Evidence map›Paper›PMID 42356796›Full record

ArticleSensors (Basel, Switzerland)2026

Design and Validation of a Cyber-Physical Medication Dispensing Platform Integrating Edge AI Verification, Distributed Control, and Cloud Synchronization.

Buddharaksa Phatcharasaksakol, Supaphan Sittithanon, Veerinrada Pianapitham, Vipas Chantrapanichkul, Jing Tang, Ratchatin Chancharoen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Buddharaksa PhatcharasaksakolInternational School of Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand.
Supaphan SittithanonInternational School of Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand.
Veerinrada PianapithamInternational School of Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand.
Vipas ChantrapanichkulInternational School of Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand.
Jing TangChulalongkorn School of Integrated Innovation, Chulalongkorn University, Bangkok 10330, Thailand.
Ratchatin ChancharoenDepartment of Mechanical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand.ORCID 0000-0002-0409-3860

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medication dispensing errors remain a significant concern in healthcare systems, particularly in elderly care and long-term medication management, where incorrect medication delivery may compromise patient safety and treatment outcomes. This study presents the design and experimental validation of a cyber-physical medication dispensing platform integrating robotic manipulation, edge AI-based visual verification, distributed motion control, and cloud synchronization. The platform combines a rotary medication storage mechanism, vacuum-based pill handling, a Klipper-based control framework, and a YOLOv8 perception subsystem deployed on a Hailo AI accelerator for real-time edge inference. Experimental evaluation was conducted under controlled laboratory conditions. Using an environment-specific validation dataset, the perception subsystem achieved a precision of 0.627, recall of 0.739, and mAP@0.5 of 0.786. An adaptive verification strategy was subsequently evaluated to improve dispensing verification under varying pill occupancy conditions. End-to-end system testing comprising 80 dispensing trials achieved an overall dispensing success rate of 86.25%, with no incorrect dispensing events observed. The results demonstrate the feasibility of integrating edge AI verification, distributed control, and cloud connectivity within a cyber-physical medication dispensing platform. The presented system provides a foundation for future research on perception-assisted medication dispensing, long-term deployment, and clinical validation in smart healthcare environments.

Indexed as

Artificial IntelligenceCloud ComputingHumansIntelligent SystemsMedication ErrorsRoboticsautomated medication dispensingcyber–physical systems (CPSs)edge computingInternet of Things (IoT)smart healthcare systems

Identifiers

PMID42356796
PMCPMC13306589

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.