Challenges and Opportunities with Green and Sustainable Computing in Healthcare

Introduction

The pervasive power of the Internet has given almost everyone access to mobile devices in the form of not just mobile phones but also smart watches, and other wearable devices embedded by sensors. Use of such devices with sensors like the accelerometer and gyroscope along with the availability of a wide variety of apps for physical as well as mental health being has made it easier to monitor our health. Development in ubiquitous computing and embedded devices as well as use of sensors brings down the cost of hardware and equipment needed for health monitoring. Thus, technology has helped healthcare have a wider reach and be available to a wider range of people. The applications of IOT in healthcare leading to e-health and m-health can be broadly classified based on the type of health condition targeted, i.e., patient care (chronic diseases and communicable diseases), medicine adherence, caretakers help, and direct contact with doctors, health monitoring, etc. Apart from these, we have the sectors of pharmaceutical industry and independent living. IT has wide applications ranging from assistance in clinical care, real-time health status, remote monitoring of patients in rural and urban areas, helping chronic disease patients in self-care by enabling adherence, post-treatment communication, etc. All these have led to reduction in the dependency of patients on medical equipment and doctors leading to better healthcare. Green computing attempts to effectively utilize computing assets. Computational devices ranging from smart phones, laptops, wearable devices, tablets, to huge servers all have some amount of energy consumption.

Better healthcare leads to economic growth, thus satisfying 3 out of 17 goals of sustainable development, i.e., number 3, which refers to good health and well-being, number 8 to economic growth and number 11 to sustainable cities and communities. Green computing is being used in healthcare with sustainable tactics, which include data center outsourcing and collocation. Hospitals are becoming smart to reduce wastage and practice sustainability. There is an opportunity to bridge the remaining gap between current sustainable usage and the optimal usage and leading to improved efficiency and decline in cost. Power management software, telecommuting and telemedicine are some of the ways to encourage green computing as well as sustainable practices in the area of healthcare. The challenges faced include managing huge quantities of data of all types structured, semi-structured, as well as unstructured, which is amplifying at an “exponential rate,” moving from volume to value, integrating sensors, monitors and instruments in real time, making hospitals smarter at the same time as making them greener.

This chapter begins with the applications of IoT and other technologies promoting green computing such as cloud, edge and fog computing in the healthcare sector. Then, the strategies to enable green and sustainable computing in healthcare sector are discussed. This is followed by a roadmap to get to this by the use of IoT and similar computing practices. At the end, the challenges faced during this are discussed followed by a case study.

Applications of Technology in the Healthcare Sector

Technology and computing is nowadays being used in every realm of life. In the healthcare sector, IoT, big data, cloud computing, machine learning, edge and fog computing have found a lot of applications and uses leading to the development of sub-fields of health analytics, IoT (IoHT, IoMT), computer-aided design (CAD), e-health, m-health, robotic surgery, etc. Health informatics (HI) also known as health information systems is a field which involves the various disciplines of computer science and healthcare such as data analytics and image processing. It deals with the devices, techniques and measures for optimizing the acquisition, repository, retrieval and “use of information in health and biomedicine.”

The use of computers in medicine began as early as the 1950s. Automation of the financial and accounting functions was the first task performed by them. From that to the ECG-enabled Apple watch technology has come a long way. The focus has now shifted to e-health and m-health technologies in the healthcare sector.

Electronic health records (EHRs) was the first step in digitalization of the field of healthcare. Digital records ensured availability of health information of patients which further led to the improvement of patient care and public health. In this, all the data about a patient is present, and it becomes easier to observe any abnormal behavior, thus resulting in quicker diagnosis. The field of remote patient monitoring has been very beneficial in healthcare applications. Internet of Things (IoT), cloud computing, machine learning, and big data are the popular Information and Communication Technology (ICT) paradigms, which are shaping the next generation of e-health and m-health systems.

The discussion begins with the sector, which has immense applications in healthcare field, i.e., ubiquitous computing, which involves IoT and edge computing. This has been widely implemented in health monitoring system. The IoT has been created by the ubiquitous deployment of mobile and sensor devices. These may include self-monitoring of everyday activities through the use of sensors in mobile phones, smart watches for lifestyle monitoring, remote patient monitoring and treatment adherence in chronic disorders or mental ailments. Technology makes patients and elderly become independent and not require the help of their relatives or caregivers. This can be made possible by continuous monitoring and alerting mechanisms [1]. Their applications can be categorized into chronic disorder treatment, mental health monitoring and treatment adherence, lifestyle monitoring, remote patient monitoring to get their physiological status and hospital management. For chronic disorders and elderly care, cloud-based e-health platform has been discussed by [2]. Remote health monitoring of elderly has been carried out by the use of sensors [3]. Cloud technology has also been combined with IoT for remote monitoring [4]. For chronic disorder management like asthma [5] and such other diseases, these have been applied. For mental health, stress management [6], fog and mobile computing techniques have been applied. Medical treatment is now being combined with intelligent systems to get precision medicine. Telemedicine is another medical care practice that has found great use of computing techniques for its wider applications. It includes not just medical care delivery and health education but also consultation, electronic medical record (EMR), diagnosis and treatment. IoT has enabled implementation of deep and rich communication and interaction by multimedia between patients and specialists even from remote areas.

Biomedical systems are another area with increased use of electronic and computing devices. Implantable devices are electronic devices which monitor the user’s physiological parameters. They can replace the biological functions of the human body. Cochlear implants and pacemakers are two examples of such medical devices. Green computing needs to ensure that energy dissipation of devices is minimal. Implantable devices need continuous energy sources and efficient thermal management, along with no compromise in quality. Biomedical servers need renewable energy sources.

Biomedical implantable devices have issues of heat dissipation along with generated electromagnetic fields. To reduce this thermal management is one approach. Another way would be efficient design of the algorithm along with the microchip of the device. This causes reduced amount of power consumption by the device. The power consumed can be reduced significantly by using compact code and having

Use of ICT in healthcare

FIGURE 2.1 Use of ICT in healthcare.

efficient operations. A huge amount of biomedical systems nowadays utilize embedded platforms. Their applications range from physiological monitoring systems and the likes of recognition systems. Migrating the computations of these systems from traditional servers to embedded platforms can lead to better energy consumption.

Some embedded biotelemetry systems monitor patient’s physiological parameters (e.g., weight and blood pressure) along with location and use Bluetooth to transmit data from device to embedded system. Embedded processors perform the basic tasks and transmit data to the centralized processing units. WBANs are also used for providing healthcare services. The increased use of technology in healthcare also generates huge amount of data, which leads to developments in the fields of big data and machine learning. Medical records of patients, hospital records, results and reports of medical examinations are the sources of data. For smarter healthcare, many techniques and architectures for analysis of this data have been provided in the big data field [7,8].

Figure 2.1 shows a graphical representation of the various sectors where ICT has found applications in healthcare. This shows the fields of u-health, big data, remote patient monitoring, etc.

 
Source
< Prev   CONTENTS   Source   Next >