Machine learning (ML) is training computers to learn from data collected through past experience. Learning is the most appropriate alternative in cases where it is not possible to directly write programs to solve problems, i.e., when the solution is not a priori known but can only be developed using data or experience. This is typical in problems in which human expertise does not exist or when it is difficult to express it. Traditional domains where ML has been largely used include speech/face recognizing, language processing, spam filter, etc., which have been investigated for a long time and mature solutions already exist. However, the use of ML tools for emerging domains such as the Internet of Things (IoT), smart environments and related applications is still in its early stages and is among the trends that have recently been attracting research communities in several disciplines. In this talk, two examples from our recent research related to the use of advanced machine learning tools in the IoT domains will be presented. The first one is the prediction of sensor readings using spatiotemporal correlation, which has a wide range of applications such as in smart buildings, smart transportations, and medical applications. The second one is for periodic broadcasting in wireless networks with energy harvesting capabilities.
Djamel Djenouri obtained the Doctorate in Computer Science from the University of Science and Technology (USTHB), Algeria, in 2007. He was granted a post-doctoral fellowship from the European Research Consortium on Informatics and Mathematics (ERCIM) and has been working at the Norwegian University of Science and Technology (NTNU), Norway, from 2008 to 2009. He was a senior research scientist (Director of Research) and deputy director at CERIST, Algiers. He also served as adjunct full professor at Blida university and the EMP polytechnic university, Algiers. In Dec 2019, he joined the University of the West of England (UWE), UK. He is working on topics related Internet of things, wireless and mobile networks, network security, machine learning and application for smart cities and green applications. He has been conducting several research projects with international collaborations as the principal investigator for many of them. He participated in many international conferences worldwide and gave many keynotes and plenary-session talks. He has been granted mobility internships for short visits to many renowned universities including NTNU, SICS (Stockholm), university of Cape Town, UPC Barcelona, JMU Liverpool, UTC (Compiegne), Nuertingen Geislingen university (Stuttgart), university of Padova, university of Oxford, etc. He has been a visiting researcher to NTNU in 2017 and 2019. He published more than 130 papers in international peer-reviewed journals and conference proceedings, two books, and he is holding two national patents. He voluntarily contributed to the organization of many conferences and workshops, and he served as TPC member of many international conferences, as well as guest editor, member of editorial board, reviewer for many Journals. He is a senior member of Association of Commuting Machinery (ACM), member of the Arab/German Young Academy of Science and Humanities (AGYA), and fellow of the UK Higher Education Academy (HEA).