[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-31111":3,"doc-seo-31111":21},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"file_id":15,"file_url":16,"file_type":17,"file_size":18,"view_count":4,"is_deleted":4,"is_public":19,"is_downloadable":19,"audit_status":19,"update_tm":20},31111,8796095461610,"Oliver","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Holographic Counterpart Modelling of Wearable IoT Data for Forensic Timeline Reconstruction","Wearable IoT devices such as smartwatches and fitness trackers generate health and behavioral streams that can support forensic timeline reconstruction and custodial monitoring in correctional environments. The paper presents the Holographic Counterpart (HC) framework as a device-agnostic digital twin enabling consistent, tamper-free, and protected monitoring through dual-way acquisition: local extraction via forensic tools and cloud retrieval via vendor APIs for redundancy and evidentiary integrity. Experiments on multiple devices and inmate sessions produce over 1.2 million multimodal points, with a workflow covering calibration, synchronization, sensor fusion, and composite anomaly scoring. Reported results show strong precision, recall, F1-score, reduced undetected anomalies, and improved forensic traceability beyond baseline methods, while addressing ethical requirements like data minimization, consent, and privacy protection.","cbCaid8y4OIlhioi","https://ap.wps.com/l/cbCaid8y4OIlhioi","pdf",1823118,1,1778619720,{"code":4,"msg":22,"data":23},"ok",{"site_id":24,"language":25,"slug":26,"title":13,"keywords":27,"description":14,"schema_data":28,"social_meta":62,"head_meta":64,"extra_data":66,"updated_unix":20},105,"en","holographic-counterpart-modelling-of-wearable-iot-data-for-forensic-timeline-reconstruction","",{"@graph":29,"@context":61},[30,47],{"@type":31,"itemListElement":32},"BreadcrumbList",[33,37,41,44],{"item":34,"name":35,"@type":36,"position":19},"https://docshare.wps.com","Home","ListItem",{"item":38,"name":39,"@type":36,"position":40},"https://docshare.wps.com/document/","Document",2,{"item":42,"name":12,"@type":36,"position":43},"https://docshare.wps.com/document/research-report/",3,{"item":45,"name":13,"@type":36,"position":46},"https://docshare.wps.com/document/holographic-counterpart-modelling-of-wearable-iot-data-for-forensic-timeline-reconstruction/31111",4,{"url":45,"name":13,"@type":48,"author":49,"headline":13,"publisher":51,"fileFormat":54,"description":14,"dateModified":55,"datePublished":55,"encodingFormat":54,"isAccessibleForFree":56,"interactionStatistic":57},"DigitalDocument",{"name":9,"@type":50},"Person",{"url":34,"name":52,"@type":53},"DocShare","Organization","application/pdf","2026-05-12",true,{"@type":58,"interactionType":59,"userInteractionCount":4},"InteractionCounter",{"@type":60},"ViewAction","https://schema.org",{"og:url":45,"og:type":63,"og:title":13,"og:site_name":52,"og:description":14},"article",{"robots":65,"canonical":45},"index,follow",{"doc_id":7,"site_id":24}]