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All Outputs (11)

Tailored risk assessment and forecasting in intermittent claudication (2024)
Journal Article
Ravindhran, B., Prosser, J., Lim, A., Lathan, R., Mishra, B., Hitchman, L., Smith, G. E., Carradice, D., Thakker, D., Chetter, I. C., & Pymer, S. (2024). Tailored risk assessment and forecasting in intermittent claudication. BJS Open, 8(1), Article zrad166. https://doi.org/10.1093/bjsopen/zrad166

Background: Guidelines recommend cardiovascular risk reduction and supervised exercise therapy as the first line of treatment in intermittent claudication, but implementation challenges and poor patient compliance lead to significant variation in man... Read More about Tailored risk assessment and forecasting in intermittent claudication.

Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring (2023)
Journal Article
Yemson, R., Kabir, S., Thakker, D., & Konur, S. (2023). Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring. Computers, 12(11), Article 238. https://doi.org/10.3390/computers12110238

With the increasing amount of data collected by IoT devices, detecting complex events in real-time has become a challenging task. To overcome this challenge, we propose the utilisation of semantic web technologies to create ontologies that structure... Read More about Ontology Development for Detecting Complex Events in Stream Processing: Use Case of Air Quality Monitoring.

From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model (2023)
Journal Article
Kureshi, R. R., Thakker, D., Mishra, B. K., & Barnes, J. (2023). From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model. Sensors, 23(7), Article 3613. https://doi.org/10.3390/s23073613

The topic of indoor air pollution has yet to receive the same level of attention as ambient pollution. We spend considerable time indoors, and poorer indoor air quality affects most of us, particularly people with respiratory and other health conditi... Read More about From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model.

FedMSA: A Model Selection and Adaptation System for Federated Learning (2022)
Journal Article
Sun, R., Li, Y., Shah, T., Sham, R. W., Szydlo, T., Qian, B., Thakker, D., & Ranjan, R. (2022). FedMSA: A Model Selection and Adaptation System for Federated Learning. Sensors, 22(19), Article 7244. https://doi.org/10.3390/s22197244

Federated Learning (FL) enables multiple clients to train a shared model collaboratively without sharing any personal data. However, selecting a model and adapting it quickly to meet user expectations in a large-scale FL application with heterogeneou... Read More about FedMSA: A Model Selection and Adaptation System for Federated Learning.

Dynamic Data Streams for Time-Critical IoT Systems in Energy-Aware IoT Devices Using Reinforcement Learning (2022)
Journal Article
Habeeb, F., Szydlo, T., Kowalski, L., Noor, A., Thakker, D., Morgan, G., & Ranjan, R. (2022). Dynamic Data Streams for Time-Critical IoT Systems in Energy-Aware IoT Devices Using Reinforcement Learning. Sensors, 22, Article 2375. https://doi.org/10.3390/s22062375

Thousands of energy-aware sensors have been placed for monitoring in a variety of scenarios, such as manufacturing, control systems, disaster management, flood control and so on, requiring time-critical energy-efficient solutions to extend their life... Read More about Dynamic Data Streams for Time-Critical IoT Systems in Energy-Aware IoT Devices Using Reinforcement Learning.

Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring (2022)
Journal Article
Kureshi, R., Mishra, B., Thakker, D., John, R., Walker, A., Simpson, S., Thakkar, N., & Wante, A. (2022). Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring. Sensors, 22(3), Article 1093. https://doi.org/10.3390/s22031093

With the emergence of Low-Cost Sensor (LCS) devices, measuring real-time data on a large scale has become a feasible alternative approach to more costly devices. Over the years, sensor technologies have evolved which has provided the opportunity to h... Read More about Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring.

Using citizen science to complement IoT data collection: a survey of motivational and engagement factors in technology-centric citizen science projects (2021)
Journal Article
Ali, M. U., Mishra, B. K., Thakker, D., Mazumdar, S., & Simpson, S. (2021). Using citizen science to complement IoT data collection: a survey of motivational and engagement factors in technology-centric citizen science projects. IoT, 2(2), 275--309. https://doi.org/10.3390/iot2020015

A key aspect of the development of Smart Cities involves the efficient and effective management of resources to improve liveability. Achieving this requires large volumes of sensors strategically deployed across urban areas. In many cases, however, i... Read More about Using citizen science to complement IoT data collection: a survey of motivational and engagement factors in technology-centric citizen science projects.

Towards design and implementation of Industry 4.0 for food manufacturing (2021)
Journal Article
Konur, S., Lan, Y., Thakker, D., Morkyani, G., Polovina, N., & Sharp, J. (2023). Towards design and implementation of Industry 4.0 for food manufacturing. Neural Computing and Applications, 35(33), 23753–23765. https://doi.org/10.1007/s00521-021-05726-z

Today’s factories are considered as smart ecosystems with humans, machines and devices interacting with each other for efficient manufacturing of products. Industry 4.0 is a suite of enabler technologies for such smart ecosystems that allow transform... Read More about Towards design and implementation of Industry 4.0 for food manufacturing.

A Semantic Knowledge-Based Framework for Information Extraction and Exploration (2021)
Journal Article
Aljamel, A., Osman, T., & Thakker, D. (2021). A Semantic Knowledge-Based Framework for Information Extraction and Exploration. International Journal of Decision Support System Technology, 13(2), 85--109. https://doi.org/10.4018/IJDSST.2021040105

The availability of online documents that describe domain-specific information provides an opportunity in employing a knowledge-based approach in extracting information from web data. This research proposes a novel comprehensive semantic knowledge-ba... Read More about A Semantic Knowledge-Based Framework for Information Extraction and Exploration.

An Internet of Things-enabled decision support system for circular economy business model (2020)
Journal Article
Mboli, J. S., Thakker, D., & Mishra, J. L. (2022). An Internet of Things-enabled decision support system for circular economy business model. Software: Practice and Experience, 52(3), 772--787. https://doi.org/10.1002/spe.2825

The traditional linear economy using a take-make-dispose model is resource intensive and has adverse environmental impacts. Circular economy (CE) which is regenerative and restorative by design is recommended as the business model for resource effici... Read More about An Internet of Things-enabled decision support system for circular economy business model.