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Digital Innovation Research Group

Unit(s) of assessment: General Engineering

School: School of Science and Technology


A research group focused on development of smart technologies by connecting interdisciplinary research in robotics, digital twins, cyber physical systems, intelligent vehicles and drones, smart logistics, digital manufacturing, renewable energy and 5G communication.

Key Research Areas:

  • High-performance flexible electronics
  • Bio-mimetic electronic systems
  • Industry 4.0 based smart factories
  • Robotics
  • Industrial Digital Twins
  • Design of Energy Efficient systems for 5G and beyond
  • Video coding, processing, adaptation, error resilience, quality, and interaction

Our current research projects include:

Mental stress factors in occupational safety in the context of smart factory and COVID-19
Use of collaborative robots (COBOTs) in the industrial setting has grown globally, especially in the context of the smart factory. Humans and COBOTs are increasingly expected to share their workspace and associated issues related to workplace health and safety are expected to rise. This project seeks to understand the impact on the workers' mental health in relation to the task variables (complexity, production speed, duration, payload etc.) whilst working alongside the COBOT. Funded by EPSRC, Connected Everything, industrial systems in the digital age, feasibility study and PepsiCo as an industrial partner.

Bio-mimetic electronic systems and Smart sensors
High-performance flexible electronics and bio-mimetic electronic systems are pursued for applications in smart sensors, intelligent systems and soft robotics. The interfaces like electronic skin are envisaged for applications in assistive, soft, safe and dexterous robots, wearables and rehab. Key demonstrators for projects are developed under funding from EPSRC, EU and CSIR.

Industry 4.0 based smart factories and Digital Twins
Industry 4.0 based smart factories are characterised through networked, cooperating modules named cyber-physical production systems. Digital twin is the key technology area developed for design, simulation and optimization of manufacturing processes. Other applications are smart maintenance, reliability, metrology and safe and secure human-robot collaboration.

5G and beyond: Technology & Services
Design of energy efficient systems for 5G and beyond, green wireless systems for simultaneous wireless information and power transfer (SWIPT), energy harvesting systems and capacity enhancement and coverage for LEO satellite. The projects funded by EPSRC, Horizon 2020 project ATOM and NASA, CASC and European satellite. The services-based research include video coding, processing, adaptation, error resilience, quality and interaction, funded by sources like EC, Innovate UK, ADB. Major projects are ACTION-TV, DIOMEDES, MUSCADE, and VISNET-II.

Related staff

Azfar Khalid - Senior Lecturer in Mechanical Engineering

Hemantha Kodikara Arachchi - Principal Lecturer in Electronic Engineering

William Navaraj - Senior Lecturer in Electronic Engineering

Shukri Afazov - Senior Lecturer in Mechanical Engineering

Vahid Vahidinasab - Senior Lecturer in Electrical (Power) Engineering

Mehdi Zenali - Lecturer in Electrical and Electronic Engineering


  • O’Brien J, Montgomery S, Yaghi A, Afazov S, 2021, Process chain simulation of laser powder bed fusion including heat treatment and surface hardening, CIRP Journal of Manufacturing Science and Technology, 32, 266-276.
  • Afazov S, Semerdzhieva E, Scrimieri D, Serjouei A, Kairoshev B, Derguti F, 2021, An improved distortion compensation approach for additive manufacturing using optically scanned data, Virtual and Physical Prototyping, 16, 1-13.
  • Siddiqui AM, Evans B, Zhang Y and Xiao P, 2021, Capacity Enhancement of High Throughput Low Earth Orbit Satellites in a constellation (HTS-LEO) in a 5G network, Advances in Intelligent Systems and Computing.
  • Alavi SA, Mehran K, Vahidinasab V, Catalão JPS, 2021, “Forecast Based Consensus Control for DC Microgrids Using Distributed Long Short-Term Memory Deep Learning Models,” IEEE Transactions on Smart Grid, DOI: 10.1109/TSG.2021.3070959.
  • Vahidinasab V, Ardalan C, Mohammadi-Ivatloo B, Giaouris D, Walker SL, 2021, “Active Building as an Energy System: Concept, Challenges, and Outlook”, IEEE Access, Vol. 9, DOI: 10.1109/ACCESS.2021.3073087.
  • Escobedo P, Ntagios M, Shakthivel D, Navaraj WT, Dahiya R, 2021, Energy Generating Electronic Skin with Intrinsic Tactile Sensing without Touch Sensors, IEEE Transactions on Robotics, Volume: 37, Issue: 2.
  • Christou, A., Gao, Y., Navaraj, W.T., Nassar, H. and Dahiya, R., 2021, 3D Touch Surface for Interactive Pseudo-Holographic Displays. Adv. Intell. Syst. 2000126.
  • Imran A, Hafeez G, Khan I, Usman M, Shafiq Z, Qazi AB, Khalid A, Thoben K-D, 2020, Heuristic-Based Programable Controller for Efficient Energy Management Under Renewable Energy Sources and Energy Storage System in Smart Grid, IEEE Access, vol. 8, pp. 139587-139608,
  • Kulupana G, Talagala DS, Arachchi HK, Akinola M, Fernando A, 2021, “Concealment Support and Error Resilience for HEVC to Improve Consumer Quality of Experience,” IEEE Transactions on Consumer Electronics.
  • Zeinali, M. and Thompson, J., 2021, Comprehensive practical evaluation of wired and wireless internet base smart grid communication. IET Smart Grid.