IoT for Smart Cities: Machine Learning Approaches in Smart Healthcare - A Review
Abstrak
Smart city is a collective term for technologies and concepts that are directed toward making cities efficient, technologically more advanced, greener and more socially inclusive. These concepts include technical, economic and social innovations. This term has been tossed around by various actors in politics, business, administration and urban planning since the 2000s to establish tech-based changes and innovations in urban areas. The idea of the smart city is used in conjunction with the utilization of digital technologies and at the same time represents a reaction to the economic, social and political challenges that post-industrial societies are confronted with at the start of the new millennium. The key focus is on dealing with challenges faced by urban society, such as environmental pollution, demographic change, population growth, healthcare, the financial crisis or scarcity of resources. In a broader sense, the term also includes non-technical innovations that make urban life more sustainable. So far, the idea of using IoT-based sensor networks for healthcare applications is a promising one with the potential of minimizing inefficiencies in the existing infrastructure. A machine learning approach is key to successful implementation of the IoT-powered wireless sensor networks for this purpose since there is large amount of data to be handled intelligently. Throughout this paper, it will be discussed in detail how AI-powered IoT and WSNs are applied in the healthcare sector. This research will be a baseline study for understanding the role of the IoT in smart cities, in particular in the healthcare sector, for future research works.
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Varun G. Menon Yuanbo Chai Xingwang Li + 5 lainnya
6 Januari 2021
The outbreak of chronic diseases such as COVID-19 has made a renewed call for providing urgent healthcare facilities to the citizens across the globe. The recent pandemic exposes the shortcomings of traditional healthcare system, i.e., hospitals and clinics alone are not capable to cope with this situation. One of the major technology that aids contemporary healthcare solutions is the smart and connected wearables. The advancement in Internet of Things (IoT) has enabled these wearables to collect data on an unprecedented scale. These wearables gather context-oriented information related to our physical, behavioural and psychological health. The big data generated by wearables and other healthcare devices of IoT is a challenging task to manage that can negatively affect the inference process at the decision centres. Applying big data analytics for mining information, extracting knowledge and making predictions/inferences has recently attracted significant attention. Machine learning is another area of research that has successfully been applied to solve various networking problems such as routing, traffic engineering, resource allocation, and security. Recently, we have seen a surge in the application of ML-based techniques for the improvement of various IoT applications. Although, big data analytics and machine learning are extensively researched, there is a lack of study that exclusively focus on the evolution of ML-based techniques for big data analysis in the IoT healthcare sector. In this paper, we have presented a comprehensive review on the application of machine learning techniques for big data analysis in the healthcare sector. Furthermore, strength and weaknesses of existing techniques along with various research challenges are highlighted. Our study will provide an insight for healthcare practitioners and government agencies to keep themselves well-equipped with the latest trends in ML-based big data analytics for smart healthcare.
A. Haque F. Blaabjerg Himanshu Sharma
23 April 2021
Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to efficiently manage the automated operation of the internet of things (IoT) nodes deployed in smart cities. In smart cities, the major IoT applications are smart traffic monitoring, smart waste management, smart buildings and patient healthcare monitoring. The small size IoT nodes based on low power Bluetooth (IEEE 802.15.1) standard and wireless sensor networks (WSN) (IEEE 802.15.4) standard are generally used for transmission of data to a remote location using gateways. The WSN based IoT (WSN-IoT) design problems include network coverage and connectivity issues, energy consumption, bandwidth requirement, network lifetime maximization, communication protocols and state of the art infrastructure. In this paper, the authors propose machine learning methods as an optimization tool for regular WSN-IoT nodes deployed in smart city applications. As per the author’s knowledge, this is the first in-depth literature survey of all ML techniques in the field of low power consumption WSN-IoT for smart cities. The results of this unique survey article show that the supervised learning algorithms have been most widely used (61%) as compared to reinforcement learning (27%) and unsupervised learning (12%) for smart city applications.
Mohammed S. Al-kahtani Faheem Khan Whangbo Taekeun
31 Juli 2022
The Internet of Things (IoT) is an innovative technology with billions of sensors in various IoT applications. Important elements used in the IoT are sensors that collect data for desired analyses. The IoT and sensors are very important in smart cities, smart agriculture, smart education, healthcare systems, and other applications. The healthcare system uses the IoT to meet global health challenges, and the newest example is COVID-19. Demand has increased during COVID-19 for healthcare to reach patients remotely and digitally at their homes. The IoT properly monitors patients using an interconnected network to overcome the issues of healthcare services. The aim of this paper is to discuss different applications, technologies, and challenges related to the healthcare system. Different databases were searched using keywords in Google Scholar, Elsevier, PubMed, ACM, ResearchGate, Scopus, Springer, etc. This paper discusses, highlights, and identifies the applications of IoT healthcare systems to provide research directions to healthcare, academia, and researchers to overcome healthcare system challenges. Hence, the IoT can be beneficial by providing better treatments using the healthcare system efficiently. In this paper, the integration of the IoT with smart technologies not only improves computation, but will also allow the IoT to be pervasive, profitable, and available anytime and anywhere. Finally, some future directions and challenges are discussed, along with useful suggestions that can assist the IoT healthcare system during COVID-19 and in a severe pandemic.
Makó Csaba Amir H. Mosavi Mehdi Sookhak + 7 lainnya
2022
The manuscript represents a comeprehensive and systematic literature review on the machine learning methods in the emerging applications of smart city. Application domains include the essential aspect of the smart cities including the energy, healthcare, transportation, security, and pollution. The methodology presents the state-of-the-art, taxonomy, evaluation and model performance. The study concludes that the hybrid models and ensembles are the best performers since they exhibit both high accuracy and not-costly complexity. On the other hand, the deep learning (DL) techniques had higher accuracy than the hybrid models and ensembles, but they demanded relatively higher computation power. Moreover, all these advanced ML methods had a slower processing speed than the single methods. Likewise, the support vector machine (SVM) and decision tree (DT) generally outperformed the artificial neural network (ANN) for accuracy and other metrics. However, since the difference is negligible, it can be concluded that using either of them is appropriate. The study’s findings identify the pros and cons of the methods in each application for future researchers, practitioners, and policy-makers for the right problem within the context of smart cities.
Adib Habbal N. A. Askar Ziyodulla Yusupov + 3 lainnya
2022
The Internet of Things (IoT) refers to the interconnected framework of web-connected objects that can collect and transfer information over a remote network without requiring any human intervention. The rapid progression in the development of IoT-based devices and their expansion towards making the medical care facility financially more savvy, proactive, and customized, has given rise to the development of the "Internet of Medical Things (IoMT)" that are assumed to function proactively in all domains of the healthcare industry. Within this framework, the IoMT-based healthcare system delivers various advantages, such as quick and unfailing treatment, enhanced communication, cost minimization, etc., through the exploitation of several new technologies. For instance, machine learning has significantly helped with the exploitation of various healthcare systems; fog computing not only minimises the cost of communication but also provides low latency; blockchain delivers its users a much better way of protecting sensitive and confidential information and data they possess. In this survey, a comprehensive elaboration of the IoMT-based healthcare systems based on modern technologies was conducted. This article describes various techniques and solutions of IoMT healthcare systems in the context of emerging technologies, and the related future trends and applications for a better understanding of how IoMT can enhance the healthcare industry now and in future.
Daftar Referensi
1 referensiArtikel yang Mensitasi
4 sitasiA Review of Emerging Technologies for IoT-Based Smart Cities
Alistair Barros Moumita Chanda + 6 lainnya
28 November 2022
Smart cities can be complemented by fusing various components and incorporating recent emerging technologies. IoT communications are crucial to smart city operations, which are designed to support the concept of a “Smart City” by utilising the most cutting-edge communication technologies to enhance city administration and resident services. Smart cities have been outfitted with numerous IoT-based gadgets; the Internet of Things is a modular method to integrate various sensors with all ICT technologies. This paper provides an overview of smart cities’ concepts, characteristics, and applications. We thoroughly investigate smart city applications, challenges, and possibilities with solutions in recent technological trends and perspectives, such as machine learning and blockchain. We discuss cloud and fog IoT ecosystems in the in capacity of IoT devices, architectures, and machine learning approaches. In addition we integrate security and privacy aspects, including blockchain applications, towards more trustworthy and resilient smart cities. We also highlight the concepts, characteristics, and applications of smart cities and provide a conceptual model of the smart city mega-events framework. Finally, we outline the impact of recent emerging technologies’ implications on challenges, applications, and solutions for futuristic smart cities.
Smart cities and smart governance models for future cities
E. Papageorgiou S. Trang + 1 lainnya
28 November 2022
In the last two decades, the concept of smart cities has attracted significant research and policy attention. Despite its extensive discussion in literature, the term smart city is a fuzzy concept (Albino et al., 2015; Angelidou, 2014; Anthopoulos, 2015). It commonly refers to environments in which information and communication technologies (ICTs) are utilized to offer innovative services to citizens in order to enhance their well-being and to stimulate sustainable economic growth (Yigitcanlar et al., 2018). According to Giffinger et al. (2007), the key defining characteristics of smart cities include smart economy, smart people, smart governance, smart mobility, smart environment, and smart living, addressing key topics such as economic competitiveness, educational level of citizens, quality of social interactions, flexibility of labor market, governmental strategies, innovative transportation systems, sustainable resource management, or public safety. However, since the introduction of the term smart cities in the ’90 s, numerous perspectives on smart cities have emerged (e.g., Chourabi et al., 2012; Dameri & Cocchia, 2013; Hosseini et al., 2018; Yigitcanlar et al., 2018). One predominant perspective relates to the role of smart ICTs to improve the quality of citizens’ life (e.g., Bifulco et al., 2016; Dameri, 2017; Ferro et al., 2013; Gade, 2019; Van Dinh et al., 2020). Smart ICTs are wireless, embedded in objects, and record the environment using sensors (Yigitcanlar & Lee, 2014). They provide the critical infrastructure for more intelligent and interconnected solutions in areas such as healthcare, real estate, utilities, transportation, public safety, and administration (Washburn et al., 2009). In the energy grid domain, for example, smart ICTs help collect and share consumption data to optimize energy management (Farmanbar et al., 2019). In the transportation domain, smart ICTs enable safe, socially inclusive, and sustainable multi-modal transportation networks, which allow citizens to travel with ease (Herrenkind et al., 2019; Lembcke et al., 2021; Nastjuk et al., 2020; Nikitas et al., 2017; Rocha et al., 2020; Trang et al., 2015). In the building domain, smart ICTs can help to establish so-called “zero energy buildings” by significantly reducing the energy demand during the lifecycle of residential and commercial buildings (Kylili & Fokaides, 2015). In the healthcare domain, smart wearable devices can, for example, cater for remote diagnosis, medical prescriptions, and treatment of patients (Ghazal et al., 2021) or allow for the effective monitoring of public health (Trang et al., 2020). In the education domain, smart ICTs promote a more engaged learning experience in which learners can “learn at anytime, anywhere, in any way and at any pace” (Liu et al., 2017, p. 33). The importance of ICTs as a key driver for smart cities varies in the aforementioned application fields. In domains such as energy or transportation management, smart ICTs are essential enablers and require big data processing capabilities, while in domains such as education or public administration, smart ICTs have a more limited role where processing large volumes of data in real time is usually not required (Neirotti et al., 2014). Apart of the relevance of ICTs to envision smart cities, a significant body of literature has argued extensively about This article is part of the Topical Collection on Smart Cities Smart governance models for future cities.
Securing Smart Cities Using Blockchain Technology
Beenu Mago Mohammad Kamrul Hasan + 6 lainnya
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Recent years have witnessed substantial advancement in the subject of smart cities. The purpose of smart city development is to enhance the quality of life for citizens. This was accomplished via the use of IoT and cloud computing technologies. Another promising technology is blockchain, which has the ability to deliver a myriad of value services to its end users. For virtual assets with value, such as Bitcoin, it is a programmable digital register that is immutable. To properly exploit blockchain technology's services inside smart cities, it is necessary to identify the technology's features, as well as its main needs and research obstacles. As such, this essay will try to define the properties of blockchain technology. Additionally, the critical needs for integrating blockchain technology into smart cities are outlined. A possible use case for blockchain technology is used to show how a smart city could be protected. There is also an overview of how a real-world three-blockchain-based smart city case study works. Finally, a number of critical research issues are highlighted and explored.