- Failure Detection
- Smart Environment Prediction
- Activities of Daily Living
- Event Spoofing Detection
- Anomaly Detection Survey
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A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living [Sensor, 2018]
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Failuresense: Detecting sensor failure using electrical appliances in the home [MASS, 2014]
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Using temporal correlation and time series to detect missing activity-driven sensor events [PERCOM, 2015]
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Idea: A system for efficient failure management in smart iot environments [Mobisys, 2016]
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Data reconciliation in a smart home sensor network [Expert Systems with Applications, 2013 ]
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Detecting abnormal events on binary sensors in smart home environments [Pervasive and Mobile Computing, 2016]
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Fault detection for binary sensors in smart home environments [PERCOM, 2015]
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Being SMART about failures: Assessing repairs in SMART homes [Ubicomp,2012]
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A fault detection and diagnosis framework for ambient intelligent systems [Autonomic and Trusted Computing, 2012]
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Generating Bayesian Network Structures for Self-diagnosis of Sensor Networks in the Context of Ambient Assisted Living for Aging Well [Smart Homes and Health Telematics, 2017]
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Fall-curve: A novel primitive for IoT Fault Detection and Isolation [Sensys, 2018]
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Detecting Anomalous Sensor Events in Smart Home Data for Enhancing the Living Experience [AAAI, 2011]
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Towards Sensor Failure Detection in Ambient Assisted Living: Sensors Correlations [CASE, 2018]
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Sensor network data fault types [TOSN, 2009]
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Anomaly detection in wireless sensor networks in a nonstationary environment [Communications Surveys & Tutorials, 2014]
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Sensor faults: Detection methods and prevalence in real-world datasets [TOSN, 2010]
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Online outlier detection in sensor data using non-parametric models [VLDB, 2006]
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Distributed online outlier detection in wireless sensor networks using ellipsoidal support vector machine [Ad hoc networks, 2013]
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Survey on Prediction Algorithms in Smart Homes [IoTJ, 2018]
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Using Temporal Relations in Smart Environment Data for Activity Prediction [ICML 2007]
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Prediction of the Next Sensor Event and Its Time of Occurrence in Smart Homes [ICNAA 2019]
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Unsupervised Recognition of Interleaved Activities of Daily Living through Ontological and Probabilistic Reasoning [Ubicomp, 2016]
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SmartFABER: Recognizing Fine-grained Abnormal Behaviors for Early Detection of Mild Cognitive Impairment [Artificial intelligence in medicine, 2016]
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Reasoning with smart objects’ affordance for personalized behavior monitoring in pervasive information systems [Knowledge and Information Systems, 2019]
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Demultiplexing Activities of Daily Living in IoT enabled Smarthomes [Inforcom, 2016]
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Activity and Anomaly Detection in Smart Home: A Survey [Next Generation Sensors and Systems, 2016]
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Anomaly Detection Models for Smart Home Security [BigDataSecurity, 2019]
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A Probabilistic Ontological Framework for the Recognition of Multilevel Human Activities [Pervasive and ubiquitous computing, 2013]
- Peeves: Physical Event Verification in Smart Homes [CCS, 2019]
- Deep learning for anomaly detection: A survey [arxiv, 2019]