Holographic Counterpart Modelling of Wearable IoT Data for Forensic Timeline Reconstruction

Jul 17, 2026

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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.

LanguageEnglish

CategoryResearch & Report

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Pages8

Reading Time20 min

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Holographic Counterpart Modelling of Wearable IoT Data for Forensic Timeline Reconstruction and Custodial Monitoring Ambarish G. Mohapatra, Anita Mohanty, Randa Allafi, Amnah Alshahrani, Saied Alshahrani, Hany Mahgoub, and Nouf Helal Alharbi Abstract—New opportunities for forensic analysis of health and behavioral data are provided by the emergence of wearable Internet of Things (IoT) devices, e.g., smartwatches and fitness trackers. The paper introduces the Holographic Counterpart (HC) framework as a device-agnostic digital twin that can be used in a correctional setting to enable consistent, tamper-free, and protected digital monitoring. The framework uses a dual-way model of acquisition, one side being local extraction through Cellebrite UFED, Magnet AXIOM, and Autopsy, and the other side involving the cloud retrieval via vendor Application Programming Interfaces (APIs) so that it enjoys redundancy, interoperability, and evidentiary integrity. The information on Apple Watch, Fitbit Versa, and Samsung Galaxy Watch, plus publicly available data, produced more than 1.2 million multimodal points in 50 inmates and 120 sessions. A structured workflow of calibration, synchronization, sensor fusion, and composite anomaly scoring is designed to bolster the reliability of an analytical procedure. Experimental validation was 92 % precision, 89 % recall, and an F1-score of 0.90, which eliminated undetected anomalies by 37% and guaranteed 92% forensic traceability, which beat Z-score, DBSCAN, and Isolation Forest baselines. The HC framework proves to be Received 2 September 2025; revised 27 October 2025; accepted 9 November 2025. Date of publication 21 November 2025; date of current version 25 March 2026 . This work was supported in part by the Deanship of Research and Graduate Studies at King Khalid University, under Grant RGP2/288/46; in part by the Princess Nourah bint Abdulrahman University Researchers Supporting Project, Riyadh, Saudi Arabia, under Grant PNURSP2025R732; in part by Northern Border University, Saudi Arabia, under Project NBUFPEJ-2025-170-05; and in part by the Deanship of Graduate Studies and Scientific Research, University of Bisha, through the Fast-Track Research Program. (Corresponding author: Anita Mohanty.) Ambarish G. Mohapatra and Anita Mohanty are with the Department of Electronics Engineering, Silicon University, Bhubaneswar, Odisha 751024, India (e-mail: [ambarish.mohapatra@gmail.com](ambarish.mohapatra@gmail.com); anitamohanty076@gmail. com) . Randa Allafi is with the Department of Computer Science, College of Science, Northern Border University, Arar 73213, Saudi Arabia (e-mail: [Rndallafi@nbu.edu.sa](Rndallafi@nbu.edu.sa)) . Amnah Alshahrani is with the Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia (e-mail: [aamshahrani@pnu.edu.sa](aamshahrani@pnu.edu.sa)). Saied Alshahrani is with the

Jul 17, 2026

Upload by Oliver