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How Deep Learning Can Transform the Transportation Sector

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How Deep Learning Can Transform the Transportation Sector


Deep learning in transportation is expected to plug out some of the oldest and most stubborn problems affecting the sector’s overall performance.

A lot of buzz around this topic, isn’t it? Well, due to its breathtaking innovation, deep learning has left various industries astonished, and the transportation industry is no exception. The industry is so large that the annual GDP amounts to 471.90 U.S.D. billion in the U.S. alone. However, this industry that forms the backbone of any economy faces some severe challenges as the scale of operation escalates. Grand View Research’s latest report stated that the deep learning market would reach a value of $10.2 billion by the end of the year 2025, which highlights the growing popularity of this technology.

When both the industry and the technology are growing at such a rate, why not use deep learning in transport to up the performance of this sector. Challenges faced by the transportation sector There are innumerable challenges faced by the transport industry. First comes the growing traffic, which needs to be resolved at the earliest. Besides, the marine traffic has been growing significantly over the last few years. There is no denying the fact that the current traffic prediction model does not forecast the traffic flow as accurately as it should.

You might have experienced situations where you planned to travel to someplace and unfortunately the train either got delayed or got canceled. The air transportation faces several challenges too. During a crisis or during uncertain weather conditions, the pilot should have insights on all possible safe routes without a second’s delay. Unfortunately, there is heavy reliance on past data and estimations when transportation strategies are devised.

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Deep learning in Transportation


Deep learning can address issues using the ‘deep approach’ of neural architecture. Deep learning will, therefore, help the transportation industry predict the traffic flow well in time to avoid any accidents or distress, whatsoever. With huge chunks of data, deep learning algorithms analyze the hidden patterns in data. Such an algorithm helps the transportation industry rise above trivial issues like traffic. In case of a train delay, deep learning systems can automatically notify the travelers about a reschedule well in advance. In case a train gets canceled, customers can get their tickets rescheduled with the help of these systems as well.

You must note here that autonomous vehicles will enhance the safety of riders in the near future. Imagine toddlers of today will never drive their vehicles manually, they will instead have the assistance of ‘self-driving cars.’ Self-driving cars will drastically reduce the number of lives lost due to accidents globally. This will also solve problems associated with air pollution. And all of this becomes possible only because of deep learning.

Deep learning in the transportation sector offers optimized traffic flow predictions, accurate weather predictions, and can help reduce pollution. 

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TECHNOLOGY

The Current State and Future of Telepresence Robots in the Educational Sector

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The Current State and Future of Telepresence Robots in the Educational Sector


The introduction of telepresence robots in education has made learning more accessible and more engaging by bridging the physical disconnection between teachers and students.

When you hear the phrase ‘robots in education’, you can be excused for imagining a fully functional humanoid machine shouting out instructions in its metallic voice and giving lectures to a class full of half-terrified kids. However, although robots are becoming capable of socializing and have made their way into the education sector, they still aren’t capable of teaching entire curriculums to students in the interactive way that actual teachers can do. Nevertheless, for the time being, they are helping people in the form of telepresence robots by enabling teachers to teach and interact with students remotely. The use of telepresence robots in education is helping students learn better and is making education accessible to those who cannot access it due to different circumstances.

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The Current State of Telepresence Robots in Education

Remote learning and teaching has already become commonplace in the world of education. The advent of the internet has spawned numerous remote learning opportunities like massive open online courses (MOOCs) and micro-credentials. As another application born from the internet and combined with robotics and sensor technology, telepresence robots are already making an impact in the field of education by extending the accessibility of education beyond schools and other educational institutions. Although they are yet to see mass adoption in conventional classroom education, telepresence robots are helping children who cannot go to regular classes due to chronic illnesses and other physically limiting conditions. Students suffering from chronic illnesses take lessons from teachers remotely through telepresence robots. These students have a telepresence robot that is equipped with a tablet that teachers from anywhere in the world can use to stream lessons. There are also cases of chronically ill students attending classes using stand-in telepresence robots and experiencing classes like regular students, engaging in two-way communication. Telepresence robots also make for excellent teachers for students with special needs, such as those having autism, helping them focus better and learn at their own pace.

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The Future of Telepresence Robots in Education

As telepresence robots are becoming more ubiquitous in education, they are also being considered for use in regular classrooms. Having a telepresence robot enables educational institutions experts from across the world to interact with and teach students, enriching their educational experience. As the global interconnectivity increases, remote learning and micro-credentials will gain more popularity. This rise in the preference for remote learning will lead to a growth in the adoption of telepresence robots in education. Telepresence robots offer more interpersonal face-to-face interaction than regular MOOCs, and can potentially gain mass preference over regular online courses, and become the standard for online learning, and even the educational sector as a whole.

Although robots and artificial intelligence are getting ever-closer to functioning like humans, and the robotification of society is seemingly approaching, teaching is an area that is among the ones furthest from being robotified. However, the use of telepresence robots in education will continue to rise, to the benefit of both students and teachers across the world.



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