A Hybrid Battery Charging Approach for Drone-Aided Border Surveillance Scheduling

Abstract

This paper proposes a new method to extend the flight capability of drones in real time. The new method combines two wireless charging methods (stationary wireless charging systems and dynamic wireless charging systems) into a hybrid mode. The drones must frequently return to a ground control center to replace or recharge its battery due to the limited performance of batteries mounted in the drones. To reduce the need of returning to the center, stationary wireless charging systems and dynamic wireless charging systems have been proposed. However, a few drawbacks of the two systems include the needs of landing/stopping on the stationary charging systems and the uncertainty of charging efficiency over the dynamic charging systems. Hence, to resolve the current limitations, we propose the hybrid approach for extending drone flight duration in real time. A mathematical formulation model is proposed to decide an optimal installation location and operating time of the hybrid mode. A case study is conducted to illustrate feasibility and effectiveness of the proposed method. Results from the case study show that we can lengthen the flight duration per charge from the initial launching point (30 min → 32–59 min), and if the value of charging efficiency of the dynamic charging systems is maintained above a certain level, the time spent on the stationary charging systems is significantly reduced (58 min → 22 min).

Background Invariant Faster Motion Modeling for Drone Action Recognition

“…Recently, a few datasets have been published in aerial and drone surveillance and can be used for action recognition, such as in [36,37]. In the past few years, the use of a drone has been increasing, and it covers almost every field of surveillance, such as road safety and traffic analysis [38], crop monitoring [39], and border area surveillance [40]. Recent work has been published in this field, which uses drone surveillance using a deep learning action recognition model for search and rescue [41].…”

A new comparison of hyperspectral anomaly detection algorithms for real-time applications

“…It is a push-broom camera which provides 1024 spatial pixels and 224 spectral bands [22]. However, due to the low signal-to-noise ratio of the first and last spectral bands, they were removed (1)(2)(3)(4)(5)(6)(7)(8)(9)(10), so that 180 bands have been retained. The original image scene covers an area of 1024 × 4967 pixels, but a much shorter scene has been cropped containing the anomalies of the scene.…”

“…There are nonetheless works in the scientific literature proposing different solutions for such problem. On one hand, a wireless power charge approach in order to reduce the stopping time [3]. On the other hand the use of alternative propulsion systems (or hybrid combinations of some of them), which alleviate the restrictions imposed by electric batteries in terms of autonomy, are attracting great attention from the scientific community [4]- [6].…”

On the Sizing of the DC-Link Capacitor to Increase the Power Transfer in a Series-Series Inductive Resonant Wireless Charging Station

“…Generally, self-driving applications like surveillance drones use a WPT station to automatize the charging process [4,5]; no operator or sophisticated connectors and platforms are required. Typically, a drone WPT charging system raises many issues, including the drone alignment with the landing platform [6][7][8], the charging time reduction to minimize no-operation intervals [9], and the reduced weight to improve the flight endurance [10]. A WPT system is usually composed of two inductive-coupled circuits.…”