A Wildfire Prediction Based on Fuzzy Inference System for Wireless Sensor Networks

The study of forest fires has been traditionally considered as an important application due to the inherent danger that this entails. This phenomenon takes place in hostile regions of difficult access and large areas. Introduction of new technologies such as Wireless Sensor Networks (WSNs) has allowed us to monitor such areas. In this paper, an intelligent system for fire prediction based on wireless sensor networks is presented. This system obtains the probability of fire and fire behavior in a particular area. This information allows firefighters to obtain escape paths and determine strategies to fight the fire. A firefighter can access this information with a portable device on every node of the network. The system has been evaluated by simulation analysis and its implementation is being done in a real environment.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570

A Review on Swarm Intelligence Based Routing Approaches

The principles of bio-inspired or swarm intelligence algorithms can be effectively used to achieve optimal solutions in routing for complex and dynamic wireless sensor networks or body area networks. As the name indicates, it is a field that is inspired by natural living beings like ants, bees, fishes, etc. Studies have proved that the routing protocols based on such bio-inspired methods perform better in terms of energy efficiency, reliability, adaptivity, scalability, and robustness. The general classification of routing protocols is classical-based and swarm-based routing protocols, where both the protocols were specifically categorized as data-centric, location-aware, hierarchical and network flow, and QoS aware protocols. In this paper, an evocative taxonomy and comparison of various swarm-based routing algorithms are presented. A brief discussion about the sensor network design and the major factors that influence the routing is also discussed. The comparative analysis of the selected swarm-based protocols is also done with respect to routing characteristics like query based, route selection, energy efficiency, and path selection. From the review, it is observed that the selection of a routing protocol is application dependent. This paper will be helpful to the researchers as a reference on bio-inspired algorithms for new protocol designs and also for the proper selection of routing protocols according to the type of applications

A Review on Swarm Intelligence Based Routing Approaches

The principles of bio-inspired or swarm intelligence algorithms can be effectively used to achieve optimal solutions in routing for complex and dynamic wireless sensor networks or body area networks. As the name indicates, it is a field that is inspired by natural living beings like ants, bees, fishes, etc. Studies have proved that the routing protocols based on such bio-inspired methods perform better in terms of energy efficiency, reliability, adaptivity, scalability, and robustness. The general classification of routing protocols is classical-based and swarm-based routing protocols, where both the protocols were specifically categorized as data-centric, location-aware, hierarchical and network flow, and QoS aware protocols. In this paper, an evocative taxonomy and comparison of various swarm-based routing algorithms are presented. A brief discussion about the sensor network design and the major factors that influence the routing is also discussed. The comparative analysis of the selected swarm-based protocols is also done with respect to routing characteristics like query based, route selection, energy efficiency, and path selection. From the review, it is observed that the selection of a routing protocol is application dependent. This paper will be helpful to the researchers as a reference on bio-inspired algorithms for new protocol designs and also for the proper selection of routing protocols according to the type of applications

Energy-efficient routing algorithms based on swarm intelligence for wireless sensor networks

High efficient routing is an important factor to be considered in the design of limited energy resource Wireless Sensor Networks (WSNs). WSN environment has limited resources in terms of on-board energy, transmission power, processing, and storage, and this prompt for careful resource management and new routing protocol so as to counteract the challenges. This work first introduces the concept of wireless sensor networks, routing in WSNs, and its design factors as they affect routing protocols. Next, a comprehensive review of the most prominent routing protocols in WSN, from the classical routing protocols to swarm intelligence based protocols is presented. From the literature study, it was found that comparing routing protocols in WSNs is currently a very challenging task for protocol designers. Often, much time is required to re-create and re-simulate algorithms from descriptions in published papers to perform the comparison. Compounding the difficulty is that some simulation parameters and performance metrics may not be mentioned. We then see a need in the research community to have standard simulation and performance metrics for comparing different protocols. To this end, we re-simulate different protocols using a Matlab based simulator; Routing Modeling Application Simulation Environment (RMASE), and gives simulation results for standard simulation and performance metrics which we hope will serve as a benchmark for future comparisons for the research community. Also, from the literature study, Energy Efficient Ant-Based Routing (EEABR) protocol was found to be the most efficient protocol due to its low energy consumption and low memory usage in WSNs nodes. Following this efficient protocol, an Improved Energy Efficient Ant-Based Routing (IEEABR) Protocol was proposed. Simulation were performed using Network Simulator-2 (NS-2), and from the results, our proposed algorithm performs better in terms of energy utilization efficiency, average energy of network nodes, and minimum energy of nodes. We further improved on the proposed protocol and simulation performed in another well-known WSNs MATLAB-based simulator; Routing Modeling Application Simulation Environment (RMASE), using static, mobile and dynamic scenario. Simulation results show that the proposed algorithm increases energy efficiency by up to 9% and 64% in converge-cast and target-tracking scenarios, respectively, over the original EEABR and also found to out-perform other four Ant-based routing protocols. We further show how this algorithm could be used for energy management in sensor network in the presence of energy harvesters. However, high number of control packets is generated by the IEEABR due to the proactive nature of its path establishment. As such, a new routing protocol for WSNs that has less control packets due to its on-demand (reactive) nature is proposed. This new routing protocol termed Termite-hill is borrowed from the principles behind the termite’s mode of communication. We first study the foraging principles of a termite colony and utilize the inspirational concepts to develop a distributed, simple and energy-efficient routing protocol for WSNs. We perform simulation studies to compare the behavior and performance of the Termite-hill design with an existing classical and on-demand protocol (AODV) and other Swarm Intelligence (SI) based WSN protocols in both static, dynamic and mobility scenarios of WSN. The simulation results demonstrate that Termite-hill outperforms its competitors in most of the assumed scenarios and metrics with less latency. Further studies show that the current practice in modeling and simulation of wireless sensor network (WSN) environments has been towards the development of functional WSN systems for event gathering, and optimization of the necessary performance metrics using heuristics and intuition. The evaluation and validation are mostly done using simulation approaches and practical implementations. Simulation studies, despite their wide use and merits of network systems and algorithm validation, have some drawbacks like long simulation times, and practical implementation might be cost ineffective if the system is not properly studied before the design. We therefore argue that simulation based validation and practical implementation of WSN systems and environments should be further strengthened through mathematical analysis. To conclude this work and to gain more insight on the behavior of the termite-hill routing algorithm, we developed our modeling framework for WSN topology and information extraction in a grid based and line based randomly distributed sensor network. We strengthen the work with a model of the effect of node mobility on energy consumption of Termite-hill routing algorithm as a function of event success rate and occasional change in topology. The results of our mathematical analysis were also compared with the simulation results

Deep Learning Methods for Remote Sensing

Remote sensing is a field where important physical characteristics of an area are exacted using emitted radiation generally captured by satellite cameras, sensors onboard aerial vehicles, etc. Captured data help researchers develop solutions to sense and detect various characteristics such as forest fires, flooding, changes in urban areas, crop diseases, soil moisture, etc. The recent impressive progress in artificial intelligence (AI) and deep learning has sparked innovations in technologies, algorithms, and approaches and led to results that were unachievable until recently in multiple areas, among them remote sensing. This book consists of sixteen peer-reviewed papers covering new advances in the use of AI for remote sensing

QoS Analysis for a Non-Preemptive Continuous Monitoring and Event Driven WSN Protocol in Mobile Environments

Evolution in wireless sensor networks (WSNs) has allowed the introduction of new applications with increased complexity regarding communication protocols, which have to ensure that certain QoS parameters are met. Specifically, mobile applications require the system to respond in a certain manner in order to adequately track the target object. Hybrid algorithms that perform Continuous Monitoring (CntM) and Event-Driven (ED) duties have proven their ability to enhance performance in different environments, where emergency alarms are required. In this paper, several types of environments are studied using mathematical models and simulations, for evaluating the performance of WALTER, a priority-based nonpreemptive hybrid WSN protocol that aims to reduce delay and packet loss probability in time-critical packets. First, randomly distributed events are considered. This environment can be used to model a wide variety of physical phenomena, for which report delay and energy consumption are analyzed by means of Markov models. Then, mobile-only environments are studied for object tracking purposes. Here, some of the parameters that determine the performance of the system are identified. Finally, an environment containing mobile objects and randomly distributed events is considered. It is shown that by assigning high priority to time-critical packets, report delay is reduced and network performance is enhanced.This work was partially supported by CONACyT under Project 183370. The research of Vicent Pla has been supported in part by the Ministry of Economy and Competitiveness of Spain under Grant TIN2013-47272-C2-1-R.Leyva Mayorga, I.; Rivero-Angeles, ME.; Carreto-Arellano, C.; Pla, V. (2015). QoS Analysis for a Non-Preemptive Continuous Monitoring and Event Driven WSN Protocol in Mobile Environments. International Journal of Distributed Sensor Networks. 2015:1-16. https://doi.org/10.1155/2015/471307S1162015Arampatzis, T., Lygeros, J., & Manesis, S. (s. f.). A Survey of Applications of Wireless Sensors and Wireless Sensor Networks. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation Intelligent Control, 2005. doi:10.1109/.2005.1467103Ramachandran, C., Misra, S., & Obaidat, M. S. (2008). A probabilistic zonal approach for swarm-inspired wildfire detection using sensor networks. International Journal of Communication Systems, 21(10), 1047-1073. doi:10.1002/dac.937Misra, S., Singh, S., Khatua, M., & Obaidat, M. S. (2013). Extracting mobility pattern from target trajectory in wireless sensor networks. International Journal of Communication Systems, 28(2), 213-230. doi:10.1002/dac.2649Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660-670. doi:10.1109/twc.2002.804190Younis, O., & Fahmy, S. (s. f.). Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach. IEEE INFOCOM 2004. doi:10.1109/infcom.2004.1354534Manjeshwar, A., & Agrawal, D. P. (s. f.). TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001. doi:10.1109/ipdps.2001.925197Manjeshwar, A., & Agrawal, D. P. (2002). APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless. Proceedings 16th International Parallel and Distributed Processing Symposium. doi:10.1109/ipdps.2002.1016600Sharif, A., Potdar, V., & Rathnayaka, A. J. D. (2010). Prioritizing Information for Achieving QoS Control in WSN. 2010 24th IEEE International Conference on Advanced Information Networking and Applications. doi:10.1109/aina.2010.166Alappat, V. J., Khanna, N., & Krishna, A. K. (2011). Advanced Sensor MAC protocol to support applications having different priority levels in Wireless Sensor Networks. 2011 6th International ICST Conference on Communications and Networking in China (CHINACOM). doi:10.1109/chinacom.2011.6158175Alam, K. M., Kamruzzaman, J., Karmakar, G., & Murshed, M. (2012). Priority Sensitive Event Detection in Hybrid Wireless Sensor Networks. 2012 21st International Conference on Computer Communications and Networks (ICCCN). doi:10.1109/icccn.2012.6289220Raja, A., & Su, X. (2008). A Mobility Adaptive Hybrid Protocol for Wireless Sensor Networks. 2008 5th IEEE Consumer Communications and Networking Conference. doi:10.1109/ccnc08.2007.159Srikanth, B., Harish, M., & Bhattacharjee, R. (2011). An energy efficient hybrid MAC protocol for WSN containing mobile nodes. 2011 8th International Conference on Information, Communications & Signal Processing. doi:10.1109/icics.2011.6173629Lee, Y.-D., Jeong, D.-U., & Lee, H.-J. 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Environmental Technology Applications in the Retrofitting of Residential Buildings

The impact of buildings on the environment is nothing short of devastating. In recent years, much attention has been given to creating an environmentally friendly built environment. Nonetheless, it has been levied on new buildings. Residential buildings make up at least 80% of the built environment, most of which were built before any energy efficiency guidelines or regulations were introduced. Retrofitting existing residential buildings is a key yet neglected priority in effecting the transition to an environmentally friendly, sustainable built environment. It is pivotal to reducing a building’s energy consumption while simultaneously improving indoor environmental quality and minimizing harmful emissions. This Special Issue showcases studies investigating applications of environmental technology that is tailored to enhance the sustainable performance of existing residential buildings. It helps to better understand the innovations that have been taking place in retrofitting residential buildings, as well as highlighting many opportunities for future research in this field

Termografía Infrarroja aplicada a la detección de incendios en la interfaz urbano-forestal y su optimización mediante redes neuronales artificiales

[EN] The Albufera of Valencia and its Devesa, form a single unit with both an ecological and social high value; reason that led them to be declared Natural Park in 1986 by the Generalitat Valenciana; being the first park declared in this autonomous community. The Devesa is the spit that separates the Mediterranean Sea from the Albufera lake, and is considered a natural area with high scientific, cultural, scenic and educational values. And although during the 60s underwent a process of urbanization, today is in the throes of regeneration to an era of ecological climax. This regeneration has been possible because of the economics efforts made by various administrations for their conservation and protection. However, these efforts do not prevent Devesa from suffering systematically wildfires that undermine their ability to regenerate and that not only produce significant ecological and economic damage, but when fires reach great dimensions, threaten the life of the people who live there and also the firefighting services This Thesis focuses on the study and optimization of the detection system of wildfires using infrared installed in the Devesa. For doing this, the wildfires produced during ten years and the alarms generated during five years of operation of the system are analyzed, relating these alarms with the weather conditions; in order to reduce false positives; on the other hand a fire risk classification system based on neural networks is developed, using as descriptions parameters those used in the IFW, that is the official system used for the official organization in charge of fire weather index in Spain: AEMET. After the development of the neural network to classify the risk of fire, and analyzed the infrared camera system, both are combined to establish a classification system of the alarms, in order to reduce false positives, and establish a criterion of risk to the user of the fire detection system.[ES] La Albufera de Valencia y su Devesa, forman un conjunto único con un elevado valor tanto ecológico como social; motivo que les llevó a ser declarados Parque Natural en 1986 por parte de la Generalitat Valenciana; siendo el primer parque declarado en esta comunidad. La Devesa es el cordón litoral que separa el Mar Mediterráneo del lago de la Albufera, y es considerada un área natural con altos valores científicos, culturales, paisajísticos y educativos. Y, pese a que durante la década de los 60 sufrió un proceso de urbanización, en la actualidad se encuentra en plena fase de regeneración hacia una época de clímax ecológico. Esta regeneración ha sido posible gracias a los esfuerzos, tanto administrativos como económicos, que han realizado diferentes administraciones para su conservación y protección. Sin embargo, estos esfuerzos no impiden que sistemáticamente el monte de la Devesa sufra incendios forestales que merman su capacidad de regeneración y que, no solo producen un daño ecológico y económico importante, sino que aquellos que alcanzan grandes dimensiones ponen en riesgo la vida de las personas que allí residen, y de los equipos de extinción que tratan de sofocarlos. La presente Tesis se centra en el estudio y optimización del sistema de detección de incendios forestales mediante infrarrojos instalado en la Devesa. Para ello se analizan los incendios ocurridos durante más de diez años, y las alarmas generadas durante cinco años de funcionamiento del sistema, relacionando estas alarmas con las condiciones meteorológicas, a fin de disminuir los falsos positivos; a su vez se desarrolla un sistema de clasificación de riesgo de incendio a partir de redes neuronales, basado en los parámetros meteorológicos descriptores usados en el IFW, índice oficial establecido por la AEMET para clasificar el riesgo de incendio. Una vez desarrollada la red neuronal para clasificar el riesgo de incendio, y analizado el sistema de cámaras infrarrojas, se combinan ambos a fin de establecer un sistema de clasificación de las alarmas capaz de disminuir los falsos positivos, y de establecer un criterio de riesgo al usuario del sistema de detección de incendios.[CA] L'Albufera de València i la seva Devesa, formen un conjunt únic amb un elevat valor tant ecològic com social; motiu que els va portar a ser declarats Parc Natural al 1986 per part de la Generalitat Valenciana; sent el primer parc declarat en aquesta Comunidad. La Devesa és el cordó litoral que separa el mar Mediterrani del llac de l'Albufera, i és considerada una àrea natural amb alts valors científics, culturals, paisatgístics i educatius. I tot i que durant la dècada dels 60 va patir un procés d'urbanització, en l'actualitat es troba en plena fase de regeneració cap a una època de clímax ecològic. Aquesta regeneració ha estat possible gràcies als esforços tant administratius, com econòmics, que han realitzat diferents administracions per a la seva conservació i protecció. No obstant això, aquests esforços no impedeixen que sistemàticament la muntanya de la Devesa pateixi incendis forestals que minven la seva capacitat de regeneració i que, no només produeixen un dany ecològic i econòmic important, sinó que aquells que arriben a tindre grans dimensions, posen en risc la vida de les persones que hi viuen, i dels equips d'extinció que tracten de sufocar-los. Aquesta tesi se centra en l'estudi i optimització del sistema de detecció d'incendis forestals mitjançant infrarojos instal · lat a la Devesa. Per a això s'analitzen els incendis ocorreguts durant més de deu anys i les alarmes generades durant cinc anys de funcionament del sistema, relacionant aquestes alarmes amb les condicions meteorològiques; per tal de disminuir els falsos positius; al seu torn es desenvolupa un sistema de classificació de risc d'incendi a partir de xarxes neuronals, basat en els paràmetres meteorològics descriptors usats en el IFW, índex oficial establert per l'AEMET per classificar el risc d'incendi. Un cop desenvolupada la xarxa neuronal per classificar el risc d'incendi, i analitzat el sistema de càmeres infraroges, es combinen tots dos a fi d'establir un sistema de classificació de les alarmes capaç de disminuir els falsos positius, i d'establir un criteri de risc a l¿usuari del sistema de detecció d'incendis. Canales Mengod, P. (2015). Termografía Infrarroja aplicada a la detección de incendios en la interfaz urbano-forestal y su optimización mediante redes neuronales artificiales [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/49830TESI