Internet of Things Applications for Smart Cities

Minoli, Daniel; Occhiogrosso, Benedict

doi:10.1002/9781119456735.ch12

Cited by 12 publications

(2 citation statements)

References 60 publications

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“…Smart City IoT applications cover indoor and outdoor applications; they also span stationary and mobile end-nodes and sensors. There is an extensive body of literature on this topic; some references of interest include but are certainly not limited to [2][3][4][5][6][7][8][9][10][11][12]. Up to the present, the IoT has been mostly utilized for supporting a large population of relatively low-bandwidth sensing devices, and where the sensing devices are typically deployed in stationary locations (e.g., electric meters, building management systems, meteorological weather stations).…”

Section: Introductionmentioning

confidence: 99%

Practical Aspects for the Integration of 5G Networks and IoT Applications in Smart Cities Environments

Minoli

Occhiogrosso

2019

Wireless Communications and Mobile Computing

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105

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Both 5G cellular and IoT technologies are expected to see widespread deployment in the next few years. At the practical level, 5G will see initial deployments in urban areas. This is perhaps fortuitous from an IoT perspective, since many “mainstream” applications of IoT will support Smart Cities, Smart Campuses and Smart Buildings. Bandwidth demand for a number of Smart City applications is the main driver for enhanced mobile broadband (eMBB)-based 5G services in general, and new-generation 5G IoT applications, in particular. In turn, the use of the millimeter wave spectrum is required to enable 5G cellular technologies to support high data rates. Millimeter wave solutions, however, impose a requirement for small cells. Generally, an implementer tries to use one or a small handful of IoT technologies; preferably, and for managerial simplicity, the implementer would want to use a cellular/5G IoT technology for all nodes, whether indoors or outdoors, instead of a heterogenous mix of various IoT technologies that have evolved over the years. This overview paper discusses a number of practical issues related to 5G-based IoT applications, particularly in Smart City environments, including the need for small cells, the transmission issues at millimeter wave frequencies, building penetration issues, the need for Distributed Antenna Systems, and the near term introduction of pre-5G IoT technologies such as NB-IoT and LTE-M, these being possible proxies for the commercial deployment and acceptance of 5G IoT.

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Section: Introductionmentioning

confidence: 99%

Practical Aspects for the Integration of 5G Networks and IoT Applications in Smart Cities Environments

Minoli

Occhiogrosso

2019

Wireless Communications and Mobile Computing

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105

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“…Smart cities deploy many different sensors to capture information from different parts of the city, such as on traffic, air pollution, waste, rain and snow, electric grids, etc. [5][6][7]. Different parts of the smart cities make up the smart environment, such as smart water, smart metering, security and emergency, retail, logistic, industrial control, smart agriculture, smart animal farming, domotic and home automation, and eHealth [8,9].…”

Section: Introductionmentioning

confidence: 99%

Minimum-Cost Drone–Nest Matching through the Kuhn–Munkres Algorithm in Smart Cities: Energy Management and Efficiency Enhancement

Mirzaeinia

Hassanalian

2019

Aerospace

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The development of new concepts for smart cities and the application of drones in this area requires different architecture for the drones’ stations (nests) and their placement. Drones’ stations are designed to protect drones from hazards and utilize charging mechanisms such as solar cells to recharge them. Increasing the number of drones in smart cities makes it harder to find the optimum station for each drone to go to after performing its mission. In classic ordered technique, each drone returns to its preassigned station, which is shown to be not very efficient. Greedy and Kuhn‒Munkres (Hungarian) algorithms are used to match the drone to the best nesting station. Three different scenarios are investigated in this study; (1) drones with the same level of energy, (2) drones with different levels of energy, and (3) drones and stations with different levels of energy. The results show that an energy consumption reduction of 25‒80% can be achieved by applying the Kuhn‒Munkres and greedy algorithms in drone‒nest matching compared to preassigned stations. A graphical user interface is also designed to demonstrate drone‒station matching through the Kuhn‒Munkres and greedy algorithms.

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Background and Functional Requirements for High‐Density Communications

2021

High‐Density and De‐Densified Smart Campus Communications

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Internet of Things Applications for Smart Cities

Cited by 12 publications

References 60 publications

Practical Aspects for the Integration of 5G Networks and IoT Applications in Smart Cities Environments

Practical Aspects for the Integration of 5G Networks and IoT Applications in Smart Cities Environments

Minimum-Cost Drone–Nest Matching through the Kuhn–Munkres Algorithm in Smart Cities: Energy Management and Efficiency Enhancement

Background and Functional Requirements for High‐Density Communications

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