Drone surveillance system—RF/WiFi-based drone detection, localization, and tracking: a survey

Bisio, Igor; Garibotto, Chiara; Haleem, Halar; Lavagetto, Fabio; Sciarrone, Andrea

doi:10.1049/sbra545e_ch3

Cited by 3 publications

(2 citation statements)

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“…Classical networking (star, tree, P2P, mesh, bus topologies) [5], [7], [28], [44], opportunistic networking [3], [5], [45], and cognitive radios [46] are different classes of networking. Drones can also be used for networking purposes, such as measuring, intruder detection, and localization [43], [66], [67].…”

Section: Networkingmentioning

confidence: 99%

Wireless Sensor Networks-based Smart Agriculture: Sensing Technologies, Application and Future Directions

Rahu

Karim

Shams

et al. 2023

SJET

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With the advent of the latest sensing technologies, agricultural tasks can be performed so quickly andadequately and termed Smart agriculture. In this paper, a system based on sensor networks has been designed tomonitor agricultural parameters wirelessly. The proposed system has been deployed in a Wheat field. The aim of this workis to increase the quality and productivity of the Wheat crops and minimize the extensive field visits of the farmers. Thissystem enables precision agriculture by periodically measuring the three most key parameters (temperature, light, andwater level) for achieving a remarkable increase in quality, productivity and growth of the Wheat crops. Thus, this systemhelps the agriculturists, landowners and research experts to monitor these parameters at the base station without goingto the field site. A GUI tool is also designed to display the measured data and stored it in the database accordingly. Whiledesigning this system; IRIS mote, MDA100 data acquisition board, and MIB520 USB interface board are employed. Weuse TinyOS operating system for the development of codes for wireless nodes and the GUI tool is designed in MicrosoftVisual Studio. ZigBee IEEE 802.15.4 protocol and direct topology are used for the communication of nodes with the basestation.

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Section: Networkingmentioning

confidence: 99%

Wireless Sensor Networks-based Smart Agriculture: Sensing Technologies, Application and Future Directions

Rahu

Karim

Shams

et al. 2023

SJET

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“…Notwithstanding the benefits of using UAVs, their peculiar usage has raised public privacy issues too [10]. Moreover, utilization of such devices impose difficulties and challenges that must be addressed.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review of Drone Based Road Traffic Monitoring System

et al. 2022

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Drone deployment has become crucial in a variety of applications, including solutions to traffic issues in metropolitan areas and highways. On the other hand, data collected via drones suffers from several problems, including a wide range of object scales, angle variations, truncation, and occlusion. To process and manipulate visual data from the drones, a variety of image processing algorithms have been employed, each with a distinct aim. Additionally, recent breakthroughs in the field of Artificial Intelligence, particularly deep learning, have attracted broad interest and are being applied to many domains in the framework of smart cities, including road traffic monitoring. The purpose of this study is to conduct a systematic review of drone-based traffic monitoring systems from a deep learning perspective. This work focuses on vehicle detection, tracking, and counting, since they are fundamental building blocks towards founding solutions for traffic congestion, flow rate and vehicle speed estimation. Additionally, drone-based datasets are examined, which face issues and problems caused by the diversity of features inherent of drone devices. The review analysis presented in this work summarizes the literature solutions provided and deployed so far and discusses future research trends in establishing a comprehensive traffic monitoring system in support of the development of smart cities INDEX TERMS deep learning, drone, smart city, traffic monitoring, uav.

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Traffic Analysis Through Deep-Learning-Based Image Segmentation From UAV Streaming

Bisio

Garibotto

Haleem

et al. 2023

IEEE Internet Things J.

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Drone surveillance system—RF/WiFi-based drone detection, localization, and tracking: a survey

Cited by 3 publications

References 0 publications

Wireless Sensor Networks-based Smart Agriculture: Sensing Technologies, Application and Future Directions

Wireless Sensor Networks-based Smart Agriculture: Sensing Technologies, Application and Future Directions

A Systematic Review of Drone Based Road Traffic Monitoring System

Traffic Analysis Through Deep-Learning-Based Image Segmentation From UAV Streaming

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