{"id":"W4226247552","doi":"10.1109/access.2022.3157726","title":"Activities Recognition, Anomaly Detection and Next Activity Prediction Based on Neural Networks in Smart Homes","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Universiti Kebangsaan Malaysia","keywords":"Autoencoder; Computer science; Activity recognition; Anomaly detection; Artificial intelligence; Deep learning; Recurrent neural network; Artificial neural network; Machine learning; Long short term memory; Anomaly (physics); Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005603152,0.0002133693,0.0002573082,0.0005125636,0.0004370665,0.0005968705,0.000483431,0.00007967148,0.00003910752],"category_scores_gemma":[0.00003725566,0.0002449949,0.00006961429,0.0009041445,0.000045545,0.003335404,0.000230045,0.0004933212,0.000003185323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002449704,"about_ca_system_score_gemma":0.00005603548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006006917,"about_ca_topic_score_gemma":0.0005847102,"domain_scores_codex":[0.9977946,0.0005808602,0.0002583468,0.0006338198,0.0004142552,0.0003180706],"domain_scores_gemma":[0.9987565,0.0004972265,0.0002100379,0.0003923432,0.00005960177,0.00008425694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003581249,0.0004085153,0.03106578,0.00004385237,0.00002759776,0.00003967752,0.0004282109,0.01751869,0.002550644,0.000004897265,0.0001880127,0.947366],"study_design_scores_gemma":[0.0008963607,0.0003435804,0.1030391,0.00002924895,0.00000878531,0.00005275357,0.00007538751,0.8909097,0.003933033,0.0001113085,0.0003166606,0.0002840341],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8377966,0.00003078378,0.1590948,0.0003339693,0.001799416,0.0004279726,0.00002622676,0.0002487384,0.000241545],"genre_scores_gemma":[0.9988617,0.000007403744,0.00004044834,0.0004472051,0.0001540984,0.0004346989,0.000008911706,0.00001898041,0.00002656424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.947082,"threshold_uncertainty_score":0.9990603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04288334898084416,"score_gpt":0.2593795181084371,"score_spread":0.2164961691275929,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}