Astrain

Fuzzy location and tracking on wireless networks

This paper describes user location and tracking on indoor scenarios through a wireless network. We propose a fuzzy location algorithm, using fuzzy inference systems, in order to deal with imprecise location based on radio-frequency trilateration estimations, providing high location rates near to 90. This indoor positioning approach is based on the pattern recognition of IEEE 802.11 (WiFi) signal strength measurements using fuzzy logic to deal with the vagueness and uncertainty of the trilateration based on signal strength. User location and tracking are considered in order to provide complete intelligent location based services. Fuzzy location techniques allow increasing location ratios even when the user trilateration can not be as precise as desired. Fuzzy tracking is performed by means of a fuzzy automaton.

An easy to deploy street light control system based on wireless communication and LED technology.

This paper presents an intelligent streetlight management system based on LED lamps, designed to facilitate its deployment in existing facilities. The proposed approach, which is based on wireless communication technologies, will minimize the cost of investment of traditional wired systems, which always need civil engineering for burying of cable underground and consequently are more expensive than if the connection of the different nodes is made over the air. The deployed solution will be aware of their surroundings environmental conditions, a fact that will be approached for the system intelligence in order to learn, and later, apply dynamic rules. The knowledge of real time illumination needs, in terms of instant use of the street in which it is installed, will also feed our system, with the objective of providing tangible solutions to reduce energy consumption according to the contextual needs, an exact calculation of energy consumption and reliable mechanisms for preventive maintenance of facilities.

Deformed fuzzy automata for correcting imperfect strings of fuzzy symbols

Presents a fuzzy method for the recognition of strings of fuzzy symbols containing substitution, deletion, and insertion errors. As a preliminary step, we propose a fuzzy automaton to calculate a similarity value between strings. The adequate selection of fuzzy operations for computing the transitions of the fuzzy automaton allows us to obtain different string similarity definitions (including the Levenshtein distance). A deformed fuzzy automaton based on this fuzzy automaton is then introduced in order to handle strings of fuzzy symbols. The deformed fuzzy automaton enables the classification of such strings having an undetermined number of insertion, deletion and substitution errors. The selection of the parameters determining the deformed fuzzy automaton behavior would allow to implement recognizers adapted to different problems. The paper also presents algorithms that implement the deformed fuzzy automaton. Experimental results show good performance in correcting these kinds of errors.

Pattern Matching Techniques to Identify Syntactic Variations of Tags in Folksonomies

Folksonomies offer an easy method to organize information in the current Web. This fact and their collaborative features have derived in an extensive involvement in many Social Web projects. However they present important drawbacks regarding their limited exploring and searching capabilities, in contrast with other methods as taxonomies, thesauruses and ontologies. One of these drawbacks is an effect of its flexibility for tagging, producing frequently multiple syntactic variations of a same tag. In this paper we study the application of two classical pattern matching techniques, Levenshtein distance for the imperfect string matching and Hamming distance for the perfect string matching, to identify syntactic variations of tags.

A distributed data gathering algorithm for wireless sensor networks with uniform architecture

Wireless sensor networks (WSNs) are commonly used for continuously monitoring applications. Data gathering and in-network processing are techniques to efficiently gather the information from sensor nodes. Usually, these techniques have been analyzed taking into account a global knowledge of the system in order to select the best path to gather the information or to establish a routing function. In this paper we propose a novel distributed data gathering algorithm for wireless networks and evaluate the effect of having a different number of cluster heads transmitting to the base station. We focus the attention on uniformly distributed nodes in a given area to evaluate the effects on the energy consumption. Our proposal distributes uniformly the energy consumption between the complete set of sensors in the system resulting in a similar longevity for all sensors in the system

Data Aggregation in Wireless Sensor Networks

Serial data aggregation ensures minimal energy consumption since only one sensor initiates the algorithm and each sensor communicates only once with its successor. But it is difficult in a real scenario (essentially distributed) to synchronize all sensors to collaborate. In this paper we propose a linear distributed algorithm to aggregate data and we simulate it for different scenarios using the ns2 network simulator. We conclude that the proposed algorithm consume energy in a uniform way.

Analysis of Wireless Sensor Network Topology and Estimation of Optimal Network Deployment by Deterministic Radio Channel Characterization

One of the main challenges in the implementation and design of context-aware scenarios is the adequate deployment strategy for Wireless Sensor Networks (WSNs), mainly due to the strong dependence of the radiofrequency physical layer with the surrounding media, which can lead to non-optimal network designs. In this work, radioplanning analysis for WSN deployment is proposed by employing a deterministic 3D ray launching technique in order to provide insight into complex wireless channel behavior in context-aware indoor scenarios. The proposed radioplanning procedure is validated with a testbed implemented with a Mobile Ad Hoc Network WSN following a chain configuration, enabling the analysis and assessment of a rich variety of parameters, such as received signal level, signal quality and estimation of power consumption. The adoption of deterministic radio channel techniques allows the design and further deployment of WSNs in heterogeneous wireless scenarios with optimized behavior in terms of coverage, capacity, quality of service and energy consumption.

Hierarchical and fault-tolerant data aggregation in wireless sensor networks

This paper presents three hierarchical algorithms for data aggregation in wireless sensor networks where sensors can crash and recover. The network is divided in several regions. The algorithms ensure (i) the selection of a common data aggregator sensor within each region, in charge of the collection of local data, and (ii) the selection of a unique super-aggregator sensor, in charge of the collection of global data, among all the aggregators. Both selections are achieved by implementing the Omega failure detector, which provides a self-organizing and fault-tolerant leader election service. We also introduce a battery depletion threshold to provide wireless sensor network QoS.

Fuzzy automata with ε-moves compute fuzzy measures between strings

This paper introduces fuzzy automata with transitions by empty string (@?-moves), and shows their relationship with other classes of classical fuzzy automata. The @?-move represents a state change of the automaton without consuming any symbol of the input string. In approximate string matching, @?-moves allow to model the effect of the insertion of a symbol (one of the possible edit operations). We provide a fuzzy measure between strings based on the concepts of string alignments and fuzzy edit operations. The main contribution of this paper is to prove that a particular class of fuzzy automata with @?-moves computes those fuzzy measures without restricting the number of errors between the strings. Given a fuzzy measure, a building method for constructing the fuzzy automaton with @?-moves that computes it, is also proposed.

Design and Implementation of Context Aware Applications With Wireless Sensor Network Support in Urban Train Transportation Environments

Transportation system is experiencing steady growth, with the aim of providing more efficient, reliable, and comfortable services, in the framework of intelligent transportation systems. Moreover, context aware environments are one of the main drivers in the achievement of smart cities and smart regions. In this paper, wireless sensor networks (WSNs) embedded in urban transportation systems will be analyzed in terms of impact on wireless channel behavior and system performance. An in-house developed 3-D ray launching tool, with the inclusion of in-house human body model as well as with the study of interference levels is employed. Wireless channel estimations indicate an initial infrastructure node density in the order of 1node/150m2 to 1node/500m2 as a function of the employed transceivers. A practical solution has been implemented, combining an Android-based application and a system level architecture over the WSN for urban train transportation environmental monitoring, providing interaction between users and the environment, with the aid of a combined WSN/WLAN platform as well as an implemented software architecture, scalable in terms of user density and future needs.