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A Revolution in the Sky

Holly Dale explores the utilization of drones in our future, whether that be good or bad.

Picture this: the year is 2030 and you are plunged into darkness as a cloud of drones flies overhead. Is this a society thriving on innovation, or a terrifying dystopian landscape? Either way, this scenario might not be as far-fetched as you think - our airspace is currently undergoing a revolution. In recent years, the number of drones that have exploded, and the total number of air vehicles is expected to double in the next 10 years. The miniaturisation of electronic components means that drones are becoming smaller, cheaper, and easier to operate, making them increasingly attractive for both commercial and recreational use.

A vast array of drone models are available, with choice of weight, wing span, flight altitude, and battery life, making them suitable for a range of applications. Miniature electromechanical ‘smart dust’ drones can have a wingspan as small as 1 mm, whilst large drones can have wingspans as large as that of large commercial aircraft.

Drones are particularly useful in situations that are unsafe or unsuitable for humans. For example, they can be used to aid the emergency services by facilitating search and rescue missions, assisting at accident scenes, and reducing the risk of harm to firefighters. The increasing number of drones is expected to boost the UK Gross Domestic Product (GDP) by £42 billion by 2030 across many industries including media, agriculture, construction, parcel delivery and transport.

However, the use of drones in congested airspace risks collisions with manned aircraft, with drone-aircraft near misses becoming increasingly common. In December 2018, a drone sighting at Gatwick Airport caused around 1000 flights to be cancelled or diverted, affecting hundreds of thousands of passengers.

Imposing regulations on drone ownership and usage can reduce the risk of accidental damage, but will not prevent intentional acts by criminals. Potential criminal applications range from privacy violations and illegal surveillance to smuggling drugs into prisons or across borders. There are also concerns about the possibility of terrorists using drones to release a biological or chemical agent into a crowd. The question is, how can we eliminate the threats so that we can continue to benefit from drones in our daily lives?

Clearly there is a need to detect, identify, and neutralise malicious drones. Radar is emerging as a leading drone surveillance method, it is capable of offering 24-hour surveillance under all weather conditions, unlike visual identification. Drones are relatively small and they fly at low altitudes and velocities, meaning that a radar with high sensitivity is needed for detection. Consequently, lots of other targets are also detected and birds, animals, vehicles, and even air conditioning units can cause false alarms. Ground based targets can be filtered out using height measurements, but distinguishing drones from birds can be difficult. Researchers are currently investigating methods of distinguishing between drones and birds using deep learning techniques.

If the problem wasn’t already challenging enough, drones can be disguised in many ways. Biologically inspired drones with flapping wings have been designed to mimic the flight of birds, bats, and insects. Electronic components have been added to taxidermy animal and bird bodies, resulting in a RoboSparrow and even an OstrichCopter.

In the right hands drones can improve our lives and our economy, but in the wrong hands they have the potential to be lethal. This is why it is so important to develop techniques of tracking drones so that we know exactly what is flying over our heads. Whether the thought of a swarm of drones coming over the horizon fills you with excitement or with terror, one thing is for certain: drones are here to stay.

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M. Hassanalian, A. Abdelkefi, Classifications, applications, and design challenges of drones: A review, Progress in Aerospace Sciences, Volume 91,2017,Pages 99-131,ISSN 0376-0421,

Taha, Bilal & Shoufan, Abdulhadi. (2019). Machine Learning-Based Drone Detection and Classification: State-of-the-Art in Research. IEEE Access. PP. 1-1. 10.1109/ACCESS.2019.2942944.

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