IEEE Consumer Electronics Magazine - November/December 2021 - 18

Unmanned Aerial Vehicles
Table 7. Comparisons of active military UAVs.
Attribute
Max Speed (knots)
Max Altitude (ft)
Engine
Max Internal Payload (lb.)
Max External Payload
(lb.)
Endurance (H)
Cost
60,000
Rolls Royce F137-RR100
3,000
NA
32+
$130
M
FUTURE OF UAVs AND ASSOCIATED
CHALLENGES
In future, UAVs will be integrated with emerging
technologies such as augmented reality (AR),
artificial intelligence (AI), and cellular networking
to enable a multitude of innovative applications.
Furthermore, advancements and miniaturization
of electronics will help realize exciting new applications
of UAVs. This section discusses some of
the futuristic embodiments and applications of
UAVs and the challenges associated with them.
UAV Swarms
A swarm of UAVs is a group of UAVs that
coordinate with each other to carry out a task.
The swarm could be semiautonomous or fully
autonomous. Semiautonomous swarms are
usually controlled by a GCS which communicates
with each UAV simultaneously. Fully
autonomous swarms use flying ad-hoc networks
(FANET) to communicate with each
other and one leader UAV communicates with
the GCS. Utilizing swarms in applications such
as surveying and mapping, agricultural, and
logistics and delivery has the benefits of saving
time and man-hours by distributing the tasks
between the UAVs. UAV swarms have gained a
lot of attention from the Air Force and the
DOD in recent years. UAV swarms can even be
used to save lives in the case of search and
rescue applications. Deploying a swarm of
UAVs in a disaster zone leads to a faster discovery
of survivors. The main challenges in
UAV swarms are collision avoidance between
18
RQ-4 Global Hawk
340
MQ-1 C Gray
Eagle
167
25,000
Lycoming DEL-120
540
1,500
50+
$21.5 M
MQ-1
Predator
120
25,000
Rotax 914
450
300
24
$40 M
ScanEagle
80
19,500
2-stroke 3 W
piston
7.5
NA
24+
$3.2 M
the UAVs in the swarms and the energy efficiency
of swarm operation.
Augmented Reality
AR is a technology that allows users to interact
with computer-generated objects in a real-world
environment.10 AR has been used in a variety of
applications, such as design and manufacturing,
tourism, navigation, education, and gaming. By
integrating AR technology in UAVs, a multitude of
new applications are possible. AR can be used to
display real-time overlaying information on the
real-world environment like maps, floor plans,
and points of interest. These ARmaps can be beneficial
in the military, and search and rescue operations.
Another example of integrated UAV-AR is
planning and designing, where architects and
engineers can fly over a location and use 3-D models
to visualize the project. Integrated UAV-AR can
also be used in inspection where the AR would
overlay and synchronize the building information
model (BIM) on the video feed from the UAV. This
could be useful in inspecting underground pipes,
bridges, power lines, and dams.
Artificial Intelligence
UAVs using AI can be utilized in various object
detection and recognition applications. Detecting
traffic congestion is an example of an application
utilizing AI-assisted UAVs.11 In this example,
a UAV takes pictures of traffic in a preplanned
route, which are subsequently processed by a
convolutional neural network (CNN) to decide if
a road is congested or not. The results from the
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