Francisco Javier Molina

Using artificial intelligence in routing schemes for wireless networks

For the latest 10 years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well-known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes.

Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring

The study presents a novel computational intelligence algorithm designed to optimise energy consumption in an environmental monitoring process: specifically, water level measurements in flooded areas. This algorithm aims to obtain a trade-off between accuracy and power consumption. The implementation constitutes a data aggregation and fusion in itself. A harsh environment can make the direct measurement of flood levels a difficult task. This study proposes a flood level estimation, inferred through the measurement of other common environmental variables. The benefit of this algorithm is tested both with simulations and real experiments conducted in Donana, a national park in southern Spain where flood level measurements have traditionally been done manually.

Automated Meter Reading and SCADA Application for Wireless Sensor Network

Currently, there are many technologies available to automate public utilities services (water, gas and electricity). AMR, Automated Meter Reading, and SCADA, Supervisory Control and Data Acquisition, are the main functions that these technologies must support. In this paper, we propose a low cost network with a similar architecture to a static ad-hoc sensor network based on low power and unlicensed radio. Topological parameters for this network are analyzed to obtain optimal performances and to derive a pseudo-range criterion to create an application-specific spanning tree for polling optimization purposes. In application layer services, we analytically study different polling schemes.

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

Abstract 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.

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.

Locating sensors with fuzzy logic algorithms

In a system formed by hundreds of sensors deployed in a huge area it is important to know the position where every sensor is.

OLIMPO, an ad-hoc wireless sensor simulator for public utilities applications

This paper introduces OLIMPO, an useful simulation tool for researchers who are developing wireless sensor communication protocols. OLIMPO is a discrete-event simulator design to be easily reconfigured by the user, providing a way to design, develop and test communication protocols. In particular, we have designed a self-organizing wireless sensor network for low data rate. Our premise is that, due to their inherent spread location over large areas, wireless sensor networks are well-suited for SCADA applications, which require relatively simple control and monitoring. To show the facilities of our simulator, we have studied our network protocol with OLIMPO, developing several simulations. The purpose of these simulations is to demonstrate, quantitatively, the capability of our network to support this kind of applications.

Using industrial standards on PLC programming learning

In this paper, we review aspects relevant to industrial standards related to PLC programming: IEC 61131, IEC 61499 and a work about safety developed by the PLC Open organization based on IEC 61508. We propose to use these standards in PLC learning to fix a common know-how that allows one to reduce the gap between industry and education, and between different professionals. We show the application scope of these standards by analyzing the IEC 61131 limits. The IEC 61499 can be introduced in distributed control systems and in complex centralized systems with multiple operating modes. In critical applications, like safety functions, where functional safety is required, the IEC 61508 is a reference model.

Localization Method for Low-power Wireless Sensor Networks

Context awareness is an important issue in ambientintelligence to anticipate the desire of the user and,in consequence, to adapt the system. In context awareness,localization is very important to enable a responsive environmentfor the users.Focusing on this issue, this paper presents a localizationsystem based on the use of Wireless Sensor Networksdevices. In contrast to a traditional RFID, these devices offerthe possibility of a collaborative sensing and processing ofenvironmental information.The proposed system is a range-free localization algorithmthat uses fuzzy inference to process the RSSI measurementand to estimate the position of mobile devices. The maingoal of the algorithm is to reduce the power consumptionand the cost of the devices, especially for the mobiles ones,maintaining the accuracy of the inferred position.

Application Of Fuzzy Logic For On-line Control Of A Laboratory-scale Anaerobic Reactor

An automatic control system, based on fuzzy logic, has been designed to be used in connection to a laboratory-scale anaerobic reactor. The automatic control system is based on a computer that receives all the data from the sensors through a PLC and the keyboard and, by means of a series of fuzzy control rules, it elaborates a control action that modifies the pumps operation times on the base of one working-cycle. A MATLAB program produces the fuzzy inference and it also takes the control decisions. The inference time reached is about 1 ms. Measurements of pH, ORP, T and reactor water level are constantly relayed to the fuzzy controler. The control system has a series of tools that could be useful to the operator such as simulation screen, evaluation screen and trend graphics. The user interface described allows to work with data not obtained directly by means of sensors, so expensive sensors could be avoided. Thus, the operator can enter data from chemical or biological analyses by the keyboard, and elaborate his own fuzzy control rules and membership functions. Moreover, it is possible to evaluate the impact of control decisions without operating on the process. Therefore, the fuzzy controller is a simple, practical, and low-cost technology and allows the operator to control and modelling the system even if he is not an expert.