Image processing and compressive sensing for Internet of Things applications
University of Essex, United Kingdom
University of Essex, United Kingdom
In numerous Internet of Things (IoT) applications, a network of sensors, camera and actuators are wirelessly connected to remotely monitor the area of interest. However, collecting massive amount of data causes extreme use of the underlying energy-scarce nodes connected by unreliable wireless links, leading to reduced network lifetimes, latency and low rates. Recently, compressive sensing (CS) has shown promising paradigm for data acquisition. CS takes advantages of data sparsity and redundancy for optimisation of acquisition and communication performance. Hence, it can be greatly explored in IoT-based systems for minimisation of overall energy consumption. In addition, many IoT applications require fusion of cameras and sensors data, therefore, sparse data representation could provide a huge benefit to the performance of future IoT devices.
This special session aims at bringing together scholars from academia and industry to discuss and present the latest research and findings on using compressive sensing, image processing and data fusion techniques in IoT Applications.
Topics of interest include but are not restricted to:
- CS techniques in IoT
- Measurement matrix optimization in IoT
- Image processing techniques for IoT applications
- Adaptive sparse sensing in IoT
- Dictionary learning for IoT
- Data gathering based on CS in IoT
- Compressive data aggregation
- Energy management techniques in Visual Sensor Networks (VSNs)
- Matrix completion in VSNs and WSNs
- Deployment of sensors for camera for monitoring and surveillance
- Data fusion and aggregation techniques in IoT
- Modelling and Performance evaluations
- Connectivity and coverage of sensors and cameras
- Smart camera networks in IoT application
ABOUT THE ORGANIZERS
Dr Anisi is an Assistant Professor at the School of Computer Science and Electronic Engineering, University of Essex and head of Internet of Everything (IoE) Laboratory. Prior to that, he worked as a Senior Research Associate at University of East Anglia, UK and Senior Lecturer at University of Malaya, Malaysia where he received ‘Excellent Service Award’ for his achievements.
His research has focused specifically on real world application domains such as energy management, transportation, healthcare and other potential life domains. As a computer scientist, he has designed and developed novel architectures and routing protocols for Internet of Things (IoT) enabling technologies including wireless sensor and actuator networks, vehicular networks, heterogeneous networks, body area networks and his research results have directly contributed to the technology industry. He has strong collaboration with industry and working with several companies in the UK with the focus on monitoring and automation systems based on IoT concept capable of reliable and seamless generation, transmission, processing and demonstration of data.
He has published more than 80 articles in high quality journals and several conference papers and won two medals for his innovations from PECIPTA 2015 and IIDEX 2016 expositions. He has received several International and national funding awards for his fundamental and practical research as PI and Co-I.
Dr Anisi is an associate editor of a number of journals including ‘IEEE Access’, ‘Ad Hoc & Sensor Wireless Networks’, ‘IET Wireless Sensor Systems’, 'International Journal of Distributed Sensor Networks'. ‘KSII Transactions on Internet and Information Systems journals’ and ‘Journal of Sensor and Actuator Networks’. He has been guest editor of special issues of the journals and Lead organizer of special sessions and workshops at IEEE conferences such as IEEE CAMAD, IEEE PIMRC, IEEE VTC and etc. He has been also serving as executive/technical committee member of several conferences. Hossein is Fellow of Higher Education Academy and Senior Member of IEEE. He is also a technical committee member of Finnish-Russian University Cooperation in Telecommunications (FRUCT), Senior Member of Institute of Research Engineers and Doctors (the IRED), Member of ACM, IEEE Council on RFID, IEEE Sensors Council, IEEE Systems Council and International Association of Engineers (IAENG).
Dr Abolghasemi is an assistant professor at the School of Computer Science and Electronic Engineering, University of Essex, UK. He recieved the Ph.D. degree from the University of Surrey, Guildford, UK in 2011. He was a postdoctoral research assistant at Brunel University, UK, during 2012 and worked on compressive sensing for terahertz imaging. His main research interests include compressive sensing, spare representation, dictionary learning, biomedical signal and image processing, and blind source separation. He has currently focused on extending the compressive sensing theory for wireless sensor networks and healthcare applications.
Dr. Abolghasemi is a senior member of IEEE, and has published more than 30 papers in international peer-reviewed scientific journals including IEEE Transactions on Image processing, IEEE signal processing letters, and Computer vision and image understanding. He has also contributed to more than 30 conference papers. He also served as a reviewer of many journals including IEEE Transactions on Image processing, IEEE Transactions on signal processing, IEEE transactions on broadcasting, IEEE transactions on circuits and systems, IEEE transactions on neural networks and learning systems, etc.