Abstract
Advances in Unmanned Aerial Vehicles (UAVs), also known as drones, offer unprecedented opportunities to boost a wide array of large-scale Internet of Things (IoT) applications. Nevertheless, UAV platforms still face important limitations mainly related to autonomy and weight that impact their remote sensing capabilities when capturing and processing the data required for developing autonomous and robust real-time obstacle detection and avoidance systems. In this regard, Deep Learning (DL) techniques have arisen as a promising alternative for improving real-time obstacle detection and collision avoidance for highly autonomous UAVs. This article reviews the most recent developments on DL Unmanned Aerial Systems (UASs) and provides a detailed explanation on the main DL techniques. Moreover, the latest DL-UAV communication architectures are studied and their most common hardware is analyzed. Furthermore, this article enumerates the most relevant open challenges for current DL-UAV solutions, thus allowing future researchers to define a roadmap for devising the new generation affordable autonomous DL-UAV IoT solutions.
Highlights
The Internet of Things (IoT) is expected to connect to the Internet more than 75 billion devices in 2025 [1]
The underlying Deep Learning (DL)-Unmanned Aerial Vehicles (UAVs) hardware and its communications architecture are essential for the success of the system, as they provide the support for implementing DL techniques and advanced features
Among the different available indoor location techniques, those based on Received Signal Strength Indicator (RSSI) or Received Signal Strength (RSS) have proved their accuracy when positioning in limited areas [101,102], but their heavily depend on characteristics of the scenario and on the used UAV hardware [103]
Summary
The Internet of Things (IoT) is expected to connect to the Internet more than 75 billion devices in 2025 [1]. Unmanned Aerial Vehicles (UAVs) have an enormous potential for enabling novel IoT applications thanks to their low maintenance cost, high mobility and high maneuverability [9]. Due to such characteristics, UAVs have been really useful in a number of fields and applications, like remote sensing, real-time monitoring, disaster management, border and crowd surveillance, military applications, delivery of goods, or precision agriculture [10,11].
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