INTERNET OF THINGS Research Projects
Ongoing research projects
Research, develop, test, and trial a low-cost labelling solution to address the issue of labelling inconsistencies to
provide verifiable and traceable packaging information of meat products in the box
mismatches happens between products, product labels, and box labels
Funded by Australian Meat Processing Corporation
Research, develop, test, and trial a solution to address product quality issues in production of Vegemite:
Reduce the waste and reprocessing of the raw materials to produce the Vegemite product
Enable complete automation of these
Predict machine settings and related operator actions to ensure product consistency
Funded by Bega Cheese
Research and Development of a Live inbound Milk Supply Chain Monitoring Solution for:
Real-time milk pick-up logistics
Highly accurate in-bound milk forecasting
Just-in-time milk delivery to processing plants
Real-time milk monitoring in the plant
Funded by CRC-P (https://www.business.gov.au/grants-and-programs/cooperative-research-centres-projects-crcp-grants)
Partners: Bega Cheese, Optus, Software AG
Real-time Internet of Things
Devise novel techniques to manage TS-IoT applications in a way their time-bound requirements are fulfilled and incorporate the techniques into a platform and evaluate their ability to meet the time-bound requirements of such applications.
Korala, H., Jayaraman, P.P., Yavari, A., and Georgakopoulos, D., 2020. APOLLO: A Platform for Experimental Analysis of Time Sensitive Multimedia IoT Applications. In Proceedings of the 18th International Conference on Advances in Mobile Computing and Multimedia (MoMM ’20), (pp. 104 -113), Chiang Mai, Thailand. https://doi.org/10.1145/3428690.3429176.
Korala, H., Yavari, A., Georgakopoulos, D., Jayaraman, P.P, 2020. Design and Implementation of a Platform for Managing Time-Sensitive IoT Applications. In Proceedings of the 6th IEEE International Conference on Collaboration and Internet Computing (CIC), (pp. 44-53), Atlanta, USA. https://doi.org/10.1109/CIC50333.2020.00016.
Korala, H., Georgakopoulos, D., Yavari, A., Jayaraman, P.P, 2021. A Time-Sensitive IoT Data Analysis Framework. In Proceedings of the 54th Hawaii International Conference on System Sciences, (pp. 7185 -7194), Hawaii, USA. https://doi.org/10.24251/HICSS.2021.865– Nominated for the Best Paper Award under Software Technology track.
Propose, design, implement, evaluate and validate a Cyber-Twins based programming framework to support the development of Industry 4.0 applications.
Bamunuarachchi. D, Banerjee. A, Jayaraman. P.P, and Georgakopoulos. D. 2020. Cyber twins supporting industry 4.0 application development. In Proceedings of the 18th International Conference on Advances in Mobile Computing & Multimedia (MoMM '20). Association for Computing Machinery, New York, NY, USA, 64–73. DOI:https://doi.org/10.1145/3428690.3429177
Exploring the opportunity for applying digital twins in the healthcare context is an emerging research area that has the potential to support more personalised care. A recognised aspect in cancer care is the need for more personalised treatment planning to complement the recent advances in precision medicine. This work is one of the first attempts to use digital twins in this capacity and represents an amalgamation of three key domains: clinical, digital health and computer science respectively.
Wickramasinghe N, Jayaraman PP, Zelcer J, Forkan AR, Ulapane N, Kaul R, Vaughan S. A Vision for Leveraging the Concept of Digital Twins to Support the Provision of Personalised Cancer Care. IEEE Internet Computing. 2021 Mar 11.
Blockchain Internet of Things
Semantic IoT Blockchain that designed specifically for IoT devices that integrates:
Marketplace to provide services for clients
Universal IoT devices discovery engine
Registration tool for IoT devices
Semantic query engine
Universal Integration solution
Dawod, A., Georgakopoulos, D., Jayaraman, P.P. & Nirmalathas, A. 2020, ‘An IoT-owned service for global IoT device discovery, integration and (Re)use’, Proceedings - 2020 IEEE 13th International Conference on Services Computing, SCC 2020, pp. 312-320
Dawod, A., Georgakopoulos, D., Jayaraman, P.P. & Nirmalathas, A. 2019, ‘Advancements towards Global IoT device discovery and integration’, Proceedings - 2019 IEEE International Congress on Internet of Things, ICIOT 2019 - Part of the 2019 IEEE World Congress on Services, pp. 147-155
past research projects
Open Source Cloud Solution for Internet of Things
OpenIoT is an open source middleware for getting information from sensor clouds, without worrying what exact sensors are used. Read more about the project and Internet-of-Things technologies. Largely discussed, the Internet-of-Things (IoT) will be an integral component of the Future Internet (FI) and therefore should be smoothly integrated within FI service delivery models and the emerging utility based cloud computing paradigms.
OpenIoT investigates the efficient ways to formulate and manage IoT cloud-based environments i.e. environments comprising IoT “entities” and resources (such as sensors, actuators and smart devices) running on the cloud and offering utility-based (i.e. pay-as-you-go) IoT services.OpenIoT is perceived as a natural extension to cloud computing implementations, which will allow access to additional and increasingly important IoT based resources and capabilities. In particular, OpenIoT researches and provide the means for formulating and managing environments comprising IoT resources, which can deliver on-demand utility IoT services such as sensing as a service as an example, in multiple domains.
OpenIoT is pertinent to a wide range of interrelated scientific and technological areas spanning: (a) Middleware for sensors and sensor networks, (b) Ontologies, semantic models and annotations for representing internet-connected objects, along with semantic open-linked data techniques (c) Cloud/Utility computing, including utility based security and privacy schemes.
More information about the project: http://openiot.eu/
Open source code repository: https://github.com/OpenIotOrg/openiot
Privacy Preserving Internet of Things
Security models for data collection, access and analysis in an IoT platform that incorporates n data stores (where n 2) in different servers or cloud providers
Data access control scheme uses a homomorphic encryption
Prem Prakash Jayaraman, Xuechao Yang, Ali Yavari, Dimitrios Georgakopoulos, and Xun Yi. 2017. Privacy preserving Internet of Things. Future Gener. Comput. Syst. 76, C (November 2017), 540-549. DOI: https://doi.org/10.1016/j.future.2017.03.001