{"type":"ScholarlyArticle","title":"PillGood: Automated and Interactive Pill Dispenser Using Facial Recognition for Safe and Personalized Medication","authors":[{"name":"Jonghyeok Kim","slug":"jonghyeok-kim","given":"Jonghyeok","family":"Kim","affiliation":"Yonsei University"},{"name":"Hosung Kwon","slug":"hosung-kwon","given":"Hosung","family":"Kwon","affiliation":"Yonsei University"},{"name":"Jonghyeon Kim","slug":"jonghyeon-kim","given":"Jonghyeon","family":"Kim","affiliation":"Yonsei University"},{"name":"Jinsoo Park","slug":"jinsoo-park","given":"Jinsoo","family":"Park","affiliation":"Yonsei University"},{"name":"Soong-Un Choi","slug":"soong-un-choi","given":"Soong-Un","family":"Choi","affiliation":"Yonsei University"},{"name":"Sookyung Kim","slug":"sookyung-kim","given":"Sookyung","family":"Kim","affiliation":"Palo Alto Research Center (PARC) {kzzzzzzzong , khs01680 , whdgus0606 , 2016145125 ,"}],"abstract":"Safety of taking medicine prescribed differently to each patient in hospital relies on the discernment of medical professionals who deals with measuring pill quantity, packaging, and distributing. It is difficult and time consuming to keep track of medication record of each patient. Also, medication safety is prone to be in risk due to the human error. To help patients get accurate medication following their prescription plan with minimizing human labors and mistakes, we developed PillGood, an automated smart pill dispenser system using facial recognition technique. PillGood provides real-time and personalized guidance to take the correct medicine by alarming patients and distributing exact quantity of pills at specific time following each patient's prescription table. The system notify patients through mobile app and speaker when they need to take the medicine, and detect who the patient is through the machine learning based face recognition. Then, based on each patient's prescribing information, the controller distributes pills to each patient. Results show that PillGood enable highly accurate personalized pill dispensation followed by precise face recognition, benefiting both patients and medical professionals. Videos for demonstrating the system can be found on  https://youtu.be/Wx7bXxRGjXA","doi":"10.24963/ijcai.2022/854","url":"https://ijcai.org/proceedings/2022/854","pdf":"https://ijcai.org/proceedings/2022/0854.pdf","markdown":"https://ijcai.org/proceedings/2022/854.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/854","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Demo Track","track":"Demo Track","number":854,"pages":{"first":5920,"last":5923},"keywords":["Multidisciplinary Topics and Applications: Health and Medicine","Multidisciplinary Topics and Applications: AI Hardware","Computer Vision: Recognition (object detection, categorization)","Computer Vision: Applications","Humans and AI: Applications"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38985349","length_sec":90,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38987206","length_sec":91,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Albaum, 1997] Gerald Albaum. 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