A framework for evidential-reasoning systems
Readings in uncertain reasoning
Combining belief functions when evidence conflicts
Decision Support Systems
Recognizing User Context via Wearable Sensors
ISWC '00 Proceedings of the 4th IEEE International Symposium on Wearable Computers
Reasoning about Uncertain Contexts in Pervasive Computing Environments
IEEE Pervasive Computing
The Knowledge Engineering Review
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Accurate activity recognition in a home setting
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Improving the recognition of interleaved activities
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
On using existing time-use study data for ubiquitous computing applications
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Managing Context Information in Mobile Devices
IEEE Pervasive Computing
Evidential fusion of sensor data for activity recognition in smart homes
Pervasive and Mobile Computing
Review: Ambient intelligence: Technologies, applications, and opportunities
Pervasive and Mobile Computing
Cross-domain activity recognition
Proceedings of the 11th international conference on Ubiquitous computing
Context reasoning using extended evidence theory in pervasive computing environments
Future Generation Computer Systems
Object relevance weight pattern mining for activity recognition and segmentation
Pervasive and Mobile Computing
Modeling and intelligibility in ambient environments
Journal of Ambient Intelligence and Smart Environments
Using Dempster-Shafer theory of evidence for situation inference
EuroSSC'09 Proceedings of the 4th European conference on Smart sensing and context
A context quality model to support transparent reasoning with uncertain context
QuaCon'09 Proceedings of the 1st international conference on Quality of context
Using fuzzy decision tree to handle uncertainty in context deduction
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
On using temporal features to create more accurate human-activity classifiers
AICS'09 Proceedings of the 20th Irish conference on Artificial intelligence and cognitive science
Using a live-in laboratory for ubiquitous computing research
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Modeling and discovering occupancy patterns in sensor networks using latent dirichlet allocation
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Review: Situation identification techniques in pervasive computing: A review
Pervasive and Mobile Computing
A constraint-based approach for proactive, context-aware human support
Journal of Ambient Intelligence and Smart Environments
Capacitive indoor positioning and contact sensing for activity recognition in smart homes
Journal of Ambient Intelligence and Smart Environments
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
An evidential fusion approach for activity recognition in ambient intelligence environments
Robotics and Autonomous Systems
An unsupervised recommender system for smart homes
Journal of Ambient Intelligence and Smart Environments - Ambient and Smart Component Technologies for Human Centric Computing
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The ability to identify the behavior of people in a home is at the core of Smart Home functionality. Such environments are equipped with sensors that unobtrusively capture information about the occupants. Reasoning mechanisms transform the technical, frequently noisy data of sensors into meaningful interpretations of occupant activities. Time is a natural human way to reason about activities. Peoples' activities in the home often have an identifiable routine; activities take place at distinct times throughout the day and last for predicable lengths of time. However, the inclusion of temporal information is still limited in the domain of activity recognition. Evidence theory is gaining increasing interest in the field of activity recognition, and is suited to the incorporation of time related domain knowledge into the reasoning process. In this paper, an evidential reasoning framework that incorporates temporal knowledge is presented. We evaluate the effectiveness of the framework using a third party published smart home dataset. An improvement in activity recognition of 70% is achieved when time patterns and activity durations are included in activity recognition. We also compare our approach with Naïve Bayes classifier and J48 Decision Tree, with temporal evidence theory achieving higher accuracies than both classifiers.