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Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods (2020)
Journal Article
Caleb-Solly, P., Gupta, P., & McClatchey, R. (2020). Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods. Neural Computing and Applications, 32(16), 12351 - 12362. https://doi.org/10.1007/s00521-020-04737-6

© 2020, The Author(s). This paper investigates the utility of unsupervised machine learning and data visualisation for tracking changes in user activity over time. This is done through analysing unlabelled data generated from passive and ambient smar... Read More about Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods.

A framework for semi-supervised adaptive learning for activity recognition in healthcare applications (2018)
Conference Proceeding
Gupta, P., & Caleb-Solly, P. (2018). A framework for semi-supervised adaptive learning for activity recognition in healthcare applications. In Engineering Applications of Neural Networks. , (3-15). https://doi.org/10.1007/978-3-319-98204-5_1

With the growing popularity of the Internet of Things and connected home products, potential healthcare applications in a smart-home context for assisted living are becoming increasingly apparent. However, challenges in performing real-time human act... Read More about A framework for semi-supervised adaptive learning for activity recognition in healthcare applications.