Intelligent UAV in smart cities using IoT

Giyenko, Andrey; Cho, Young Im

doi:10.1109/iccas.2016.7832322

Cited by 71 publications

(50 citation statements)

References 3 publications

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“…The United States Office of the Secretary of Defense (OSD) identifies over twenty UAV mission types, ranging from intelligence, surveillance (Giyenko and Cho, 2016a), reconnaissance missions (Broad, 1981), force protection, firefighting, electronic warfare to communication nodes and others (Malone et al, 2013).…”

Section: Relevant Application Areasmentioning

confidence: 99%

Distributed Uav-Swarm-Based Real-Time Geomatic Data Collection Under Dynamically Changing Resolution Requirements

Almeida¹,

Hildmann

Solmaz³

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Unmanned Aerial Vehicles (UAVs) have been used for reconnaissance and surveillance missions as far back as the Vietnam War, but with the recent rapid increase in autonomy, precision and performance capabilities -and due to the massive reduction in cost and size -UAVs have become pervasive products, available and affordable for the general public. The use cases for UAVs are in the areas of disaster recovery, environmental mapping & protection and increasingly also as extended eyes and ears of civil security forces such as fire-fighters and emergency response units. In this paper we present a swarm algorithm that enables a fleet of autonomous UAVs to collectively perform sensing tasks related to environmental and rescue operations and to dynamically adapt to e.g. changing resolution requirements. We discuss the hardware used to build our own drones and the settings under which we validate the proposed approach.

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Section: Relevant Application Areasmentioning

confidence: 99%

Distributed Uav-Swarm-Based Real-Time Geomatic Data Collection Under Dynamically Changing Resolution Requirements

Almeida¹,

Hildmann

Solmaz³

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…In this case, EVs need to stay connected with AGs to keep up with the RES and road conditions. The randomness of RES makes this integration tasks time-sensitive, requiring extreme low-latency and mobile communication technologies such as cellular and aerial networks [220], [224]. • Regulation Service: Regulation service such as frequency regulation is closely related to the SG stability.…”

Section: Information Management For V2g Servicesmentioning

confidence: 99%

Energy and Information Management of Electric Vehicular Network: A Survey

Chen

Wang

Zhang

et al. 2020

IEEE Commun. Surv. Tutorials

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The connected vehicle paradigm empowers vehicles with the capability to communicate with neighboring vehicles and infrastructure, shifting the role of vehicles from a transportation tool to an intelligent service platform. Meanwhile, the transportation electrification pushes forward the electric vehicle (EV) commercialization to reduce the greenhouse gas emission by petroleum combustion. The unstoppable trends of connected vehicle and EVs transform the traditional vehicular system to an electric vehicular network (EVN), a clean, mobile, and safe system. However, due to the mobility and heterogeneity of the EVN, improper management of the network could result in charging overload and data congestion. Thus, energy and information management of the EVN should be carefully studied. In this paper, we provide a comprehensive survey on the deployment and management of EVN considering all three aspects of energy flow, data communication, and computation. We first introduce the management framework of EVN. Then, research works on the EV aggregator (AG) deployment are reviewed to provide energy and information infrastructure for the EVN. Based on the deployed AGs, we present the research work review on EV scheduling that includes both charging and vehicle-to-grid (V2G) scheduling. Moreover, related works on information communication and computing are surveyed under each scenario. Finally, we discuss open research issues in the EVN.

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“…This type of equipment means that UAVs have a very important role in the IoT and can act as a mobile air base station, providing reliable downlink and uplink communications to terrestrial users, thereby increasing the capacity of wireless networks [2]. In addition, UAVs can be used as airborne wireless relays, as well as signal boosters and mobile nodes for the IoT and sensor networks [3]. If they are used as reliable air base stations, UAVs need to be positioned precisely.…”

Section: Introductionmentioning

confidence: 99%

Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things

Zhao

Yang

et al. 2019

Wireless Communications and Mobile Computing

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Unmanned aerial vehicles (UAVs) have broad application potential for the Internet of Things (IoT) due to their small size, low cost, and flexible control. At present, the main positioning method for UAVs is the use of GPS. However, GPS positioning may be affected by stronger electromagnetic signals from spoofing attacks. In this study, a radar-assisted positioning method based on 5G millimeter waves is proposed. In 5G end-to-end network slices, the rotors of UAVs can be detected and identified by deploying 5G millimeter wave radar. High-resolution range profile (HRRP) is used to obtain the UAV location in the detection zone. Micro-Doppler characteristics are used to identify the UAVs and the cepstrum method is used to extract the number and speed information of the UAV rotor. The sinusoidal frequency modulation (SFM) parameter optimization method is used to separate multiple UAVs. The proposed method provides information on the number of UAVs, the position of the UAV, the number of rotors, and the rotation speed of each rotor. The simulation results show that the proposed radar detection method is well suited for UAV detection and identification and provides a valid GPS-independent method for UAV tracking.

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Intelligent UAV in smart cities using IoT

Cited by 71 publications

References 3 publications

Distributed Uav-Swarm-Based Real-Time Geomatic Data Collection Under Dynamically Changing Resolution Requirements

Distributed Uav-Swarm-Based Real-Time Geomatic Data Collection Under Dynamically Changing Resolution Requirements

Energy and Information Management of Electric Vehicular Network: A Survey

Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things

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