Internet of Drones

Gharibi, Mirmojtaba; Boutaba, Raouf; Waslander, Steven L.

doi:10.1109/access.2016.2537208

Cited by 413 publications

(235 citation statements)

References 18 publications

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“…Multi-UAV Ad Hoc networks can be applied to achieve above two goals. The multi-UAV network cannot only independently cover the remote areas but also execute many specific tasks (including relay communications, remote sensing, data acquisition, etc [175]). From a global perspective, multi-UAV Ad Hoc networks are required to enable the specified coverage when UAVs fly to remote areas.…”

Section: B Uav-enabled Ioementioning

confidence: 99%

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Liu

Dai

Wang

et al. 2020

Computer Communications

173

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The recent advances in information and communication technology (ICT) have further extended Internet of Things (IoT) from the sole "things" aspect to the omnipotent role of "intelligent connection of things". Meanwhile, the concept of internet of everything (IoE) is presented as such an omnipotent extension of IoT. However, the IoE realization meets critical challenges including the restricted network coverage and the limited resource of existing network technologies. Recently, Unmanned Aerial Vehicles (UAVs) have attracted significant attentions attributed to their high mobility, low cost, and flexible deployment. Thus, UAVs may potentially overcome the challenges of IoE. This article presents a comprehensive survey on opportunities and challenges of UAV-enabled IoE. We first present three critical expectations of IoE: 1) scalability requiring a scalable network architecture with ubiquitous coverage, 2) intelligence requiring a global computing plane enabling intelligent things, 3) diversity requiring provisions of diverse applications. Thereafter, we review the enabling technologies to achieve these expectations and discuss four intrinsic constraints of IoE (i.e., coverage constraint, battery constraint, computing constraint, and security issues). We then present an overview of UAVs. We next discuss the opportunities brought by UAV to IoE. Additionally, we introduce a UAV-enabled IoE (Ue-IoE) solution by exploiting UAVs's mobility, in which we show that Ue-IoE can greatly enhance the scalability, intelligence and diversity of IoE. Finally, we outline the future directions in Ue-IoE.

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Section: B Uav-enabled Ioementioning

confidence: 99%

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Liu

Dai

Wang

et al. 2020

Computer Communications

173

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“…Researchers have showed that personal drones are vulnerable to cache-poisoning and buffer overflow that have the potential of causing Denial of Service (DoS) attacks. The penetration tests that were conducted on personal drones like the Wireless Parrot Bebop UAVs revealed the aforementioned vulnerabilities [10], [12], [13]. Some reported cases like the interception of live feeds from US drones by Iraqi militants who managed to access and watch captured videos on their laptops using a $26 worth software shows that even military-grade drones are vulnerable [5], [23].…”

Section: Background Information and Related Workmentioning

confidence: 99%

No Peeking through My Windows: Conserving Privacy in Personal Drones

Fitwi

Chen

Zhu

2019

2019 IEEE International Smart Cities Conference (ISC2)

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The drone technology has been increasingly used by many tech-savvy consumers, a number of defense companies, hobbyists and enthusiasts during the last ten years. Drones often come in various sizes and are designed for a multitude of purposes. Nowadays many people have small-sized personal drones for entertainment, filming, or transporting items from one place to another. However, personal drones lack a privacypreserving mechanism. While in mission, drones often trespass into the personal territories of other people and capture photos or videos through windows without their knowledge and consent. They may also capture video or pictures of people walking, sitting, or doing private things within the drones' reach in clear form without their go permission. This could potentially invade people's personal privacy. This paper, therefore, proposes a lightweight privacy-preserving-by-design method that prevents drones from peeking through windows of houses and capturing people doing private things at home. It is a fast window object detection and scrambling technology built based on image enhancing, morphological transformation, segmentation and contouring processes (MASP). Besides, a chaotic scrambling technique is incorporated into it for privacy purpose. Hence, this mechanism detects window objects in every image or frame of a real-time video and masks them chaotically to protect the privacy of people. The experimental results validated that the proposed MASP method is lightweight and suitable to be employed in drones, considered as edge devices.

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“…• Once the drone is in a stationary position, i.e., floating at the desired location, the power consumption will rapidly sink [16], [17] and the harvested power can mostly be used for data communication to obtain a required bit-error rate while the remaining power is stored by P charge 2 .…”

Section: System Modelmentioning

confidence: 99%

Wireless powering of drone-based MANETs for disaster zones

Calvo

Alirezaei

Mathar

2017

2017 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)

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Abstract-Since in emergency zones the communication network has to be rapidly established, the usage of autonomous drones, forming an ad-hoc network, is an interesting alternative. By using the mentioned drones, the main technical challenge to face is the difficulty of powering the drones for a long service time, having in mind that they are not wired to any infrastructure and the batteries are not designed for lasting the required period of time. To prolong the operating lifetime of such networks, we hence propose and investigate a new simultaneous wireless information and power transmission (SWIPT) scheme. We first study the optimal distribution of the harvested energy, that can be shared between data communication, drone movement, and battery charging. Then we optimize the positioning of the drones such that a line-of-sight situation is achieved as well as a minimum required signal-to-noise ratio is ensured at the receivers. Afterwards, the lobes of both transmitter and receiver antennas are optimally aligned to maximize the harvested energy. Finally, the proposed drone-based network is simulated by using realistic parameters to show its adequate performance in practice.

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Internet of Drones

Cited by 413 publications

References 18 publications

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

No Peeking through My Windows: Conserving Privacy in Personal Drones

Wireless powering of drone-based MANETs for disaster zones

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