The WISENET Lab has managed to get 6 papers accepted at the IEEE ICASSP 2018 international conference. The IEEE ICASSP is the top international conference in the area of signal and data processing. These are the papers accepted:
by Baltasar Beferull Lozano
The WISENET Lab has obtained also funding for the INDURB project from the IKTPLUSS Program, Research Council of Norway. The project INDURB focuses on data-driven cyber-physical networked systems for autonomous cognitive control in water environments.
Only two long-term research projects (out of more than 100 project proposal applications) were selected in the whole IKTPLUSS Call, one of them INDURB, led by the WISENET Lab at UiA.The INDURB project involves highly multidisciplinary research across different areas, and in addition to international cooperation, it will have a direct strong impact on both the Sørlandet region and national-wise through the various water-related circuits and problems.
Two IEEE CAMSAP papers accepted:
The papers are:
Antonio Ortega, Professor, University of Southern California, visited the WISENET Lab from August 15th to August 18th. Prof. Ortega gave a very interesting Talk "Learning Graphs from Data" and attended several presentations given by PhD students in our Lab related to Graph Signal Processing, providing useful feedback.
Wireless Sensor Networks have emerged as a very powerful tool for the monitoring and control, over large areas, of diverse phenomena. One of the most appealing properties of these networks is their potentiality to perform complex tasks in a total distributed fashion, without requiring a central entity. In this scenario, where nodes are constrained to use just local information and communicate only with one-hop neighbors, iterative consensus algorithms enjoy great popularity due to their simplicity. In this work, we propose a consensus-based distributed implementation of a Kalman filter for state estimation, in a sensor network whose connections are subject to random failures. As a result of this unreliability, the agreement value of the consensus process is a random variable. Under these conditions, we ensure that the estimator is unbiased, and adaptively compute the gain of the filter by considering the statistical properties of the consensus process. To the best of our knowledge, this is the first time that the distributed implementation of the Kalman filter is addressed by considering the random error introduced by the consensus. We present some numerical results that confirm the validity of our approach.
Prof. Baltasar Beferull-Lozano has been appointed as of March 15, 2016, Senior Associate Editor for IEEE Transactions on Signal Processing.
The Research Council of Norway has published the evaluation results here. Our project WISECART is one of the only two research projects funded in Norway within the FRIPRO TOPPFORSK Programme, in the area of Information and Communication Technologies. These are excellent news for the WISENET Lab, as well as for the Department of Information and Communication Technologies and the Faculty of Engineering and Science at University of Agder.
Event detection is a crucial tasks in wireless sensor networks. The importance of a fast response makes distributed strategies, where nodes exchange information just with their one hop neighbors to reach local decisions, more adequate than schemes where all nodes send observations to a central entity. Distributed detectors are usually based on average consensus, where all nodes iteratively communicate to asymptotically agree on a final result. In a realistic scenario, communications are subject to random failures, which impacts the performance of the consensus. We propose an alternative detector, which adapts to the statistical properties of the consensus and compensate deviations from the average. Simulation results show that this adaptive detector improves the performance and approximates to the one of the optimal detector.
Prof. Baltasar Beferull was elected as new Member of the Agder Academy of Sciences and Letters, Norway. The ceremony will take place on October 30th, 2015, at Klubben, in Kristiansand.
The main mission of the Academy is to contribute to strengthening the scientific activity in Norway, and increasing the general understanding of the vital importance of science in society. This mission is accomplished in particular by organizing public meetings, conferences and seminars, and by focusing on outstanding academic achievements through the awarding of academic prizes.
Prof. Baltasar Beferull has been invited to attend the National Instruments RF & Communications 5G Round Table 2015 in Vienna. This invitation-only event aims at bringing together a network of leading European researchers and educators active in the area of new communication technologies. This year, the event will have a strong focus on technologies supporting vehicular connectivity, 5G research and development and for prototyping as well as test bed implementations.
This two-day event is limited to a small number of preeminent group leaders and professors, to allow for effective networking and feedback with NI executives, R&D representatives and senior experts as well as experienced Communications platform users. The aim is to prioritize case studies that discuss the use of LabVIEW Communications to accelerate research by reducing the time needed to get from research concept to real-time test bed implementation.
WISENET is co-organizing together with ICS-FORTH (Signal Processing Lab) the 2nd International Workshop on Cyber-Physical Systems for Smart Water Networks (CySWater2016) during the CPS (Cyber-Physical Systems) Week in Viena.
The objective of the 2nd International Workshop on Cyber-physical Systems for Smart Water Networks (CySWater2016) is to bring together for the second time researchers and engineers from the fields of Communications/Networking, Learning/Processing, and Control and practitioners from the Water Industry to both share their experiences, as well as formulate novel CPS paradigms for fulfilling the vision of Smart Water Networks (SWN). Emphasis will be given to both theoretical modelling, as well as modern exemplars that respond to different aspects of the water life-cycle.
The proposed, multi-disciplinary agenda attempts both to stimulate the research and engineering questions, as well as to solicit CPS-based solutions, for addressing the problem of water crisis. As such CySWater aspires to serve as the application-driven forum, where CPS modelling, deployment, and evaluation are tailored to the specific needs of an emerging societal challenge. Therefore CySWater both fits perfectly the purposes of the CPS Week, and complements the agenda of the CPS Week conferences.
Topics of interest include, but are not limited to:
Data Acquisition, Processing & Learning: Infrastructure & smart sensor devices for SWN; Signal sampling, classification & anomaly detection for SWN; Decentralized multi-sensor fusion, learning & data analytics.
Communications, Networking & Control: Underground & underwater CPS; Mobile network agents for large-scale CPS; Networked Control Systems architecture, incl. cloud computing aspects; CPS and security for SWN.
Analysis, Performance, & Applications: Testbeds, field studies, & performance analysis; Novel CPS application paradigms for modern water applications, s.a. water treatment, water recycle and reuse, waste/sewage/storm water management; Standardization and policies for enabling SWN.
The WISENET Lab is currently growing in size with the hiring of three new PhD. and three new Postdoctoral researchers.
Full project name: Off-shore–On-shore Collective Analytics & Intelligence for condition-based monitoring in drilling & operations using heterogeneous networks (SMART-RIG)
Funding: Researcher Project, Research Council of Norway
Principal Investigator: Prof. Baltasar Beferull-Lozano
Topic: This project is motivated by the grand challenge of providing a new ICT solution for collective off-shore–on-shore intelligence for predictive CBM of drilling rigs, covering: a) the distributed acquisition of sensor signals, including data pre-processing,adaptive sampling rate optimization and collaborative calibration capabilities (Network Tier 1), b) in-network cooperative processing and distributed context-aware intelligence to perform essential data analytics tasks such as local event prediction and detection, low-level feature extraction, decision-making support and learning, c) design of semantic sensor management tools at micro-server nodes (Network Tier 2), with higher resources in terms of computation and communication capabilities, providing data aggregation across different inter-related subsystems and an intermediate medium-to-high level inference about the data collection, i.e., high-level diagnostics (fault detection, isolation and cause identification) and prognostics (fault & degradation prediction), tracking continuous consistency with the on-shore high-level analytics running at the servers (Network Tier 3) of Control Centers, providing recommendations or direct actions if necessary. The proof of concept will be demonstrated with the support from Lundin, Frigstad and MHWirth.
Role: Coordination and Leader of all technical WorkPackages.
Period: 2015 – 2019