Application of Internet of Things and Big Data towards a Smart City

Yadav, Preeti; Vishwakarma, Sandeep Kumar

doi:10.1109/iot-siu.2018.8519920

Cited by 67 publications

(33 citation statements)

References 10 publications

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“…The generic architecture of IoT consists of multiple layers, i.e., business, application, middleware, and perception layers [63], which are illustrated in Figure 1. The business layer contains system management solutions that may be varied according to the requirements [48,62]. The middleware layer is the most critical layer that consists of information processing [30], ubiquitous computing [52], services management [20], databases [59,64], and decision units [24].…”

Section: Introductionmentioning

confidence: 99%

EdgeTrust - A Lightweight Data-centric Trust Management Approach for Green Internet of Edge Things

Awan

Din

Almogren

et al. 2021

Preprint

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Internet of Things (IoT) is bringing revolution into today’s world where devices in our surroundings become smart and perform daily-life activities and operations with more precision. The architecture of IoT is heterogeneous as it provides autonomy to nodes that they can communicate among other nodes and can also exchange information at any period. Due to the heterogeneous environment, IoT faces numerous security and privacy challenges, and one of the most significant challenges is the identification of malicious and compromised nodes. In this article, we have proposed a Machine Learning-based trust management approach for edge nodes. The proposed approach is a lightweight process to evaluate trust because edge nodes cannot perform complex computations. To evaluate trust, the proposed mechanism utilizes the knowledge and experience component of trust where knowledge is further based on several parameters. To eliminate the triumphant execution of good and bad-mouthing attacks, the proposed approach utilizes edge clouds, i.e., local data centers, to collect recommendations to evaluate indirect and aggregated trust. The trustworthiness of nodes is ranked between a certain limit where only those that satisfy the threshold value can participate in the network. To validate the performance of a proposed approach we have performed an extensive simulation in comparison with the existing approaches and the result shows the effectiveness of the proposed approach against several potential attacks.

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Section: Introductionmentioning

confidence: 99%

EdgeTrust - A Lightweight Data-centric Trust Management Approach for Green Internet of Edge Things

Awan

Din

Almogren

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…Internet of Things (IoT) has found many applications in various areas since its breakthrough to praxis about 10 years ago. For instance, we can find it as an assistant for many human activities in the frame of smart homes [1,2], healthcare, smart cities [3], smart agriculture [4], transportation, or manufacturing. IoT is also an important element in such concepts as cyber-physical systems [5] and Industry 4.0 [6].…”

Section: Introductionmentioning

confidence: 99%

Means of IoT and Fuzzy Cognitive Maps in Reactive Navigation of Ubiquitous Robots

et al. 2021

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Development of accessible and cheap sensors as well as the possibility to transfer and process huge amounts of data offer new possibilities for many areas utilizing till now conventional approaches. Navigation of robots and autonomous vehicles is no exception in this aspect and Internet of Things (IoT), together with the means of computational intelligence, represents a new way for construction and use of robots. In this paper, the possibility to move sensors from robots to their surroundings with the help of IoT is presented and the modification of the IoT concept in the form of intelligent space as well as the concept of ubiquitous robot are shown in the paper. On an example of route tracking, we will clarify the potential of distributed networked sensors and processing their data with the use of fuzzy cognitive maps for robotic navigation. Besides, two modifications of adaptation approaches, namely particle swarm optimization and migration algorithm, are presented here. A series of simulations was performed, which are discussed and future research directions are proposed.

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“…Heterogeneous cellular networks comprising different nodes, such as macro and microcells, have been used for analysis [9]. Interconnected objects in IoT are known as smart objects [10]. A large number of smart objects with numerous connections are used in the digital world.…”

Section: Introductionmentioning

confidence: 99%

Hotspots Analysis Using Cyber-Physical-Social System for a Smart City

Amin

Choi

2020

IEEE Access

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Internet of things plays a vital role in providing various services to users. Significant volumes of data are generated from the communication between a large numbers of heterogeneous devices over the Internet. Big data technology is generally used to handle the large volume of data. Complex networks are graphs (networks) having non-trivial topological features, such as random graphs and lattices. Big data of complex networks concerns big data methods that can be used to analyze massive structural data sets, including considerably large networks and sets of graphs. This study is based on the critical phenomenon arising in complex networks that enable us to analytically predict the hotspots in smart cities. Hotspots are places with significantly high communication traffic relative to others. In this study, we propose a cyber-physical-social system for the analysis of high communication traffic hotspots using telecom data. The proposed model constructs a graph, and perform social network analysis on it. The process of hotspot extraction is performed, followed by social network analysis, which is conducted by quantifying the importance of each hotspot based on network metrics. These metrics aid in determining the importance of each hotspot in a telecom data network. Our objective is to prioritize different areas and detect hotspots quickly. Our results indicate that the proposed model has an efficiency comparable with that of state of the art methods. This research study will be helpful for urban planning and development, as well as in upgrading telecommunication infrastructure.

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Application of Internet of Things and Big Data towards a Smart City

Cited by 67 publications

References 10 publications

EdgeTrust - A Lightweight Data-centric Trust Management Approach for Green Internet of Edge Things

EdgeTrust - A Lightweight Data-centric Trust Management Approach for Green Internet of Edge Things

Means of IoT and Fuzzy Cognitive Maps in Reactive Navigation of Ubiquitous Robots

Hotspots Analysis Using Cyber-Physical-Social System for a Smart City

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