Smart Cities and Healthcare: A Systematic Review

"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

Systematic literature review of context-awareness applications supported by smart cities’ infrastructures

Since none of the existing systematic reviews of the literature related to smart cities have focused on smart cities applications using context-aware features, this study aims to provide a comprehensive view of (1) the characteristics of context-aware applications supported by smart cities’ infrastructures, (2) the characteristics of the context-aware technologies being used, and (3) the maturity level of the identified applications. An electronic search was conducted on Scopus, Web of Science, and IEEE Xplore databases, combining relevant keywords. After the studies’ selection, 27 studies were included. The results show the interest in using context-aware features to develop smart cities’ applications targeting public health, tourism experience, urban mobility, active citizenship, shopping experience, management of urban infrastructures, public alerts, recommenders, and smart environments. Moreover, the applications reported by the included studies do not allow the execution of actions without the explicit consent of the users, and they integrate personal sensors, sensors deployed in the city and crowdsourcing mechanisms to acquire primary context attributes (i.e., location, activity, and environment) and secondary context attributes (i.e., speed, physical activity, points of interest, stress, and tourists’ emotions). In addition, the included studies present scarce details about context reasoning, data privacy, integrity, and confidentiality, data aggregation and accuracy, and data interoperability. Finally, the results also indicate low maturity level of the developed applications, which is evidenced by the lack of user-centred evaluations, as well as by the difficulty in integrating important technologies being developed for smart cities.

Datafication Process in the Concept of Smart Cities

Datafication, currently visible in almost all areas of the human life, turned out to be a very good basis for the development of the concept of smart cities. Smart city authorities use various types of information and communication technologies (ICT) in the process of managing individual urban infrastructure systems. Modern ICT solutions enable city authorities to collect and process data about citizens. The purpose of this article is to determine the correlation between datafication and a city’s position in the global smart cities ranking, with particular emphasis on the role of social media. To achieve the goal, the method of examining documents was used. Two independent reports were thoroughly analyzed: the Smart City Index 2020 and the Digital 2021 Local Country Headlines. The study showed that the more residents use social media, the better a city performs in the ranking. Additionally, a directly proportional relationship between the level of urbanization and the percentage of people using the Internet was demonstrated. The results of the presented study may be important primarily for people and institutions responsible for creating modern urban space.

Cost-Effectiveness Assessment of Internet of Things in Smart Cities

With the ongoing rapid urbanization of city regions and the growing need for (cost-)effective healthcare provision, governments need to address urban challenges with smart city interventions. In this context, impact assessment plays a key role in the decision-making process of assessing cost-effectiveness of Internet of Things-based health service applications in cities, as it identifies the interventions that can obtain the best results for citizens' health and well-being. We present a new methodology to evaluate smart city projects and interventions through the MAFEIP tool, a recent online tool for cost-effectiveness analysis that has been used extensively to test information and communications technology solutions for healthy aging. Resting on the principles of Markov models, the purpose of the MAFEIP tool is to estimate the outcomes of a large variety of social and technological innovations, by providing an early assessment of the likelihood of achieving anticipated impacts through interventions of choice. Thus, the analytical model suggested in this article provides smart city projects with an evidence-based assessment to improve their efficiency and effectivity, by comparing the costs and the efforts invested, with the corresponding results.

Introducing the “15-Minute City”: Sustainability, Resilience and Place Identity in Future Post-Pandemic Cities

The socio-economic impacts on cities during the COVID-19 pandemic have been brutal, leading to increasing inequalities and record numbers of unemployment around the world. While cities endure lockdowns in order to ensure decent levels of health, the challenges linked to the unfolding of the pandemic have led to the need for a radical re-think of the city, leading to the re-emergence of a concept, initially proposed in 2016 by Carlos Moreno: the “15-Minute City”. The concept, offering a novel perspective of “chrono-urbanism”, adds to existing thematic of Smart Cities and the rhetoric of building more humane urban fabrics, outlined by Christopher Alexander, and that of building safer, more resilient, sustainable and inclusive cities, as depicted in the Sustainable Development Goal 11 of the United Nations. With the concept gaining ground in popular media and its subsequent adoption at policy level in a number of cities of varying scale and geographies, the present paper sets forth to introduce the concept, its origins, intent and future directions.

SmartWalk BAN: Using Body Area Networks to Encourage Older Adults to Perform Physical Activity

Due to the demographic ageing of the world’s population and the respective consequences, it is necessary to guarantee that older adults can be active and maintain their independence and autonomy for longer. The aim of the SmartWalk system is to promote walks in the city in order to stimulate physically active lifestyles. Body area networks are used to aggregate data collected by different type of sensors, which are transmitted to a server to support informed decisions of caregivers when planning physical activities for their care receivers. This article presents the SmartWalk system and reports an experimental setup that was developed to assess the performance of the current implementation and the respective critical components. According to the results, the SmartWalk system presents good performance in terms of battery usage, data upload, capacity to recover from connectivity failures and wireless coverage of its body area network.

The Internet of Things: Impact and Implications for Health Care Delivery

The Internet of Things (IoT) is a system of wireless, interrelated, and connected digital devices that can collect, send, and store data over a network without requiring human-to-human or human-to-computer interaction. The IoT promises many benefits to streamlining and enhancing health care delivery to proactively predict health issues and diagnose, treat, and monitor patients both in and out of the hospital. Worldwide, government leaders and decision makers are implementing policies to deliver health care services using technology and more so in response to the novel COVID-19 pandemic. It is now becoming increasingly important to understand how established and emerging IoT technologies can support health systems to deliver safe and effective care. The aim of this viewpoint paper is to provide an overview of the current IoT technology in health care, outline how IoT devices are improving health service delivery, and outline how IoT technology can affect and disrupt global health care in the next decade. The potential of IoT-based health care is expanded upon to theorize how IoT can improve the accessibility of preventative public health services and transition our current secondary and tertiary health care to be a more proactive, continuous, and coordinated system. Finally, this paper will deal with the potential issues that IoT-based health care generates, barriers to market adoption from health care professionals and patients alike, confidence and acceptability, privacy and security, interoperability, standardization and remuneration, data storage, and control and ownership. Corresponding enablers of IoT in current health care will rely on policy support, cybersecurity-focused guidelines, careful strategic planning, and transparent policies within health care organizations. IoT-based health care has great potential to improve the efficiency of the health system and improve population health.

SMS: A Secure Healthcare Model for Smart Cities

Technological innovations have enabled the realization of a utopian world where all objects of everyday life, as well as humans, are interconnected to form an “Internet of Things (IoT).” These connected technologies and IoT solutions have led to the emergence of smart cities where all components are converted into a connected smart ecosystem. IoT has envisioned several areas of smart cities including the modern healthcare environment like real-time monitoring, patient information management, ambient-assisted living, ambient-intelligence, anomaly detection, and accelerated sensing. IoT has also brought a breakthrough in the medical domain by integrating stake holders, medical components, and hospitals to bring about holistic healthcare management. The healthcare domain is already witnessing promising IoT-based solutions ranging from embedded mobile applications to wearable devices and implantable gadgets. However, with all these exemplary benefits, there is a need to ensure the safety and privacy of the patient’s personal and medical data communicated to and from the connected devices and systems. For a smart city, it is pertinent to have an accessible, effective, and secure healthcare system for its inhabitants. This paper discusses the various elements of technology-enabled healthcare and presents a privacy-preserved and secure “Smart Medical System (SMS)” framework for the smart city ecosystem. For providing real-time analysis and responses, this paper proposes to use the concept of secured Mobile Edge Computing (MEC) for performing critical time-bound computations on the edge itself. In order to protect the medical and personal data of the patients and to make the data tamper-proof, the concept of blockchain has been used. Finally, this paper highlights the ways to capture and store the medical big data generated from IoT devices and sensors.

How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic

SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health Organization. Thanks to the latest advancements in the field of molecular and computational techniques and information and communication technologies (ICTs), artificial intelligence (AI) and Big Data can help in handling the huge, unprecedented amount of data derived from public health surveillance, real-time epidemic outbreaks monitoring, trend now-casting/forecasting, regular situation briefing and updating from governmental institutions and organisms, and health facility utilization information. The present review is aimed at overviewing the potential applications of AI and Big Data in the global effort to manage the pandemic.