{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108186"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108186","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Scaling IoT-based noise cancellation to multiple noise sources","abstract":"A recent development integrating Internet-of-Things (IoT) sensing techniques with active noise cancellation (ANC) has demonstrated certain benefits over the conventional methods for ANC, including wideband cancellation without blocking the ear and non-causal adaptive filtering. These benefits, however, can only be observed in acoustic environments with a single noise source. This thesis presents a new design for an IoT-based active noise cancellation system that can effectively cancel multiple independent noise sources. By incorporating multiple reference microphone inputs, the new system can estimate the unique acoustic channels between different sources of noise and the listener. Through simulation and hardware experiments, this new design is evaluated and shown to achieve significant improvement in cancellation over the previous implementation of IoT-based ANC.","abstract_html":"A recent development integrating Internet-of-Things (IoT) sensing techniques with active noise cancellation (ANC) has demonstrated certain benefits over the conventional methods for ANC, including wideband cancellation without blocking the ear and non-causal adaptive filtering. These benefits, however, can only be observed in acoustic environments with a single noise source. This thesis presents a new design for an IoT-based active noise cancellation system that can effectively cancel multiple independent noise sources. By incorporating multiple reference microphone inputs, the new system can estimate the unique acoustic channels between different sources of noise and the listener. Through simulation and hardware experiments, this new design is evaluated and shown to achieve significant improvement in cancellation over the previous implementation of IoT-based ANC.","abstract_has_math":false,"creators":["Collins, Michael Liam"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Hassanieh, Haitham"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-26T23:58:46Z","date_published":"2020-08-26T23:58:46Z","updated_at":"2026-07-22T22:24:47Z","subjects":["Active noise cancellation"],"languages":["en"],"rights":["Copyright 2020 Michael Collins"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108186","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hassanieh, Haitham"]},{"key":"dc:creator","label":"Author","values":["Collins, Michael Liam"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-08-26T23:58:46Z","2022-08-26T23:58:55Z","2020-05-12","2020-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Active noise cancellation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Michael Collins"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108186"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A recent development integrating Internet-of-Things (IoT) sensing techniques with active noise cancellation (ANC) has demonstrated certain benefits over the conventional methods for ANC, including wideband cancellation without blocking the ear and non-causal adaptive filtering. These benefits, however, can only be observed in acoustic environments with a single noise source. This thesis presents a new design for an IoT-based active noise cancellation system that can effectively cancel multiple independent noise sources. By incorporating multiple reference microphone inputs, the new system can estimate the unique acoustic channels between different sources of noise and the listener. Through simulation and hardware experiments, this new design is evaluated and shown to achieve significant improvement in cancellation over the previous implementation of IoT-based ANC.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Michael Collins, accepted the attached license on 2020-05-11 at 17:56.","The student, Michael Collins, submitted this Thesis for approval on 2020-05-11 at 18:06.","This Thesis was approved for publication on 2020-05-12 at 14:09.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15340 on 2020-08-25 at 17:31:01","Made available in DSpace on 2020-08-26T23:58:46Z (GMT). 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These benefits, however, can only be observed in acoustic environments with a single noise source. This thesis presents a new design for an IoT-based active noise cancellation system that can effectively cancel multiple independent noise sources. By incorporating multiple reference microphone inputs, the new system can estimate the unique acoustic channels between different sources of noise and the listener. Through simulation and hardware experiments, this new design is evaluated and shown to achieve significant improvement in cancellation over the previous implementation of IoT-based ANC.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01","The student, Michael Collins, accepted the attached license on 2020-05-11 at 17:56.","The student, Michael Collins, submitted this Thesis for approval on 2020-05-11 at 18:06.","This Thesis was approved for publication on 2020-05-12 at 14:09.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15340 on 2020-08-25 at 17:31:01","Made available in DSpace on 2020-08-26T23:58:46Z (GMT). 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