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Remote Safety Assistance and Health Monitoring System

机译:远程安全协助和健康监测系统

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Objectives: With the increase in the aging population, the health of the elderly has been a widespread concern. There rises a need to develop a system which does remote monitoring and safety assistance. Methods: In this proposed work, heart Beats per Minute (BPM), temperature, precise location of the patient, seizure detection and fall detection of the elderly individual is monitored continuously. The precise location of the aged individuals is achieved by means of Radio-Frequency Identification (RFID) technology. Seizure detection uses accelerometer sensor. Fall detection is identified using gyro sensor. Temperature and hearts beat per minute are calculated using heart beat sensor and lm35 sensor. Findings: The algorithms developed for the seizure and fall detection are tested on different conditions and the results are satisfactory. Fall detection algorithm completely differentiates between the fall and bend of the individual. Always a doctor or care takers cannot be present for monitoring. Hence there rises a need to send alert messages when the fall or seizure is detected. Alerts are sending to caretakers or doctors using internet. Improvement/Applications: The work can be further extended by monitoring several individuals at the same time and developing a mobile app for remote monitoring and assisting.
机译:目标:随着人口老龄化的增加,老年人的健康受到广泛关注。迫切需要开发一种进行远程监控和安全协助的系统。方法:在这项拟议的工作中,持续监测每分钟的心跳(BPM),体温,患者的精确位置,癫痫发作检测和跌倒检测。老年人的精确位置是通过射频识别(RFID)技术实现的。癫痫发作检测使用加速度传感器。使用陀螺仪传感器识别跌倒检测。使用心跳传感器和lm35传感器计算每分钟的温度和心跳。结果:针对癫痫和跌倒检测开发的算法在不同条件下进行了测试,结果令人满意。跌倒检测算法可以完全区分个体的跌倒和弯曲。总是不能有医生或护理人员在现场进行监视。因此,当检测到跌倒或癫痫发作时,有必要发送警报消息。警报正在通过互联网发送给看护者或医生。改进/应用程序:可以通过同时监视多个人并开发用于远程监视和协助的移动应用程序来进一步扩展工作。

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