Internet of things, represented by an abstract image of a phone surrounded by home appliances

Industrial Internet of Things (IIoT) research group

Intro

IIoT research group is a multidisciplinary group with members from engineering and computing backgrounds, focusing on industry-driven research. Our group members have strong expertise in: 
  • Sensing, localisation and navigation technologies 
  • Industrial Internet of Things (IIoT) and big data analytics 
  • Intelligent systems 
  • System security 
  • Harvesting and scheduling systems 

Jump to each section of the page:

Those who are interested in PhD position under the areas of expertise of this research group, can directly contact the head of the research group at nagham.saeed@uwl.ac.uk.

IIoT events

Find out more about our upcoming events including our Early Career Talks.

Industrial Internet of Things research group logo

Group members

PhD students

  • Cristiane Girotto (CEng, BEng (Hons), MRes)

    Cristiane Girotto Photo

    Introduction:

    Eng. Cristiane is a PhD student at the University of West London and holds a BEng from the Universidade Federal do Rio Grande do Sul (UFRGS - Brazil), a first BEng(Hons) in civil and environmental engineering from the University of West London (UWL), and a distinction MRes from the University College London (UCL). Her previous research work was related to the analysis of environmental factors sustaining recurrent cholera outbreaks in Sub-Saharan Africa. She was one of the project coordinators on the OVERCOME project, which is a transnational consortium formed by world-leading scientists from the Universities of Exeter, University College London, University of West London, Public Health England, and Aquobex Technologies in the United Kingdom; the University of Malawi, The Polytechnic in Malawi, the National Institute of Meteorology in Mozambique, the Chinhoyi University of Technology; University of Zimbabwe, and University of Ghana in Africa; working on digital innovation in flood early warning and water-related disease prevention for community capacity building and resilience. She also participated in three international projects, published one peer-reviewed conference paper and is now working on a journal article about digital innovation application for preventing climatic hazards related diseases.

    She was awarded the Vice Chancellor Scholarship at UWL to work on her PhD research on the development of AI-based models to improve the performance of Sustainable Drainage Systems (SuDS). Her research interests include urban planning, rainwater management, hydrology and hydraulic modelling, sustainable drainage systems, flood forecasting and early warning, innovative technology applications, nature-based solutions, the internet of things, artificial intelligence, climate change impact on critical urban infrastructure, water-borne disease prevention, climatic hazards impact assessment, mitigation, and resilience strategies, and climate change impact on critical urban infrastructure.

    She is a member of the AWARENESS team representing the UWL at the RAE’s Frontiers Champions 2022 project working to propagate the positive impacts of IoT in water reuse. The group is developing an IoT-based shower gadget that encourages behavioural changes to save water and energy.

    Publications: 

    • Girotto, C; Behzadian, K; Musah, A; Chen, A; Ali, A; Campos, L; (2021) Impact of water and sanitation services on cholera outbreaks in sub-Saharan Africa. In: Proceedings of the AQUA360 – Water for All –Emerging Issues and Innovations. AQUA≈360: Virtual. (In press)

    Conferences:

    • AQUA ≈360 virtual conference: Water for All - Oral presentation - Sept/2021 – Impact of water and sanitation services on cholera outbreaks in sub-Saharan Africa
    • SCE Research & Industry Day - Jun/2022 – Poster presentation at UWL – Analysis of environmental factors supporting recurring cholera outbreaks in Sub-Saharan Africa
    • Panellist for ONWARD Webinar no.5 – Nov/2022 - Analysis of environmental factors supporting recurring cholera outbreaks in Sub-Saharan Africa

    PhD proposal title:

    Development of Artificial Intelligence (AI)-based Models for Performance Improvement of Sustainable Drainage Systems (SuDS)

    Due to the effects of climate change, urban infrastructure is required to adapt quickly while keeping CO2 emissions targets on track. This study aims to make a significant contribution to expand the implementation of sustainable drainage systems (SuDS) for large-scale urban drainage projects, exploring alternatives to increase SuDS performance data, monitoring and management. The methodology used in this study aims to apply different AI techniques to understand SuDS performance and provide practical alternatives from the prediction of rainwater peak flow for a combination of SuDS technologies and different distribution of SuDS on the catchment area.

  • Jamie Pordoy (PhD Student of Computing and Engineering)

    Jamie Pordoy photo

    Introduction:

    After completing an undergraduate degree in computer science (BSc) and a post graduate degree in software engineering (MSc), Jamie pursued his passion for academic research and was awarded the Vice Chancellor Scholarship award at the University of West London. Now a PhD scholar located in the school of computing and engineering, Jamie researches novel Ai applications for healthcare, with a focus on the early detection of generalised tonic-clonic (GTC) seizures for patients diagnosed with epilepsy. Using a multi-sensor approach, Jamie’s research aims to use several IoT sensors (ECG, EMD, ACM) to record the real-time physiological signals of patients during the pre-ictal and ictal phases. A deep neural network (DNN) is then used to detect whether the data has real-time biomarkers that indicate the onset of a GTC seizure. The first 2 years of Jamie’s PhD investigated different types of DNN, and how they could be used to interpret the sensory data recorded from multiple IoT nodes. Now in his final year, Jamie is constructing an intelligent IoT sensory network that will bring together various facets of his PhD to accurately detect GTC seizures in real-time.

    Publications:

    • Pordoy, J., Zhang, Y, Matoorian, N, Zolgharni, M., 2020. Predicting Epileptic Seizures with a Stacked Long Short-Term Memory Network, Int J Auto AI MachLearn, 1(1), pp.93–108.
    • Pordoy, J., Zhang, Y, Matoorian, N, Zolgharni, M., 2020. Seizure Classification Using Person-Specific Triggers. EAI Endorsed Transactions on Collaborative Computing, 18(3), pp.168650.

    Conferences:

    • Pordoy, J., Zhang, Y, Matoorian, N., 2020.A Novel Approach for Seizure Classification Using Patient Specific Triggers: Pilot Study, Collaborative Computing: Networking, Applications and Work sharing, 350, pp.455–468, 2021.
    • Pordoy, J., 2021. Research Seminar - Online SCE (School of Computing and Engineering) Research Seminar
    • Pordoy, J., 2021. UWL Doctoral Conference - (MPhilPhD2021): Research event and doctoral students’ conference. Poster presentation (1st Place).

  • Rakan Armoush

    Rakan Armoush

    Research interest/area:

    Artificial intelligence, unmanned aerial vehicles (UAVs), Internet of Things, real-time processing, edge computing.

    PhD proposal title:

    UAV-assisted Mobile Edge Computing for Optimal Disaster Management: Leveraging Advanced Learning Models

    What the research is about

    Large-scale natural disasters can cause widespread damage and loss of life. Public safety communications (PSC) systems are essential for responding to these disasters, but traditional PSC systems are often not able to meet the demands of large-scale disasters. This paper proposes a new approach to PSC that uses unmanned aerial vehicles and edge computing (EC). UAVs can be used to provide on-demand communication links in areas where the infrastructure has been damaged, and EC can be used to provide computing resources closer to the disaster site, which can reduce latency and improve performance. The proposed approach is evaluated through simulations and experimental results.

Research interest and projects

Professional researching on laptop

We work closely with industry to deliver innovative solutions for society, covering research themes including:

  • IIoT sensor nodes and wearable devices 

  • Sensor fusion in IIoT

  • Augmented reality and wearable technologies 

  • Smart flood warning systems 

  • Smart rainwater harvesting systems 

  • Smart power grid 

  • Intelligent transportation systems

  • An IoT-enabled real-time personalised seizure detection system for diagnosed epileptics (Jamie Pordoy)

    Using a multi-sensor approach, Jamie’s research aims to use several IoT sensors (ECG, EMD, ACM) to record the real-time physiological signals of patients during the pre-ictal and ictal phases. A deep neural network (DNN) is then used to detect whether the data has real-time biomarkers that indicate the onset of a GTC seizure. The first 2 years of Jamie’s PhD investigated different types of DNN, and how they could be used to interpret the sensory data recorded from multiple IoT nodes. Now in his final year, Jamie is constructing an intelligent IoT sensory network that will bring together various facets of his PhD to accurately detect GTC seizures in real-time.

  • Leveraging AI-based technology for data sourcing and improvement of SUDS performance (Cristiane Girotto)

    Due to the effects of climate change, urban infrastructure is required to adapt quickly while keeping CO2 emissions targets on track. This study aims to make a significant contribution to expand the implementation of sustainable drainage systems (SuDS) for large-scale urban drainage projects, exploring alternatives to increase SuDS performance data, monitoring, and management.

    The methodology used in this study aims to apply different AI techniques to understand SuDS performance and provide practical alternatives from the prediction of rainwater peak flow for a combination of SuDS technologies and different distribution of SuDS on the catchment area.

  • Sustainable decision-making digital twin for water-energy-food nexus

    Abstract achieving food security for the growing human population without widespread environmental degradation is one of the biggest challenges of the twenty-first century. Constructed wetlands (CWs) are an excellent example of how the integrated management of water-energy-food nexus in a single system can effectively reverse environmental degradation. CWs are artificial wetlands engineered to provide multiple ecosystem services to semi-arid areas; by treating wastewater and storm-water runoff through microorganisms (as much as 90%), while also providing habitat for wildlife and producing food, through low-tech methods that contribute to significant cost savings. Although these benefits have been locally demonstrated on a small scale, the quantitative benefits across all three resources have not been widely realised. In this project, and for the first time, Digital Twins (DT) will represent the virtual environment of a CW in South Africa (SA) and Malaysia. The prototype will be developed based on a successfully operating CW in a remote village in Cyprus. Consecutively, this will be tested and validated by implementing it in a similar CW in SA and Malaysia. This will enable us to simulate how different processes and equipment configurations affect energy consumption, water quality, and the crops that are being yielded from the treated water. The use of the DT will break the silos around the water-energy-food sectors and will add to the understanding of the nexus concept, minimise the risk of costly failures, and allow for more rapid innovation and development through integration. Additionally, by providing a shared, interactive platform for understanding and exploring complex systems, DT can help to build a more informed and engaged leadership and community around water-energy-food nexus projects in the global south. DT can revolutionise how we approach projects involving the water-energy-food nexus allowing more efficient and effective decision-making, by optimising the interlinkages and interdependencies of these.

    • Funded value: £20,000
    • Funded period: March 2023 - March 2024
    • Funder: RAE-REDAA
    • Project reference: FS-2223-18-102
    • UWL team: Dr Nagham Saeed and Dr Atiyeh Ardakanian

  • Working towards energy efficient wireless network: evaluation for the AI and ML usage project

    5G and beyond networks envision a massive increase in wireless network devices and traffic demands. This translates to significant growth in energy consumption, resulting in high network operation costs. Extending the usage of AI and ML in all the network layers is a business target that may enhance the communication radio interface. Minimising network operation costs and energy consumption will help to reach net zero goals. Collaboration outcomes expected from this work, include a scope report to BT Group, a workshop, a paper, and a developed KTP application for future funded projects led by BT partners.

    • Funded value: £3,000
    • Funded period: February 2023 – August 2023
    • Funder: KE Seed fund
    • UWL team: Dr Nagham Saeed

  • Research projects for PhD and Post Doc candidates

    Digital twin for wetland systems within the water-energy-food nexus

    Primary supervisors: Dr Atiyeh Ardakanian and Dr Nagham Saeed

    Research context

    The proposed PhD project is a continuation of our awarded project from the Royal Academy of Engineering – on utilising digital twins to visualise the water-energy-food nexus.

    The primary objective of this research is to further develop an advanced digital twin of a constructed wetland, aimed at optimising the intersections of water, energy and food systems through integrated modelling and simulation.

    The project will utilise GIS systems, Internet of Things sensors and real-time data to further develop the virtual model. The model aims to simulate water flows, energy dynamics and biomass productivity, enabling the exploration of various management scenarios and operational optimisations.

    By providing a visual and functional simulation of wetland dynamics, this digital twin will serve as a critical tool for researchers, policymakers and environmental engineers. The model aims to enhance decision-making processes, promote sustainable practices and optimise the synergies within the WEF nexus.

    Further information

    Questions regarding academic aspects of the project should be directed to Dr Atiyeh Ardakanian (atiyeh.ardakanian@uwl.ac.uk) or Dr Nagham Saeed (nagham.saeed@uwl.ac.uk).

Past projects

  • Smart Urban Drainage Systems using Artificial Intelligence and Data Mining Techniques

    PhD title of Farzad is “Smart Urban Drainage Systems using Artificial Intelligence and Data Mining Techniques” which aims to “make use of AI and data mining techniques to develop novel analytical tools for enhancing the performance of urban drainage systems in real-time management of urban flood events”. This research follows these objects: “Developing new data-driven models for merging rainfall data as input of urban flood forecasting by using data mining and deep learning techniques”, “Enhancement the performance of real-time prediction of urban flood events in the smart UDS” and “Improving the performance of real-time prediction of urban flooding in UDS through assimilation of physical parameters in the catchment”.

  • OVERCOME - Digital Innovation in Flood Early Warning and Water-Related Disease Prevention for Community Capacity Building and Resilience

    • Funded value: £134,894
    • Funded period: April 2020 – October 2021
    • Funder: EPSRC-Digital Innovation for Development in Africa (DIDA)
    • Project reference: EP/T030089/1
    • UWL team: Dr Ying Zhang and Professor Kourosh Behzadian

    Find out more via the UKRI website.

Selected publications

  • 2023

    Goudarzi, S., Soleymani, S. A., Wang, W., and Xiao, P., "UAV-Enabled Mobile Edge Computing for Resource Allocation Using Cooperative Evolutionary Computation". IEEE Transactions on Aerospace and Electronic Systems, doi: 10.1109/TAES.2023.3251967. https://ieeexplore.ieee.org/abstract/document/10058597

    Soleymani, S., Goudarzi, S., Liu, X. et al. (Accepted: 2023) "Multi-target tracking using a swarm of UAVs by Q-learning algorithm". In: Proceedings of the Sensor Signal Data Processing in Defence (SSPD) 2023 Conference. Sensor Signal Data Processing in Defence (SSPD) 2023 Conference, 12-13 Sep 2023, Edinburgh, Scotland, UK. Institute of Electrical and Electronics Engineers (IEEE). (In Press) https://eprints.whiterose.ac.uk/201100/

    Hossain, J., Marzband, M., Kalam, A., Hossain, M.A., Manojkumar, R., Saeed, N., "Optimizing PV and Battery Energy Storage Systems for Peak Demand Reduction and Cost Savings in Malaysian Commercial Buildings". 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET), 1-6. https://ieeexplore.ieee.org/abstract/document/10149980

    Hossain, J., Kadir, A.F.A., Shareef, H., Manojkumar, R., Saeed, N., Hanafi, A.N., "A Grid-Connected Optimal Hybrid PV-BES System Sizing for Malaysian Commercial Buildings". Sustainability 15 (13), 10564. https://www.mdpi.com/2071-1050/15/13/10564

    ul Khairi, D., Ayaz, F., Saeed, N., Ahsan, K., Ali, S.Z., "Analysis of deep convolutional neural network models for the fine-grained classification of vehicles". Future Transportation 3 (1), 133-149. https://www.mdpi.com/2673-7590/3/1/9

  • 2022

    Ayaz, F., Sheng, Z., Tian, D., Nekovee, M., Saeed, N. "Blockchain-Empowered AI for 6G-Enabled Internet of Vehicles". Electronics 2022, 11, 3339. https://doi.org/10.3390/electronics11203339 

    Pouresmaeil, H., Faramarz, M.G., ZamaniKherad, M., Behzadian, K.  et al. A decision support system for coagulation and flocculation processes using the adaptive neuro-fuzzy inference system. Int. J. Environ. Sci. Technol. 19, 10363–10374 (2022). https://doi.org/10.1007/s13762-021-03848-4 

    Shi, T., Loo, J., et al., "Task Scheduling with Collaborative Computing of MEC System Based on Federated Learning," 2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring), 2022, pp. 1-5, doi: 10.1109/VTC2022-Spring54318.2022.9860987. 

  • 2021

    H. Pouresmaeil, M. Faramarz, M. Zamani, M. Gheibi, A. Fathollahi, K. Behzadian, G. Tian, 2021 A Decision Support System for Coagulation and Flocculation Processes Using the Adaptive Neuro-fuzzy Inference System, International Journal of Environmental Science and Technology, accepted/ in press 2022

    M. Shahsavar, M. Akrami, M. Gheibi, B. Kavianpour, A. Fathollahi, Behzadian, K., 2021. Constructing a smart framework for supplying the biogas energy in green buildings using an integration of response surface methodology, artificial intelligence and petri net modelling. Energy Conversion and Management, 248, p.114794. (IF=9.7 Q1), doi.org/10.1016/j.enconman.2021.114794

    Yeganeh A, M.Y. Heravi, K. Behzadian, and H. Shariatmadar, 2021 Applying a New Systematic Fuzzy FMEA Technique for Risk Management in Light Steel Frame Systems, Journal of Asian Architecture and Building Engineering, 1-22, doi.org/10.1080/13467581.2021.1971994,

    J. Pordoy, Y. Zhang,N. Matoorian and M. Zolgharni, ‘Seizure Classification Using Person-Specific Triggers’, EAI Endorsed Transactions on Collaborative Computing, EAI Publisher, ISSN: 2312-8623, 4(14), February 2021. 

    U.  M.  Butt, S.  Letchmunan, F.  H.  Hassan, M.  Ali, A.  Baqir and H.  H. R. Sherazi, ‘Spatio-Temporal Crime Predictions by Leveraging Artificial Intelligence for Citizens Security in Smart Cities’, IEEE Access, IEEE Press, ISSN: 2169-3536, Vol.9 pp. 47516-47529, March 2021. 

    H. H. R. Sherazi, L. A. Grieco, M. A. Imran and G. Boggia, ‘Energy-Efficient LoRaWAN for Industry 4.0 Applications’, IEEE Transactions on Industrial Informatics, IEEE Press, ISSN: 1551-3203, 17(2), pp.  891-902, February 2021.

  • 2020

    J. Pordoy, Y. Zhang, N. Matoorian and M. Zolgharni, ‘Predicting Epileptic Seizures with a Stacked Long Short-Term Memory Network’, International Journal of Automation, Artificial Intelligence and Machine Learning, Research Lake, ISSN: 2563-7568, 1(1), October 2020.  

    J. Pordoy, Y. Zhang and N. Matoorian, ‘A Novel Approach for Seizure Classification Using Patient Specific Triggers: Pilot Study’. In Gao et al. (Eds), Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2020), Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, ISBN: 978-3-030-67539-4, pp. 455-468, Vol. 350. Springer, Cham. 

    U.  M.  Butt, S.  Letchmunan, F. H. Hassan, M. Ali, A.  Baqir and H. H. R. Sherazi, ‘Spatio-Temporal Crime HotSpot Detection and Prediction: A Systematic Literature Review’, IEEE Access, IEEE Press, ISSN: 2169-3536, Vol.  8, pp.  166553-166574, September 2020. 

    O. Landa-Cansigno, K. Behzadian, D. I. Davila-Cano, L. C. Campos, ‘Performance Assessment of Water Reuse Strategies Using Integrated Framework of Urban Water Metabolism and Water-energy-pollution Nexus’, Environmental Science and Pollution Research, 27:4582–4597, 2020. 

  • 2019

    Z. Dar, A. Ahmad, F. A. Khan, F. Zeshan, R. Iqbal, H. H. R. Sherazi, A K. Bashir, ‘A Context-aware Encryption Protocol Suite for Edge Computing-based IoT Devices’, The Journal of Supercomputing, Springer Science Press, ISSN: 0920-8542, 76(4), pp. 2548-2567, October 2019. 

    K. Awan, H. H. R. Sherazi, A. Ali, R. Iqbal, Z. A. Khan, and M. Mukherjee, ‘Energy Aware Cluster-based Routing Optimization for WSNs in Livestock Industry’, Transactions on Emerging Telecommunications Technologies,  John Wiley and Sons Press, ISSN: 2161-2935, 30(12), December 2019. 

    A. Cagnano, H. H. R. Sherazi, and E. De Tuglie, ‘Communication System Architecture of an Industrial-scale Microgrid: A Case Study’, Internet Technology Letters, John Wiley and Sons Press, ISSN: 2476-1508, 2(6), November/December 2019. 

    M. J. Ahmed, S. Iqbal, K. M. Awan, K. Sattar, Z. A. Khan, H. H. R. Sherazi, ‘A Congestion Aware Route Suggestion Protocol for Traffic Management in Internet of Vehicles’, Arabian Journal for Science and Engineering, Springer Press, ISSN: 2191-4281, 45(4), pp. 2501-2511, August 2019. 

    D. Saeed, R. Iqbal, H. H. R. Sherazi, and U. G. Khan, ‘Evaluating Near Field Communication Tag Security for Identity Theft Prevention’, Internet Technology Letters, John Wiley and Sons Press, ISSN: 2476-1508, 2(5), July 2019. 

    H. H. R. Sherazi, R. Iqbal, F. Ahmad, Z. A. Khan and M. H. Chaudary, ‘DDoS Attack Detection: A Key Enabler for Sustainable Communication in Internet of Vehicles’, Sustainable Computing, Informatics and Systems, ScienceDirect, ISSN: 2210-5379, Vol. 23, pp. 13–20, September 2019. 

    A. Atchome, H. H. R. Sherazi, T.O. Edoh, L. A. Grieco and A. Vianou, ‘A Hybrid Network Model Embracing NB-IoT and D2D Communications: Stochastic Geometry Analysis’, Proceedings of 11th EAI International Conference on e‐Infrastructure and e‐Services for Developing Countries (AFRICOMM 2019), Porto-Novo, Benin, 2019. 

    H. H. R. Sherazi, R. Iqbal and L. A. Grieco, ‘AREA: Adaptive Resilience Algorithm for Clustering in Vehicular Ad-hoc Networks’, Proceedings of 18th IEEE International Symposium on Network Computing and Applications (NCA 2019), Cambridge, USA, 2019. 

    A. Urbonavicius and N. Saeed, ‘IoT Leak Detection System for Building Hydronic Pipes’, International Journal of Engineering and Manufacturing, 9(5), 2019. 

    H. Gao, K. K. Dluzniak, H. Xia, W. Jie, Y. Chen, W. Xing, X. Wang and Z. Wang, ‘A Service Clustering Method based on Wisdom of Crowds’, 2019 IEEE International Congress on Big Data, Milan, Italy, 8th-13th July 2019, IEEE Press, ISBN: 978-1-7281-2772-9. 

    M. Momeni, Z. Zakeri, M. Esfandiari, K. Behzadian, S. Zahedi and V. Razavid, ‘Comparative analysis of agricultural water pricing between Azerbaijan Provinces in Iran and the state of California in the US: A hydro-economic approach’, Agricultural Water Management, 2233 (20), 2019. 

    O. Landa-Cansigno, K. Behzadian, D. I. Davila-Cano and L. C. Campos, ‘Performance Assessment of Water Reuse Strategies Using Integrated Framework of Urban Water Metabolism and Water-energy-pollution Nexus’, Environmental Science and Pollution Research, 2019. 

    A. J. Veldhuis, J. Glover, D. Bradley, K. Behzadian and et al., ‘Re-distributed Manufacturing and the Food-water-energy Nexus: Opportunities and Challenges’, Production Planning and Control, 30(7), 2019. 

  • 2018

    H. H. R. Sherazi, M. A. Imran, G. Boggia and L. A. Grieco, ‘Energy Harvesting in LoRaWAN: A Cost Analysis for the Industry 4.0’, IEEE Communications Letters, IEEE Press, ISSN: 1089-7798, 22(11), pp. 2358-2361, November 2018. 

    H. H. R. Sherazi, G. Piro, A. Grieco, G. Boggia, ‘When Renewable Energy Meets LoRa: A Feasibility Analysis on Cable-less Deployments’, IEEE Internet of Things Journal, IEEE Press, ISSN: 2327-4662, 5(6), pp. 5097-5108, December 2018. 

    H. H. R. Sherazi, L. A. Grieco, and G. Boggia, ‘A Comprehensive Review on Energy Harvesting MAC Protocols in WSNs: Challenges and Tradeoffs’, Ad Hoc Networks, ScienceDirect ISSN: 1570-8705 Vol. 71, PP. 117–134, March 2018. 

    F. Piadeh, M. Ahmadi and K. Behzadian, ‘Reliability Assessment for Industrial Wastewater Recycling Hybrid Systems: Using Combined Event Tree and Fuzzy Fault Tree Analysis’, Journal of Cleaner Production, Vol. 201, 2018. 

    F. Rahmani, K. Muhammed, K. Behzadian and R. Farmani, ‘Optimal Operation of Water Distribution Systems Using a Graph Theory–Based Configuration of District Metered Areas’, Journal of Water Resources Planning and Management, 144(8), 2018. 

    H. Sun, W. Jie, J. Loo, L. Wang, S. Ma, G. Han, Z. Wang and W. Xing, ‘A Parallel Self-Organizing Overlapping Community Detection Algorithm Based on Swarm Intelligence for Large Scale Complex Networks’, Future Generation Computer Systems, Vol. 89, 2018. 

    Y. Li, W. Ren, T. Zhu, Y. Ren, Y. Qin and W. Jie, ‘RIMS: A Real-time and Intelligent Monitoring System for Live-broadcasting Platforms’, Future Generation Computer Systems, Vol.87, 2018. 

    J. Yan, Y. Ma, L. Wang, K. K. R. Choo and W. Jie, A Cloud-based Remote Sensing Data Production System, Future Generation Computer Systems, Vol. 86, 2018 

    T. Ngalo, H. Xiao, B. Christianson and Y. Zhang, Threat Analysis of Software Agents in Online Banking and Payments, 2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, 16th International Conference on Pervasive Intelligence and Computing, 4th International Conference on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech), Athens, Greece, 12th-15th August 2018. IEEE Computer Society Press, ISBN: 978-1-5386-7518-2.  

    S. Sacchi, N. M. Dhutia, M. J. Shun-Shin, M. Zolgharni, N. Sutaria, D. P. Francis and G. D. Cole, ‘Doppler Assessment of Aortic Stenosis: a 25-operator Study Demonstrating Why Reading the Peak Velocity is Superior to Velocity Time Integral’, European Heart Journal of Cardiovasc Imaging, 19(12), 2018. 

Activities

The IIoT research group is committed to supporting WIE and Women in STEM, therefore we are sponsoring the events:

A graphic representing artificial intelligence

Seminar: The quest for AI systems

  • Date: Wednesday 27 March 2024, 12pm - 1pm
  • Location: Ealing site, BY.01.017

AI is currently talked about everywhere, but do we have the right underlying technologies available to truly power and deliver what we set out to achieve?

The aim of this presentation is to look at the reality of what our current computers are good at and not so good at to then explore if there are more effective ways of achieving AI functionality. This should demonstrate that to create AI systems that deliver functionalities like that of the human brain, there will be a need for some quite different lines of thinking to be explored in more depth.

Register here

  • Sensors (MDPI) journal: call for submissions

    We are inviting you to contribute to a forthcoming special issue for the journal Sensors. This special issue, titled "Optimizing the Future: Securing and Streamlining IoT Resource Allocation in the 6G Era with Edge Computing and UAV Integration" and edited by IIoT research group member Dr Shidrokh Goudarzi, aims to explore the forefront of IoT and 6G technologies, focusing on innovative solutions for resource allocation, security, and efficiency.

    The integration of edge computing and UAVs (Unmanned Aerial Vehicles) in the IoT ecosystem presents novel opportunities and challenges, especially as we transition into the 6G era. We are looking for original research articles, case studies, and comprehensive reviews that address these topics, providing insights into the future of IoT and 6G technologies.

    Submission details:

    • Special issue title: Optimizing The Future: Securing and Streamlining IoT Resource Allocation in the 6G Era with Edge Computing and UAV Integration
    • Journal: Sensors (MDPI)
    • Submission deadline: 25 July 2024
    • Link for submission and more information

    Please feel free to reach out to shidrokh.goudarzi@uwl.ac.uk directly if you have any questions or need further details about the special issue or submission process. Additionally, we would appreciate it if you could share this invitation with any colleagues or researchers in your network who might be interested in contributing.

  • 2024 Early Career Talks (IEEE WIE UK&I Ambassadors Network)

    IEEE WIE UK&I's goal is to facilitate the recruitment and retention of women in technical disciplines globally. We envision a vibrant community of IEEE women and men collectively using their diverse talents to innovate for the benefit of humanity. IEEE WIE UK and Ireland through the Ambassadors Network is calling women in engineering to participate in a technical, inspirational and empowering session “Early Career Talks”. The previous ECT events were very successful, they have attracted attention from both academia and industry. This event converges the state-of-the-art research and technology in engineering and computing besides establishing networking/collaboration links and exploring new opportunities for developing interactions between academia, industry, and government, fostering economic and social development.

    What are the themes?

    We offer two themes in this call which take place online and will be around March and June 2024 respectively.

    Theme 1: Unlocking the potential of offshore renewable energy: innovations, challenges and environmental sustainability

    • Explore the dynamic landscape of offshore renewable energy in this theme, covering advancements, challenges and innovations in harnessing sustainable energy from offshore sources. Submissions may address topics such as wind, solar, wave and tidal energy, along with associated technologies, environmental impact assessments and offshore infrastructure developments.

    Theme 2: Revolutionising robotics: harnessing the power of 5G and emerging technologies for next-generation applications

    • Delve into the cutting-edge intersection of robotics and 5G technology in this theme, showcasing research and developments that leverage high-speed connectivity to propel robotics into new realms. Submissions can span a spectrum of applications, including industrial automation, healthcare robotics, autonomous vehicles and the integration of emerging technologies beyond 5G, providing insights into the future of robotic systems.

Past activities

Contact us

The research group is always looking for talented postgraduate research students and potential collaborations. 

For further information about PhD study in these areas and the collaborative opportunities, please contact Research Group Head,  Dr Nagham Saeed on nagham.saeed@uwl.ac.uk.

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