RESUMEN
Intelligent medical management is one of several modern city and society management fields where the Internet of Things (IoT) is essential. Smart cities' current engagement between technology and the health care system is strengthened by the intelligent IoT's limitless networking capabilities for big data analysis in medicine. Allows for more practical methods for efficiently monitoring patients' health and providing medical services remotely online assessment of patients' health status by doctors, nurses, and other healthcare professionals. The of the current study aims to provide a full examination of the function of IoT in medical management systems, analyse the available concerns, and address many of the open questions. It also aims to provide an up-to-date and comprehensive review of this field. Enabling technology and hints at a variety of uses There have been suggested research plans. The following are some examples of IoT applications from previous studies: wearable technology, monitoring technology, rehabilitation technology, telehealth, behaviour modification, smart city, and smart home. This comprehensive review identifies the crucial elements that make it possible to comprehend the healthcare possibilities and obstacles providers to put IoT applications into action. Lastly, anticipated COVID-19 effects on IoT uptake this review assessed in the field of healthcare. © 2022 IEEE.
RESUMEN
Contactless authentication has become a trending topic these days, especially in this Corona pandemic situation, where contactless access systems are precautionary steps. The two most important contactless authentication systems right now are facial recognition and gait recognition. With having a possibility of spook attacks on facial recognition, gait patterns have gained popularity especially in the high-secured zones. Gait biometrics is considered as the next generation of biometrics which can enable identification of subjects even through a certain distance, avoiding any surface-contact. However, complex challenges gait patterns are mainly the view angles and distances for environmental setup and crucial gait features for algorithm setup. Hence, the authors are extending their previous work which is identifying 'specific targets' based on their gait patterns in Defence applications. We combined facial recognition designed with our anti-spoofing algorithm and gait patterns which gave on an average 92% accuracy irrespective of their background, motion, and angle. © 2020 IEEE.