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C2C Digital Magazine (Fall 2022 - Winter 2023)

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Cover, page 16 of 22


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Book review: Smartening UAVs for effective services

By Shalin Hai-Jew, Kansas State University


Revolutionary Applications of Intelligent Drones
Mohit Angurala and Vikas Khullar
Nova Science Publishers
155 pp.

The general public may have seen news stories of unmanned aerial vehicles (UAVs) delivering drugs and even human organs (for transplantation) across a hospital campus, monitoring the U.S.-Mexico border, delivering food, and providing security overflight.  They may have seen creative light displays as new year celebrations, with smart drones flashing their brights.  Others have been used for building-based art shows, alongside high-powered light projectors.  Perhaps they have handled a commercial drone to shoot footage for their social media channels or films.  They may have seen fleeting visuals of military-style UAVs in news stories of a hot war.  Based on consumed information and experiences, people likely have various evocations in terms of “drones” and “UAVs.”

Mohit Angurala and Vikas Khullar’s Revolutionary Applications of Intelligent Drones (2022) offers a look at various practical uses of these aircraft.  Their edited collection may help situate understandings of such craft in a more systematized way.  Indeed, drones have been used for “drug delivery, agricultural applications, vertical structure inspection, construction site survey” and other applications (n.p.).  They have been applied in medicine, agriculture, disaster management, entertainment, and military applications.  During the SARS-CoV-2 / COVID-19 pandemic, they were used for package deliveries.  They may affect how people live, interact, share, war-fight, and otherwise engage.  

Figure 1.  UAV (by SymphysisMarketing on Pixabay)


Over time, various cutting-edge technologies have been engineered into drones.  Machine learning analytics have been applied.  But first, the basics.  

Some Basics about Drone Technologies

Jyoti Kandpal, Pankaj Kumar Mishra, Bhavna Chilwal, Abhay Kumar Singh, and Geetanjali Balutia’s  “Introduction to Drone Technologies” (Ch. 1) opens with a listing of various ways industries may improve with the use of UAVs:  in operations, cost controls, customer experiences, and security, among others (p. 1).  While the objectives all look reasoned, without particular use cases and examples, it may be harder to better understand the applied capabilities.  

UAVs do not have a human pilot on board.  They may be guided by software-controlled flight plans.  Low-altitude vehicles may be flown remotely based on on-board global positioning systems (GPS) and spatial sensing.  Some types are referred to as remotely piloted aircraft (RPA).  UAVs may be part of an unmanned aircraft system.  UAVs are usually part of an unmanned aircraft system (UAS) “that usually involves a ground-based director and a communicating infrastructure with a UAV” (Kandpal, Mishra, Chilwal, Singh, & Balutia, 2022, p. 2)  

These researchers explain the historical background of such flying machines that led to the colloquial label of “drone”:  

In 1935, a complete restructuring of the de Havilland DH82B ‘Queen Bee’ biplane became the earliest widely utilized drone.  It mainly was flown unmanned to permit artillery raiders in coaching to practice shooting, ‘drone’ came from a play on the ‘Queen Bee’ pseudonym.   (Kandpal, Mishra, Chilwalk Singh, & Balutia, 2022, p. 2)  

Even from early days, there has been interest in military usage, for both offense and defense, information collection and information delivery, and perhaps the deploying of particular mixed payloads.  There has always been a secret track and a non-secret track for UAV development.  As with any "dual use" technology, advances in the field may be harnessed for various ends. 

The technologies for a drone’s navigation is usually in the nose cone.  There are sensors to capture external and internal data.  Present-day UAVs derive their energy from batteries, fuels, or both.  With other fuels, like nuclear, such drones may feasibly hover for much longer periods.  The researchers write:  

The quantity and efficiency of sensors on board are referred to as degrees of freedom (DOF):  6 degrees of freedom denotes 3-axis gyroscopes and accelerometers (a standard inertial measurement unit – IMU), 9 degrees of freedom denotes an IMU plus a compass, 10 degrees of freedom denotes the addition of a barometer, and 11 degrees of freedom denotes the addition of a GPS receiver. (Kandpal, Mishra, Chilwalk Singh, & Balutia, 2022, p. 3)  

Drones may be categorized based on their structure, such as whether they have one or multiple rotors.  They may be fixed-wing drones vs. “fixed-wing hybrid” ones.  There are micro drones, small drones, and larger-sized ones.  “Tactical” drones are used for surveillance and may be fitted with infrared cameras.  Tactical drones “have six subtypes:  Medium altitude, long endurance, endurance, long range, medium range, short range and close range.  Long range is used for satellite platforms” (p. 7).  “GPS” drones are used to autonomously collect data across long distances.  Some drones are designed for racing, for hobbyist enjoyment.  

This chapter goes on to summarize details of handheld transmitters, a briefcase-borne base station; various UAV aircraft frames; flight controllers; and batteries.  It summarizes some of the encountered challenges in various practical applications, such as “routing problems,” and some proposed engineering and software solutions (based on a review of the literature from the past recent years).  

Drones date back to World War 1, “when the US and France collaborated on developing unmanned aircraft” (Kandpal, Mishra, Chilwalk Singh, & Balutia, 2022, pp. 17 - 18). 

Figure 2.  Target


The top industries using commercial UAVs are the following, in descending order:  photography (42.9%), real estate (20.7%), utilities (10.9%), construction (8.6%), agriculture (8%), education (1.9%), manufacturing (1.5%), emergency services, insurance, government, conservation, scientific, other, and research (Kandpal, Mishra, Chilwalk Singh, & Balutia, 2022, p. 18).  Aerial drone mapping is used for “asset management, forestry (management), environmental (sciences), remote sensing, agriculture, oil, and gas (industry)” (pp. 18 – 19).  Some are used for weather forecasting (p. 20).  Work is continuing apace to ensure that UAVs are used in “an ecosystem that ensures safety, reliability, and accountability” for daily life applications (p. 21).  

A Wide Range of Possibilities for UAVs in Various Sectors

Pankaj Kumar Mishra, Jyoti Kandpal, Abhay Kumar Singh, Geetanjali Balutia, Bhavna Chilwalk and Bhongiri Prasuna’s “Drones for Society and Industry” (Ch. 2) describe unmanned aerial vehicles as sensing platforms, mobile units that can carry a variety of sensing devices for surveillance, for inspection, and for data collection. They provide case studies of UAVs to locate new cars in a lot for human drivers to move, drones that assist self-driving vehicles by providing another set of eyes for route optimization (p. 27); human passenger transport (p. 28); “oil and gas exploration” (with data from “oil rigs, offshore platforms, and other places”);  inspection and monitoring of pipelines, and “oil and gas operations” (pp. 28 – 29), information about oil spills and gas leaks (p. 30); dynamic visuals to showcase real estate (pp. 32 – 34), traffic monitoring (p. 35), border surveillance (p. 36), mass-scale emergencies (pp. 37 – 38), delivery of goods (pp. 38 – 39), sanitation and hygiene during pandemics (p. 39), support for agriculture such as for monitoring, crop spraying, soil analysis, and “scaring birds” (pp. 39 – 41), support for construction (pp. 41 – 43) medical contents delivery (p. 43), and others.  For all the wide ranges of ideas, commercial drones still seem limited in terms of their diffusion in the world.  

Capturing the Data from Drones in an “Internet of Drones” (IoD) Network Infrastructure

Vrajesh Sharma and Nipun Chhabra’s “Cloud-Based UAV Architecture, Security Concerns and Challenges” (Ch. 3) opens with a comparison of UAV or drone networks with the Internet of Things (IoT).  UAVs use radio frequency transmissions to exchange information with ground stations.  To use the data created by and captured by UAVs, which may be various types, the data often needs to be transferred to external devices with “better storage and computational capacities” through fog computing (p. 45) in a so-called Internet of Drones (IoDs) network infrastructure.  Researchers are working on how to build out cloud-based architectures to collect UAV data securely and to process those in useful ways.  Sensor nodes are common in both the IoT and the IoD, for civilian, commercial, and military applications.  Many such nodes in cyber-physical systems do not have high-security protections and are susceptible to hijacking, jamming, data corruption, spoofing, denial of service attacks, and other challenges.  

Figure 3.  Aerial View


Features and Functions of Commercial Drones

Harsh Taneja and Ashish Sharma’s “Drones and their Utilities Using Emerging Technology” (Ch. 4) begins with the idea that new technologies may require work in the moral and legal realms, perhaps requiring some new moral grounding in the varied usages of the new technologies.  With that interesting setup, one might expect some fresh insights, but the chapter generally covers territory addressed by other works.  The other angle that is somewhat fresh is a reference to blockchain technologies for secure communications (pp. 63 – 65).  One other idea of note:  the researchers mention the uses of “a large number of coordinated drones…to complete complex missions” (p. 59), which is a helpful conceptualization of the possible complexities of UAV deployment.  

Integrating Machine Learning and UAV Capabilities

Geetanjali Sharma and Rajeev Kumar Bedi’s “Introduction to Machine Learning in UAVs” (Ch. 5) provides glimpses of the promise of contemporaneous technologies that may be integrated with UAV functions.  The researchers note:  “The aerial vehicle industry welcomes ideas that can solve various issues like power management and automatic control of drone with the help of machine learning” (p. 67).  In this chapter, they focus on computer vision and machine and deep learning technologies, in potential usage with drone technologies.  Machine learning refers to computer abilities to “learn without being explicitly programmed” (1959) (p. 68).  The co-authors then describe the processes of machine learning in three types:  supervised machine learning, unsupervised machine learning, and reinforcement learning. They offer insights on deep learning and some basic algorithms.  Then, they ask how the machine learning could help a UAV potentially adapt to a new context, respond to new information, handle new commands, and such.  While this work has at the beginning a promise of a thought piece, the thought is apparently something readers are to generate.  

Machine Learning-Based Decision Making for UAVs

Harmeet Singh’s “Decision Making Using Machine Learning in Drones” (Ch. 6) suggests that artificial intelligence technologies, like machine learning, may be used to direct drone routes based on particular rules of safety, energy conservation, speed, collision avoidance, and basic kinematics (p. 84).  This work offers a very brief summary of machine learning and sets up as a prompt for readers to possibly solve.  Perhaps the work is in the very nascent stages at present.  

UAVs in Agriculture

Prabhjot Kaur and Anand Muni Mishra’s “UAV Applications in Agriculture” (Ch. 7) highlights the criticality of agriculture as a sector for human employment and one for assuaging hunger and meeting nutritional needs of humanity.  This chapter suggests that UAVs can play a critical role in crop monitoring against disease, pestilence, and other potential harms, in “precision agriculture” applications.  Cameras and sensors mounted on a UAV may enable various types of remote sensing, such as soil attributes.  The researchers summarize some basic features of UAVs. Then they share ideas for various agricultural applications of UAVs in agronomy, such as plant stress detection, crop mapping, spraying, and irrigation.  While brief, this chapter is highly readable and engaging.  

A UAV-Based Agriculture Support Service

Figure 4.  Plumcot


Prabhdeep Singh, Kiran Deep Singh and Mohit Angurala’s “Drone Centric IoT-Fog-Cloud Based Smart Agriculture Support Service (Ch. 8) lauds the importance of smart agriculture to provide for the world’s growing needs for food. They propose “…a platform for environmental monitoring that provides data for the user to understand what is going on in the region that is being monitored” (p. 107). Theirs is a  three-tiered framework that uses “fog computing to perform real-time processing” (p. 107) of data from drones in an Internet of Drones (IoD).  The IoD is “a layered network control architecture created for the coordination of unmanned aerial vehicle access to controlled airspace and the provision of navigation services between nodes” (p. 108).  This work lists various possible applications in the agriculture space, such as 3D mapping, assessment of soil health, assessment of crop health, assessment of chemicals in the fields, weather prediction, evaluation of irrigation systems, data collection to inform harvesting techniques, the monitoring of stored agricultural products, and others.  They then describe their proposed technological solution for building out an IoD.  They describe their setup as “a self-configuring network” with various devices (p. 121).  For this and other designed networks, a paper prototype may be assessed and perhaps smaller deployments in a controlled space.  

Cloud-Based UAVs for Disaster Management

Nipun Chhabra and Vrajesh Sharma’s “Disaster Management using Cloud-Based UAVs” (Ch. 9) builds on knowledge gleaned from the setting up of the Internet of Things (IoT) networks albeit applied to drones.  Both IoT sensors and sensors on drones have restricted energy sources and low computational capabilities.  Without augmentation of energy and of computational processing and access to communications channels, they cannot be used in real time to inform responses to disasters, like flooding, fires, oil spills, earthquakes, and others.  

The researchers write:  

Wireless sensor network (WSNs) and UAVs technologies can detect fire and assist in evading serious fire accidents at an early stage.  Here, the amalgamation of technologies like Internet of Things (IoTs) sensors, cloud computing, wireless technologies along with the UAVs can be combined to handle (the) outbreak of such incidents. (Chhabra & Sharma, 2022, p. 125)

They elaborate that these technologies have been used for “damage assessment; search and rescue missions; situational awareness, logistics and evacuation; standalone communication system; disaster information fusion and sharing, (and) monitoring, forecast and early warning systems” (p. 128).  What follows are textual descriptions and diagrams explaining the system in general terms.  Deep learning from the collected videos and stills may be analyzed for the presence of fire, for example.  

Blockchain to Address Security Challenges in UAVs

Harmeet Singh’s “Blockchain-Based Methods to Overcome Security Issues in Drones” (Ch. 10) suggests that the popularization of UAVs in industrial and commercial applications have led to heightened attacks on these systems.  This work proposes a blockchain-based security approach to maintain privacy for UAV communications and data.  Singh offers a “multi-stage defensive architecture” proposed as a general system.  The descriptions are not sufficiently specific or detailed enough to use as directions, but these could be used as a starting point (not a blueprint).   


Mohit Angurala and Vikas Khullar’s Revolutionary Applications of Intelligent Drones (2022) does not quite live up to the promise of the title.  Some of the ideas read as relevant, but perhaps not revolutionary.   If the various cases were less thought experiments and more real-world cases, that would be helpful. 

The jury is still out on whether UAVs can add value to various human endeavors.  Will there be sufficient capital investment and brainpower and advocacy to enable lift off?  Regardless, the uses of UAVs beyond military and hobbyist applications seem far out in the future. 

About the Author

Shalin Hai-Jew works as an instructional designer / researcher at Kansas State University.  Her email is  
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