A framework for use of wireless sensor networks in forest fire detection and monitoring

Forest fires are one of the main causes of environmental degradation nowadays. Current surveillance systems for forest fires lack in supporting real-time monitoring of every point of a region at all times and early detection of fire threats. Solutions using wireless sensor networks, on the other hand, can gather sensory data values, such as temperature and humidity, from all points of a field continuously, day and night, and, provide fresh and accurate data to the fire-fighting center quickly. However, sensor networks face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully. In this paper, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, sensor deployment scheme, and clustering and communication protocols. The aim of the framework is to detect a fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the environmental conditions that may affect the required activity level of the network. We implemented a simulator to validate and evaluate our proposed framework. Through extensive simulation experiments, we show that our framework can provide fast reaction to forest fires while also consuming energy efficiently.     

基于K-means和颜色模型的林火辨识方法研究

为了确保火灾探测结果的可靠性和准确性,从林火燃烧时火焰和烟雾特征出发,对现有的林火探测技术进行了分析,提出了一种基于K-means和颜色模型的林火辨识方法。首先使用Kmeans算法对采集到的彩色图像进行分割,根据火灾发生时火焰和烟雾的颜色特征,采取一种改进的颜色模型对分割出来的子图像进行辨识,对疑似火焰子图像和疑似烟雾子图像进行初步确认,然后从疑似子图像中提取出火焰和烟雾的特征输入到RBF神经网络,判断是否确实发生火灾。     

A framework for the collective movement of mobile robots based on distributed decisions

A novel framework for the control of the collective movement of mobile robots is presented and analyzed in this article. It allows a group of robots to move as a unique entity performing the following functions: obstacle avoidance at group level, speed control and modification of the inter-robot distance. Its flocking controller is distributed among the robots, allowing them to move in the desired common direction and maintain a desired inter-robot distance. The framework is made up of different modules that modify the behavior of the group thus allowing different functions. They are based on consensus algorithms that allow the robots to agree on different parameters, taking into account which robot has more relevant information. New modules can be easily designed and incorporated into the framework in order to augment its capabilities. It can be easily implemented on any mobile robot capable of measuring the relative positions of neighboring robots and communicating with them. It has been successfully tested using 8 real robots and in simulation with up to 40 robots, demonstrating experimentally its scalability with an increasing number of robots.     

A framework for the assessment of synthetic personalities according to user perception

Endowing artificial conversational agents with personality is a very promising way to obtain more believable user interactions with robots and computers. However, although many authors have studied how to create an agent׳s personality and how it affects performance and user satisfaction, less attention has been paid to assess whether the designed agent׳s personality corresponds to the users׳ perception, whether it is easily recognizable, and what is the effect that the user׳s own personality has in the discrimination of the agents׳ personality. In this paper we present an assessment framework to address these issues in an integrated way, which in our opinion offers enough flexibility to consider the diversity of application domains and evaluation approaches that can be found in the literature. The framework is based on numerical measures, which facilitate the interpretation of results and makes it possible to compare and rank different agents with respect to the user׳s perception of the rendered personality. In addition, we have developed a tool that implements the framework, which may be very useful for researchers in order to easily evaluate different agent personalities.     

A hybrid deep learning model by combining convolutional neural network and recurrent neural network to detect forest fire

Multimedia Tools and Applications - Forest fire poses a serious threat to wildlife, environment, and all mankind. This threat has prompted the development of various intelligent and computer vision...     

Mobile agent-enabled framework for structuring and building distributed systems on the internet

Mobile agent has shown its promise as a powerful means to complement and enhance existing technology in various application areas. In particular, existing work has demonstrated that MA can simplify the development and improve the performance of certain classes of distributed applications, especially for those running on a wide-area, heterogeneous, and dynamic networking environment like the Internet. In our previous work, we extended the application of MA to the design of distributed control functions, which require the maintenance of logical relationship among and/or coordination of proc- essing entities in a distributed system. A novel framework is presented for structuring and building distributed systems, which use cooperating mobile agents as an aid to carry out coordination and cooperation tasks in distributed systems. The framework has been used for designing various distributed control functions such as load balancing and mutual ex- clusion in our previous work. In this paper, we use the framework to propose a novel ap- proach to detecting deadlocks in distributed system by using mobile agents, which dem- onstrates the advantage of being adaptive and flexible of mobile agents. We first describe the MAEDD (Mobile Agent Enabled Deadlock Detection) scheme, in which mobile agents are dispatched to collect and analyze deadlock information distributed across the network sites and, based on the analysis, to detect and resolve deadlocks. Then the design of an adaptive hybrid algorithm derived from the framework is presented. The algorithm can dynamically adapt itself to the changes in system state by using different deadlock detec- tion strategies. The performance of the proposed algorithm has been evaluated using simulations. The results show that the algorithm can outperform existing algorithms that use a fixed deadlock detection strategy.     

A framework to model and manipulate constraints for over-constrained geographic applications

Geographic applications are often over-constrained because of the stakeholders’ multiple requirements and the various spatial, alphanumeric and temporal constraints to be satisfied. In most cases, solving over-constrained problems is based on the relaxation of some constraints according to values of preferences. This article proposes the modelling and the management of constraints in order to provide a framework to integrate stakeholders in the expression and the relaxation of their constraints. Three families of constraints are defined: static vs. dynamic, intra-entity vs. inter-entities and intra-instance vs. inter-instances. Constraints are modelled from two points of view: system with the complexity in time of the different involved operators and user with stakeholders’ preferences. The methodology of constraints relaxation is based on primitive, complex and derived operations. These operations allow a modification of the constraints in order to provide a relevant solution to a simulation. The developed system was applied to reduce the streaming/floods risks in the territory of Pays de Caux (Seine Maritime, France).     

A model of distributed recovery for the SUPRENUM multiprocessor

SUPRENUM (Superrechner für numerische Anwendungen) is a German supercomputer project. This paper describes a model for distributed recovery on the SUPRENUM multiprocessor. First we describe the architecture of the SUPRENUM multiprocessor in some definitions. In the next section the distribution of global system checkpoints and an algorithm for distributed reconfiguration is given.     

A fault tolerant model to attain reliability and high performance for distributed computing on the Internet

The aim of the proposed fault tolerant model is to attain reliability and high performance for distributed computing on the Internet. The novelty of this model lies in the integration of three unique schemes that work in unison within a single framework. These three schemes are consecutive message transmission, adaptive buffer control, and message balancing. Message balancing essentially seeks to ensure that each message queue is served for an interval, which depends on the current length of the queue, by the processor. In the experiments, only two parameters: current buffer length and rate of change of the actual queue length were used for proportional and derivative feedback control of adaptive buffer management. Test results have indicated clearly that the model goes a considerable way towards achieving the stated aim.     

Synergistic effects of combined Landsat-TM and SIR-B data for forest resources assessment

Abstract

Three different incidence angle data sets, obtained by the Shuttle Imaging Radar-B in October 1984 over a forested area in northern Florida, were combined with Landsat-5 Thematic Mapper data, to create a digitally registered 10 channel optical/microwave data set. The work discussed in this paper involved the analysis of the data obtained by the two sensors separately and in combination, to determine if there are synergistic effects obtained through the simultaneous use of data obtained from both the optical and microwave portion of the spectrum. The radar data were filtered with a low-pass filter to eliminate the speckle noise. Classifications of the TM, SIR-B and combined TM +SIR-B data sets were performed with both per-point and contextual classifiers. The results showed that filtered radar data can be used to classify accurately major cover types (i.e., pine forest, swamplands and radar smooth targets) and that the contextual classifier provided better classification performance. The combined TM and SIR-B data provided statistically improved classification performances compared to classifications from the three incidence angle SIR-B data, or the TM data alone. A four band subset (TM-2, TM-4, TM-5, and SIR-B 28°) of the 10 channels of the combined TM and SIR-B data set provided higher classification performances (91 per cent overall performance) than the 10 channel data set (86 per cent overall performance).     

An assessment of modelling capacity to identify the impacts of climate variability on catchment hydrology

The aim is to investigate the consistency or variability of catchment response over time and space and evaluate the predictive error caused by the impacts of climate variability on streamflow. For this purpose, both data- and top-down model-based analyses of the dynamic relation between rainfall and runoff for selected sub-catchments have been undertaken. Data analysis techniques (e.g. trend analysis, deconvolution and baseflow filtering) were used to assess the temporal and spatial variation in the hydrologic response characteristics for each site. The lumped conceptual rainfall-runoff model IHACRES CMD (Catchment Moisture Deficit) version is applied to the sub-catchments to assess the adequacy of the model response in representing the impact of weather patterns on streamflow. Several performance criteria have been used to evaluate the performance of the model in each calibration period using a multi-criteria approach. The IHACRES-3S (3 Storage) model is applied to assess low flow behaviour and capture the timing in the switch between baseflow and no flow periods. Rainfall-runoff model performance characteristics of each sub-catchment are quite related to their incident rainfall regime. Sub-catchments which are located in a lower rainfall regime show poor to average model performance. The reduction in performance in R² is due to the poor fitting to the peaks for both large and small streamflow events, with the model underestimating the highest flow peaks, and overestimating smaller peaks. Further work will be needed to assess observed data reliability and improve model performance in order to separate the impacts of climate variations and land use change on hydrological response. An appropriate model structure having a variable partitioning between quick and slow flow components is under consideration and techniques are being used to identify problematic periods and events with high error in the observational data.     

A software framework for fine grain parallelization of cellular models with OpenMP: Application to fire spread

We are dealing here with the parallelization of fire spreading simulations following detailed physical experiments. The proposal presented in this paper has been tested and evaluated in collaboration with physicists to meet their requirements in terms of both performance and precision. For this purpose, an object-oriented framework using two abstraction levels has been developed. A first level considers the simulation as a global phenomenon which evolves in space and time. A local level describes the phenomena occurring on elementary parts of the domain. In order to develop an extensible and modular architecture, the cellular automata paradigm, the DEVS discrete event system formalism and design patterns have been used. Simulation treatments are limited to a set of active elements to improve execution times. A new kind of model, called Active-DEVS is then specified. The model is computed with a fine grain parallelization very efficient for present day multi-core processors which are elementary units of modern computing clusters and computing grids. In this paper, the parallelization with Open MultiProcessing (OpenMP) standard directives on Symmetric MultiProcessing (SMP) architectures is discussed and the efficiency of the retained solution is studied.     

A model for specification and synchronization of data for distributed multimedia applications

As network technology provides the capability to handle multimedia traffic and the demand of multimedia services increases, protocols are required for effective communication of multimedia data in a distributed environment. Synchronization is one of the key issues in a multimedia system. Most of the current approaches do not support an integrated solution to the problem of synchronization. In this paper we propose a mechanism for synchronization of multimedia data in distributed environment where the accuracy of the protocol can be tailored to the application. The system model supports live and video-on-demand service. We present a scheme where the specification of the temporal requirements provided by the application can be directly mapped to obtain the information necessary to enforce the synchronization required. We present two examples of specifying the temporal requirements and process of obtaining the information and present performance results of our simulation studies.     

MoVES: A framework for parallel and distributed simulation of wireless vehicular ad hoc networks

In this paper, we illustrate a Mobile Wireless Vehicular Environment Simulation (MoVES) framework for the parallel and distributed simulation of vehicular wireless ad hoc networks (VANETs). The proposed framework supports extensible, module-based and layered modeling, and scalable, accurate and efficient simulation of vehicular scenarios integrated with wireless communication and mobile services/applications. The vehicular layer includes models for vehicles, synthetic and trace-driven mobility, driver behavior, GPS-based street maps, intersection policies and traffic lights. The wireless communication layer currently includes models for physical propagation, and a network protocol stack including IEEE 802.11 Medium Access Control, up to the Application layer. MoVES provides a platform for microscopic modeling and simulation-based analysis of wireless vehicular scenarios and communication-based services and applications, like Intelligent Transportation Systems, communication-based monitoring/control and info-mobility services. The framework includes design solutions for scalable, accurate and efficient parallel and distributed simulation of complex, vehicular communication scenarios executed over cost-effective, commercial-off-the-shelf (COTS) simulation architectures. Dynamic model partition and adaptation-based load balancing solutions have been designed by exploiting common assumptions and model characteristics, in a user-transparent way. Test-bed performance evaluation for realistic scenarios has shown the effectiveness of MoVES in terms of simulation efficiency, scalability, adaptation and simulation accuracy.     

A semantic framework for the abstract model checking of tccp programs

The Timed Concurrent Constraint programming language (tccp) introduces time aspects into the Concurrent Constraint paradigm. This makes tccp especially appropriate for analyzing timing properties of concurrent systems by model checking. However, even if very compact state representations are obtained thanks to the use of constraints in tccp, large state spaces can still be generated, which may prevent model-checking tools from verifying tccp programs completely. Model checking tccp programs is a difficult task due to the subtleties of the underlying operational semantics, which combines constraints, concurrency, non-determinism and time. Currently, there is no practical model-checking tool that is applicable to tccp. In this work, we introduce an abstract methodology which is based on over- and under-approximating tccp models and which mitigates the state explosion problem that is common to traditional model-checking algorithms. We ascertain the conditions for the correctness of the abstract technique and show that this preliminary abstract semantics does not correctly simulate the suspension behavior, which is a key feature of tccp. Then, we present a refined abstract semantics which correctly models suspension. Finally, we complete our methodology by approximating the temporal properties that must be verified.     

A UML-based quantitative framework for early prediction of resource usage and load in distributed real-time systems

This paper presents a quantitative framework for early prediction of resource usage and load in distributed real-time systems (DRTS). The prediction is based on an analysis of UML 2.0 sequence diagrams, augmented with timing information, to extract timed-control flow information. It is aimed at improving the early predictability of a DRTS by offering a systematic approach to predict, at the design phase, system behavior in each time instant during its execution. Since behavioral models such as sequence diagrams are available in early design phases of the software life cycle, the framework enables resource analysis at a stage when design decisions are still easy to change. Though we provide a general framework, we use network traffic as an example resource type to illustrate how the approach is applied. We also indicate how usage and load analysis of other types of resources (e.g., CPU and memory) can be performed in a similar fashion. A case study illustrates the feasibility of the approach.

BIOTURB: A FORTRAN program to simulate the effects of bioturbation on the vertical distribution of sediment

Bioturbation may have serious implications for preservation of original stratigraphic distribution of sediment. Thus, several methods have been developed to model the redistribution of sediment by bioturbation. The program BIOTURB provides a tool to compare and evaluate different models of bioturbation and their effects on sediment distribution. A flexible approach allowing changes in bioturbating fauna with time, fluctuation of sedimentation rate and sediment type deposited, selective sediment transport by organisms, both random and nonrandom mixing processes, and variation in intensity of mixing with depth was taken. This was achieved by using a transition matrix modeled after a bioturbating fauna in conjunction with a Monte Carlo procedure to govern the redistribution of sediment during mixing. The simulation model, FORTRAN program, and an example are described in detail.