{"id":{"repo_id":"nott-trent","oai_identifier":"oai:irep.ntu.ac.uk:60"},"canonical_url":"https://search.dev.ndltd.org/etd/nott-trent/oai:irep.ntu.ac.uk:60","repository":{"repo_id":"nott-trent","name":"Nottingham Trent University","base_url":"https://irep.ntu.ac.uk/cgi/oai2"},"display":{"title":"Identification and prediction of abnormal behaviour activities of daily living in intelligent environments","abstract":"The aim of this research is to investigate efficient mining of useful information from a sensor network forming an Ambient Intelligence (AmI) environment. In this thesis, we investigate methods for supporting independent living of the elderly (and specifically patients who are suffering from dementia) by means of equipping their home with a simple sensor network to monitor their behaviour and identify their Activities of Daily Living (ADL). Dementia is considered to be one of the most important causes of disability in the elderly. Mostpatients would prefer to use non-intrusive technology to help them tomaintain their independence. Such monitoring and prediction would allow the caregiver to see any trend in the behaviour of the elderly person and to be informed of any abnormal behaviour.","abstract_html":"The aim of this research is to investigate efficient mining of useful information from a sensor network forming an Ambient Intelligence (AmI) environment. In this thesis, we investigate methods for supporting independent living of the elderly (and specifically patients who are suffering from dementia) by means of equipping their home with a simple sensor network to monitor their behaviour and identify their Activities of Daily Living (ADL). Dementia is considered to be one of the most important causes of disability in the elderly. Mostpatients would prefer to use non-intrusive technology to help them tomaintain their independence. Such monitoring and prediction would allow the caregiver to see any trend in the behaviour of the elderly person and to be informed of any abnormal behaviour.","abstract_has_math":false,"creators":["Mahmoud, SM"],"institution":"Nottingham Trent University","degree_name":"phd","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-24T06:30:42Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Mahmoud, SM"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2012"]},{"key":"dc:date.issued","label":"Date","values":["2012"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Nottingham Trent University"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://irep.ntu.ac.uk/id/eprint/60/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["phd"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://irep.ntu.ac.uk/id/eprint/60/1/212198_Sawsan%20Mahmoud%20Thesis.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The aim of this research is to investigate efficient mining of useful information from a sensor network forming an Ambient Intelligence (AmI) environment. In this thesis, we investigate methods for supporting independent living of the elderly (and specifically patients who are suffering from dementia) by means of equipping their home with a simple sensor network to monitor their behaviour and identify their Activities of Daily Living (ADL). Dementia is considered to be one of the most important causes of disability in the elderly. Mostpatients would prefer to use non-intrusive technology to help them tomaintain their independence. Such monitoring and prediction would allow the caregiver to see any trend in the behaviour of the elderly person and to be informed of any abnormal behaviour."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Identification and prediction of abnormal behaviour activities of daily living in intelligent environments"]}]}],"canonical_facts":{"dc:creator":["Mahmoud, SM"],"dc:date":["2012"],"dc:date.issued":["2012"],"dc:description.abstract":["The aim of this research is to investigate efficient mining of useful information from a sensor network forming an Ambient Intelligence (AmI) environment. In this thesis, we investigate methods for supporting independent living of the elderly (and specifically patients who are suffering from dementia) by means of equipping their home with a simple sensor network to monitor their behaviour and identify their Activities of Daily Living (ADL). Dementia is considered to be one of the most important causes of disability in the elderly. Mostpatients would prefer to use non-intrusive technology to help them tomaintain their independence. Such monitoring and prediction would allow the caregiver to see any trend in the behaviour of the elderly person and to be informed of any abnormal behaviour."],"dc:format":["text"],"dc:identifier.uri":["https://irep.ntu.ac.uk/id/eprint/60/1/212198_Sawsan%20Mahmoud%20Thesis.pdf"],"dc:language":["en"],"dc:publisher.institution":["Nottingham Trent University"],"dc:relation.isreferencedby":["https://irep.ntu.ac.uk/id/eprint/60/"],"dc:title":["Identification and prediction of abnormal behaviour activities of daily living in intelligent environments"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["phd"]},"updated_at":"2026-07-24T06:30:42Z"}