救护车无人机使用机器学习,轻量级加密和可变图像隐写的紧急医疗援助

Indrajit Das, Sanjoy Roy, Sumagna Dey, Tulsi Dey, Piyali Roy
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引用次数: 0

摘要

每天都有大量的人在等待救援车辆准时到达现场时遭受痛苦或最终死亡。造成这种延误的主要原因是交通堵塞、街道堵塞、救护车无法到达等等。紧急救护无人机或无人机(UAV, Unmanned Aerial Vehicle)可能是解决这一问题的更好可行方案,如本文所提出的那样,在空中路径上行驶,不受任何地面障碍物的影响。救护车无人机将由坐在医院控制室的人来控制。这将是在紧急情况下最快的医疗援助。这架无人机将携带医疗设备,并利用从移动应用程序接收到的病人的GPS位置,毫无阻碍地到达现场。然后,无人机可以将患者的数据音频和视频流传输到医院、医疗中心,并将必要的指令传达给附近的观众或当地医生,以便使用合适的设备(ECG、Pulse Sensor、Oximeter等)进行患者诊断,并使用Haar级联分类器检测人脸,使用LBPH算法识别人脸。本文对静止图像和视频图像的人脸识别进行了对比研究,静止图像和视频图像的平均准确率分别为99.4%和99.34%。此外,针对医生不在医院的情况,设计了一个带有帮助决策树的自主系统,可以由患者确定疾病的可能原因。安全的信息传输是通过轻量级加密和可变MSB - LSB图像隐写完成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emergency Medical Assistance by Ambulance Drone Using Machine Learning, Light-Weight Cryptography and Variable Image Steganography
A huge amount of people suffer or eventually die every day waiting for the rescue vehicle to reach the spot on time. The primary cause for this delay is traffic jams, blockage in streets, inaccessibility of ambulance and so forth. An emergency ambulance drone or UAV (Unmanned Aerial Vehicle) could be a better feasible solution to this problem travel the aerial path and is unaffected by any terrestrial obstacles, as proposed in this paper. The ambulance drone would be controlled by a human sitting in the hospital control room. This would be the quickest possible medical assistance in case of an emergency. The drone would carry medical aid and using the patient's GPS location, which it receives from the mobile application, can reach the spot without any hindrance. Thereafter the drone can start the audio and video streaming of patient's data to the hospitals, medical centers and necessary instructions can be communicated to the nearby spectators or local doctors for using the right equipment (ECG, Pulse Sensor, Oximeter, etc) for patients diagnosis and detect the face with Haar cascade classifier and recognize the face with LBPH algorithm. In this, a comparative study has been done over face recognition between still and video images, the average accuracy of still and video images is 99.4% and 99.34% respectively. Also, for the situation, when doctors are not present in the hospital, an autonomous system has been designed with the help decision tree that can determine the probable cause of the disease by the patient. The secure information transfer is done via lightweight cryptography and Variable MSB – LSB Image steganography.
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