WISENET leads the INTPART project Indo-Norwegian collaboration in Autonomous Cyber-Physical Systems (INCAPS)

WISENET at University of Agder will lead the new INTPART project INCAPS, where our Center will collaborate with several highly reputed and top Indian Universities. This project establishes a long-term collaboration between top ranked Indian Universities, including Indian Institute of Science (IISc), Bangalore, Indian Institute of Technology, Hyderabad (IITH), International Institute of Information Technology, Hyderabad (IIITH) and Birla Institute of Technology and Science (BITS), Hyderabad and Norwegian Universities and research Institutes, University of Agder (UiA), Norwegian University of Science and Technology (NTNU) and Norwegian Institute for Water Research (NIVA) in world-class research and education says project manager, Prof. Linga Reddy Cenkeramaddi.

Key participants from University of Agder are researchers from WISENET Lab, including Prof. Linga Reddy Cenkeramaddi, Prof. Baltasar Beferull Lozano and Prof. Daniel Romero. Other key researchers involved in the project are, Prof. Kimmo Kansanen from NTNU, Dr. Christopher Harman from NIVA, Prof. Phaneendra K. Yalavarthy from IISc Bangalore, Prof. Abhinav Kumar from IIT Hyderabad, and Prof. Soumya J from BITS Hyderabad.

Only the foremost established and excellent research communities can apply for this INTPART grant and this is highly competitive as the competition is among the world renowned research centers. Major goals are to strengthen the competitiveness and innovation capacity, solving major societal challenges and developing high-quality academic environments. WISENET Lab obtains this grant by competing with the best research centers across the nation. Main objective is to create sustainable partnerships with the best international institutions and research communities across the globe.

This project considers broad areas of research which include smart sensing for autonomous systems, mmWave sensors based system design, analog, digital and mixed signal circuit design, prototyping of wireless communication systems, low-altitude UAVs tracking and communications, de-centralized wireless communications, in-network processing and intelligence for heterogeneous wireless sensor and communication networks, machine learning and deep learning for autonomous systems, data analytics, energy harvesting based smart electronic systems, smart water networks and inference methods for timely detection and prediction, cognitive control and adaptive learning in autonomous cyber-physical systems.

 


WP6 Workshop on Graph Signal Processing


On October 25 the WP6 Leader prof. Baltasar Beferull Lozano organized a workshop on the fundamentals of Graph Signal Processing, together with his colleagues Dr. Daniel Romero and Dr. Luis Miguel Lopez Ramos. Several participants from industry attended, in addition to researchers from UiA. The agenda for the workshop was as follows:

10-12: Basics of Graph Signal Processing, possible applications in different domains (within the SFI OM project) and Feedback from industrial partners.

13-14: Brief review of already well-functioning cooperation cases with industrial partners in WP6.

14-15: Exploration of new cooperation opportunities with industrial partners, associated use cases and strategies.


Data Science in O&G meets Graph Signal Processing


Wisenet Lab was invited to present his work and vision at the Godt tenkt! Conference.

Title: Data Science in O&G meets Graph Signal Processing

Speaker: Baltasar Beferull Lozano

Godt tenkt! is an Innovation Conference that brings together the oil and gas industry. New technologies and smart solutions are crucial for the Norwegian oil and gas industry to be able to renew and improve. Lundin Norway and the Norwegian Petroleum Association will therefore like to gather those who work with tomorrow’s solutions.


Awarded Best Master’s Thesis in ICT 2018

Development, Deployment & Evaluation of Wireless IoT Devices with Energy Harvesting

 

Students Rolf Arne KjellbySvein Erik Løtveit & Thor Eirik Johnsrud, did their Master Thesis under main supervision of Associate professor Linga Reddy Cenkeramaddi and co-supervision of Assistant Professor Geir Jevne. Project task is defined by Assoc. Prof. Linga Reddy Cenkeramaddi. Students designed and developed self-powered and ultra-low powered wireless IoT devices for indoor and outdoor applications. These nodes are tested and work up to 1.8 km and can be deployed in remote places where the accessibility is limited. The nodes can also be deployed in harsh-weather conditions without requiring any maintenance. Designed nodes are of professional market-quality, market-ready, efficient, self-powered and maintenance free. Many possibilities for further research based on these nodes including a start-up company.

Automation of indoor climate is becoming increasingly popular for both household and industrial use. Through automation, comfort increases and power consumption decreases. In order to deploy an automation system, sensors are required.

This master thesis proposes two wireless sensor nodes based on ATmega328p along with the nRF24l01+ transceiver and nRF52840 with various capabilities in both star and multi-hop network configurations. The designed nodes are fully self-powered through energy harvesting, and the nodes are completely self sustainable with no wires, and no user intervention is required during the lifetime of the components. In addition, these nodes do not require any maintenance and can be deployed in remote places. The wireless sensor nodes can be deployed anywhere as long as they are in range of a gateway or nodes that can forward towards a gateway, and as long as there is sufficient light level for the solar panel, such as indoor lights. Fully functional wireless sensor nodes are designed and tested, and compared the performance of both star and multi-hop topologies. The developed nodes consume less power than what is harvested in both indoor and outdoor environments.