Next Generation Technologies for Smart Healthcare: Challenges, Vision, Model, Trends and Future Directions

Modern industry employs technologies for automation that may include Internet of Things (IoT), Cloud and/or Fog Computing, 5G as well as Artificial Intelligence (AI), Machine Learning (ML), or Blockchain. Currently, a part of research for the new industrial era is in the direction of improving healthcare services. This work throws light on some of the major challenges in providing affordable, efficient, secure and reliable healthcare from the viewpoint of computer and medical sciences. We describe a vision of how a holistic model can fulfill the growing demands of healthcare industry, and explain a conceptual model that can provide a complete solution for these increasing demands. In our model, we elucidate the components and their interaction at different levels, leveraging state‐of‐the art technologies in IoT, Fog computing, AI, ML and Blockchain. We finally describe current trends in this field and propose future directions to explore emerging paradigms and technologies on evolution of healthcare leveraging next generation computing systems

An Edge Computing Based Smart Healthcare Framework for Resource Management

The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time

Cross-SN: a lightweight authentication scheme for a multi-server platform using IoT-based wireless medical sensor network

Several wireless devices and applications can be connected through wireless communication technologies to exchange data in future intelligent health systems (e.g., the Internet of Medical Things (IoMT)). Smart healthcare requires ample bandwidth, reliable and effective communications networks, energy-efficient operations, and quality of service support (QoS). Healthcare service providers host multi-servers to ensure seamless services are provided to the end-users. By supporting a multi-server environment, healthcare medical sensors produce many data transmitted via servers, which is impossible in a single-server architecture. To ensure data security, secure online communication must be considered since the transmitted data are sensitive. Hence, the adversary may try to interrupt the transmission and drop or modify the message. Many researchers have proposed an authentication scheme to secure the data, but the schemes are vulnerable to specific attacks (modification attacks, replay attacks, server spoofing attacks, Man-in-the middle (MiTM) attacks, etc.). However, the absence of an authentication scheme that supports a multi-server security in such a comprehensive development in a distributed server is still an issue. In this paper, a secure authentication scheme using wireless medical sensor networks for a multi-server environment is proposed (Cross-SN). The scheme is implemented with a smart card, password, and user identity. Elliptic curve cryptography is utilized in the scheme, and Burrows–Abadi–Needham (BAN) logic is utilized to secure mutual authentication and to analyse the proposed scheme’s security. It offers adequate protection against replies, impersonation, and privileged insider attacks and secure communication in multi-server parties that communicate with each other

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution