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  6. Fall Detection Model 'RFID Tag Type 2G'

Fall Detection Model 'RFID Tag Type 2G'

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last updated:Jul 17, 2019

礫川システムデザイン事務所
礫川システムデザイン事務所
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Detects falls and tumbles, with forced alarm notifications! The patient's condition is easily understood at a glance.

The "RFID Tag Type2G" is a product that detects falls and alerts notifications. It continuously tracks the patient's location, and when a fall occurs, it notifies the location along with an alarm. With dimensions of 30mm by 30mm and a thickness of only 9.8mm, and a lightweight of 11.5g, it does not create a sense of discomfort when worn. 【Features】 ■ Danger notification for unauthorized exits ■ When detected in a danger zone, it can activate a patrol light and lock doors ■ The dedicated receiver uses PoE power supply, eliminating the need for special electrical wiring ■ Immediately notifies the location of a patient who has fallen ■ If a patient falls, the forced alarm notification system reports where the patient fell and their subsequent condition in real-time *For more details, please refer to the PDF document or feel free to contact us.

    IC tagOther security and surveillance systems
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Fall Detection Model 'RFID Tag Type 2G'

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【Other Features】 ■ Displays the location of patients on the map ■ The patient's condition is easily recognizable by the color around the icon ■ Nearby patients can also be viewed in a list ■ Alarms can be forcibly notified with warning sounds and screen flashing *For more details, please refer to the PDF document or feel free to contact us.

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【Purpose】 ■Detection of falls and drops *For more details, please refer to the PDF document or feel free to contact us.

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Fall Detection Model "RFID Tag Type 2G"

Fall Detection Model "RFID Tag Type 2G"

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礫川システムデザイン事務所

礫川システムデザイン事務所

Information and Communications

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At Tokikawa System Design Office, we provide various application technologies such as medical device management systems, radiation information systems, reporting systems, conference systems, communication tools using SIP, and gateways for HL7 and DICOM. In the future, we will also work on "monitoring systems" utilizing location information systems, as well as "behavior analysis" and "hazard prediction" using AI technology based on those records.

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