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The Evolution of the Wheel: Implications for Business and Society

Humankind has always engaged in invention of things to make life easier on the planet Earth. For example, the Sumerians are given the credit to have invented the wheel to transport things from one place to another. Wheels were invented circa 3,500 B.C., and rapidly spread across the Eastern Hemisphere. Historically speaking, wheels are the archetype of a primitive, caveman-level technology. But in fact, they are so ingenious that it took until 3500 B.C. for someone to invent them.

The oldest known wheel used for transportation was found by archaeologists in Mesopotamia. It is believed to date back to 3,500 B.C. However, wheels had been in operation for hundreds of years before that to make pottery, as it is believed that potters' wheels existed since the Neolithic Era. Ample evidence also suggests that the first wheel dates back to 3500 B.C., according to the Smithsonian Magazine.

Most scholars believe that the wheel first came into existence in the area of Mesopotamia, in what is today modern Iraq. Archaeological evidence also indicates that early wheels were used for pottery, not for transporting goods or people. Some researchers believe that as many as three hundred years passed between when the first wheel was created and when people used them to make chariots for war.

While in the past the wheels of invention turned very slowly, in the 21st century science and technology are producing mindboggling innovations exponentially. In modern times, the use of wheels have proliferated almost every aspect of human activity. One major area is the automobile which has changed the landscape of human habitation on the planet Earth. Humankind has had a love affair with the automobile to the extent that every year most people prefer to see a new model of their preferred make of automobile.

Innovation in the new automobiles have been continuous for over 200 years. For a great recent example is the self-driving trucks which promises to have profound effect on business and society. Tractor-trailers without a human at the wheel will soon barrel onto highways in your neighborhood. What will this mean for the nation’s 1.7 million truck drivers? They will have to go jobless for a while, until they are trained for other kind of employment.

As for the effect on society, imagine if you will for a moment: you are driving on a two lane road and you notice that in the oncoming traffic there is a truck approaching you in the opposite direction. Suddenly, you notice that there is no diver in that truck! How would you react to a situation like this? I would break into a profuse perspiration and cringe at the fear that if the computer brain of that truck makes the slightest mistake, I would end up having a head-on collision with a leviathan. Thus, the negative psychological effect on ordinary people would be enormous. Some would opt not to drive anymore for fear of collision with self-driving automobiles.

Autonomous vehicles are based on LIDAR technology, a detection system that works on the principle of radar, but uses light from a laser. Applications like LIDAR, laser scanning devices and 3D LIDAR used in autonomous vehicle applications require very high performance to acquire the data, process the data and get the relevant data to the central control system in sufficient time to make decisions for vehicle steering (control) and to avoid objects which have come into the vehicle’s path. The devices need to be small, light-weight and cost effective in order to be used in high volume applications.

Is LIDAR technology 100 percent accurate, one may ask? Like all technologies, the accuracy depends on the environmental circumstances in which it operates. LIDAR is a surveying method that measures distance to a target by illuminating that target with a laser light. For example, autonomous robots have been used for a variety of purposes in agriculture ranging from seed and fertilizer dispersions, sensing techniques as well as crop scouting for the task of weed control. In order to execute weed control, one of the major factors is the detection and classification of the plant and species. Additionally, it is difficult to differentiate the characteristics and appearances of the plant and convert the data into computer understandable form. Also, it is not possible to accurately detect structures of the plant in 3D data. The problem is somewhat solved by classifying the plant species by using a set of example plants and machine learning methods. In the self-driving vehicles, the classification of objects in the environment would a herculean task, if not an impossible one.

Like all robotics, humans are replaced with machines. But the most fearful aspect of the autonomous, self-driving vehicles is the possibility of error involved in assessing objects in the environment of the self-driving vehicle. The feeling that you might run into an accident is a crippling fear to contend with while one is on the road with self-driving vehicles. So, please Santa, I do not want a self-driving vehicle to have or to face one on the road. Thank you for the thought, just the same!

Z. S. Demirdjian, Ph.D.

Senior Review Editor

California State University, Long Beach, CA