Permission to reuse the abstract has been secured from the Publisher.Abdelhafidh, MarouaMohamed, FouratiFourati, Lamia ChaariMnaouer, Adel BenMokhtar, Zid2020-02-092020-02-0920182018-07-02Abdelhafidh, M., Fourati, M., Fourati, L. C., Ben Mnaouer, A., & Mokhtar, Z. (2018). Cognitive Internet of Things for Smart Water Pipeline Monitoring System. In Proceedings of the 2018 IEEE/ACM 22nd International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2018 (pp. 212–219). https://doi.org/10.1109/DISTRA.2018.86009999781538650486http://dx.doi.org/10.1109/DISTRA.2018.8600999https://hdl.handle.net/20.500.12519/113Water Pipeline Monitoring System (WPMS) is extremely important considering the several pipeline damages and the various hydraulic failures that cause a critical water loss. In this context, Cognitive Water Distribution System integrates Internet of Things (IoT) technology, based on smart sensors, actuators and connected objects, with a reliable Big Data processing for smart and robust Structural Health Monitoring (SHM) of pipelines. In this paper, we propose a cognitive IoT-based architecture where we used Apache Spark framework to maintain a real time processing of the large amount of collected data. This efficient processing of measured data and its correspondent calculated values simplify the transient simulations and leak detection and make it faster and easier. © 2018 IEEE.enPermission to reuse abstract has been secured from Institute of Electrical and Electronics Engineers Inc.Big dataCognitive IoTSimulationWater Monitoring SystemData handlingLeak detectionMonitoringPipeline processing systemsPipelinesStructural health monitoring (SHM)Water distribution systemsWater pipelinesInternet of Things (IoT)Pipeline monitoringRealtime processingSimulationTransient simulationWater monitoring systemsConference PaperCopyright : 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.