1.
Industrial Revolution
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The Industrial Revolution was the transition to new manufacturing processes in the period from about 1760 to sometime between 1820 and 1840. The Industrial Revolution began in Great Britain and most of the important technological innovations were British, aided by these legal and cultural foundations, an entrepreneurial spirit and consumer revolution drove industrialisation in Britain, which would be emulated in countries around the world. A change in marrying patterns to getting married later made able to accumulate more human capital during their youth. The Industrial Revolution marks a turning point in history, almost every aspect of daily life was influenced in some way. In particular, average income and population began to exhibit unprecedented sustained growth, mechanised textile production spread from Great Britain to continental Europe in the early 19th century, with important centres of textiles, iron and coal emerging in Belgium, and later in France. Since then industrialisation has spread throughout much of the world, the precise start and end of the Industrial Revolution is still debated among historians, as is the pace of economic and social changes. Economic historians are in agreement that the onset of the Industrial Revolution is the most important event in the history of humanity since the domestication of animals and plants. The term Industrial Revolution applied to change was becoming more common by the late 1830s. Friedrich Engels in The Condition of the Working Class in England in 1844 spoke of an industrial revolution, however, although Engels wrote in the 1840s, his book was not translated into English until the late 1800s, and his expression did not enter everyday language until then. Credit for popularising the term may be given to Arnold Toynbee, some historians, such as John Clapham and Nicholas Crafts, have argued that the economic and social changes occurred gradually and the term revolution is a misnomer. This is still a subject of debate among some historians, the commencement of the Industrial Revolution is closely linked to a small number of innovations, beginning in the second half of the 18th century. By the 1830s the following gains had been made in important technologies, Textiles – mechanised cotton spinning powered by steam or water greatly increased the output of a worker, the power loom increased the output of a worker by a factor of over 40. The cotton gin increased productivity of removing seed from cotton by a factor of 50, large gains in productivity also occurred in spinning and weaving of wool and linen, but they were not as great as in cotton. Steam power – the efficiency of steam engines increased so that they used between one-fifth and one-tenth as much fuel, the adaptation of stationary steam engines to rotary motion made them suitable for industrial uses. The high pressure engine had a power to weight ratio. Steam power underwent an expansion after 1800. Iron making – the substitution of coke for charcoal greatly lowered the fuel cost for pig iron, using coke also allowed larger blast furnaces, resulting in economies of scale. The cast iron blowing cylinder was first used in 1760 and it was later improved by making it double acting, which allowed higher furnace temperatures
2.
Cyber-physical system
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A cyber-physical system is a mechanism controlled or monitored by computer-based algorithms, tightly integrated with the internet and its users. Examples of CPS include smart grid, autonomous systems, medical monitoring, process control systems, robotics systems. CPS involves transdisciplinary approaches, merging theory of cybernetics, mechatronics, design, the process control is often referred to as embedded systems. In embedded systems the emphasis tends to be more on the computational elements, CPS is also similar to the Internet of Things sharing the same basic architecture, nevertheless, CPS presents a higher combination and coordination between physical and computational elements. Unlike more traditional embedded systems, a full-fledged CPS is typically designed as a network of interacting elements with physical input and output instead of as standalone devices, the notion is closely tied to concepts of robotics and sensor networks with intelligence mechanisms proper of computational intelligence leading the pathway. Mobile cyber physical systems, in which the system under study has inherent mobility, are a prominent subcategory of cyber-physical systems. Examples of mobile physical systems include mobile robotics and electronics transported by humans or animals, the rise in popularity of smartphones has increased interest in the area of mobile cyber-physical systems. Common applications of CPS typically fall under sensor-based communication-enabled autonomous systems, for example, many wireless sensor networks monitor some aspect of the environment and relay the processed information to a central node. Other types of CPS include smart grid, autonomous systems, medical monitoring, process control systems, distributed robotics. A real-world example of such a system is the Distributed Robot Garden at MIT in which a team of robots tend a garden of tomato plants and this system combines distributed sensing, navigation, manipulation and wireless networking. A focus on the control system aspects of CPS that pervade critical infrastructure can be found in the efforts of the Idaho National Laboratory, another example is MITs ongoing CarTel project where a fleet of taxis work by collecting real-time traffic information in the Boston area. Together with historical data, this information is used for calculating fastest routes for a given time of the day. Cyber-physical models for future manufacturing—With the motivation a cyber-physical system, an approach was developed. The coupled model first constructs an image from the early design stage. System information and physical knowledge are logged during product design, based on which a model is built as a reference for future analysis. Initial parameters may be generalized and they can be tuned using data from testing or the manufacturing process using parameter estimation. The simulation model can be considered as an image of the real machine. These features pave the way toward implementing cyber manufacturing, additionally, as of today there is no language in terms of design practice that is common to all the involved disciplines in CPS
3.
Robotics
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Robotics is the interdisciplinary branch of engineering and science that includes mechanical engineering, electrical engineering, computer science, and others. Robotics deals with the design, construction, operation, and use of robots, as well as systems for their control, sensory feedback. These technologies are used to develop machines that can substitute for humans, Robots can be used in any situation and for any purpose, but today many are used in dangerous environments, manufacturing processes, or where humans cannot survive. Robots can take on any form but some are made to resemble humans in appearance and this is said to help in the acceptance of a robot in certain replicative behaviors usually performed by people. Such robots attempt to replicate walking, lifting, speech, cognition, many of todays robots are inspired by nature, contributing to the field of bio-inspired robotics. Throughout history, it has been assumed that robots will one day be able to mimic human behavior. Many robots are built to do jobs that are hazardous to people such as defusing bombs, finding survivors in unstable ruins, Robotics is also used in STEM as a teaching aid. The word robotics was derived from the robot, which was introduced to the public by Czech writer Karel Čapek in his play R. U. R. which was published in 1920. The word robot comes from the Slavic word robota, which means labour, the play begins in a factory that makes artificial people called robots, creatures who can be mistaken for humans – very similar to the modern ideas of androids. Karel Čapek himself did not coin the word and he wrote a short letter in reference to an etymology in the Oxford English Dictionary in which he named his brother Josef Čapek as its actual originator. According to the Oxford English Dictionary, the word robotics was first used in print by Isaac Asimov, published in May 1941 in Astounding Science Fiction. Asimov was unaware that he was coining the term, since the science and technology of electrical devices is electronics, he assumed robotics already referred to the science and technology of robots. In some of Asimovs other works, he states that the first use of the word robotics was in his short story Runaround, however, the original publication of Liar. Predates that of Runaround by ten months, so the former is generally cited as the words origin, in 1942, the science fiction writer Isaac Asimov created his Three Laws of Robotics. In 1948, Norbert Wiener formulated the principles of cybernetics, the basis of practical robotics, fully autonomous only appeared in the second half of the 20th century. The first digitally operated and programmable robot, the Unimate, was installed in 1961 to lift hot pieces of metal from a die casting machine, commercial and industrial robots are widespread today and used to perform jobs more cheaply, more accurately and more reliably, than humans. They are also employed in jobs which are too dirty, dangerous. For example, a designed to travel across heavy dirt or mud
4.
Artificial intelligence
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Artificial intelligence is intelligence exhibited by machines. Colloquially, the artificial intelligence is applied when a machine mimics cognitive functions that humans associate with other human minds, such as learning. As machines become increasingly capable, mental facilities once thought to require intelligence are removed from the definition, for instance, optical character recognition is no longer perceived as an example of artificial intelligence, having become a routine technology. AI research is divided into subfields that focus on specific problems or on specific approaches or on the use of a tool or towards satisfying particular applications. The central problems of AI research include reasoning, knowledge, planning, learning, natural language processing, perception, general intelligence is among the fields long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI, Many tools are used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience, the field was founded on the claim that human intelligence can be so precisely described that a machine can be made to simulate it. Some people also consider AI a danger to humanity if it progresses unabatedly, while thought-capable artificial beings appeared as storytelling devices in antiquity, the idea of actually trying to build a machine to perform useful reasoning may have begun with Ramon Llull. With his Calculus ratiocinator, Gottfried Leibniz extended the concept of the calculating machine, since the 19th century, artificial beings are common in fiction, as in Mary Shelleys Frankenstein or Karel Čapeks R. U. R. The study of mechanical or formal reasoning began with philosophers and mathematicians in antiquity, in the 19th century, George Boole refined those ideas into propositional logic and Gottlob Frege developed a notational system for mechanical reasoning. Around the 1940s, Alan Turings theory of computation suggested that a machine, by shuffling symbols as simple as 0 and 1 and this insight, that digital computers can simulate any process of formal reasoning, is known as the Church–Turing thesis. Along with concurrent discoveries in neurology, information theory and cybernetics, the first work that is now generally recognized as AI was McCullouch and Pitts 1943 formal design for Turing-complete artificial neurons. The field of AI research was born at a conference at Dartmouth College in 1956, attendees Allen Newell, Herbert Simon, John McCarthy, Marvin Minsky and Arthur Samuel became the founders and leaders of AI research. At the conference, Newell and Simon, together with programmer J. C, shaw, presented the first true artificial intelligence program, the Logic Theorist. This spurred tremendous research in the domain, computers were winning at checkers, solving problems in algebra, proving logical theorems. By the middle of the 1960s, research in the U. S. was heavily funded by the Department of Defense and laboratories had been established around the world. AIs founders were optimistic about the future, Herbert Simon predicted, machines will be capable, within twenty years, Marvin Minsky agreed, writing, within a generation. The problem of creating artificial intelligence will substantially be solved and they failed to recognize the difficulty of some of the remaining tasks
5.
Nanotechnology
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Nanotechnology is manipulation of matter on an atomic, molecular, and supramolecular scale. It is therefore common to see the plural form nanotechnologies as well as nanoscale technologies to refer to the range of research. Because of the variety of applications, governments have invested billions of dollars in nanotechnology research. Until 2012, through its National Nanotechnology Initiative, the USA has invested 3.7 billion dollars, scientists currently debate the future implications of nanotechnology. Nanotechnology may be able to create new materials and devices with a vast range of applications, such as in nanomedicine, nanoelectronics, biomaterials energy production. These concerns have led to a debate among advocacy groups and governments on whether regulation of nanotechnology is warranted. The term nano-technology was first used by Norio Taniguchi in 1974, also in 1986, Drexler co-founded The Foresight Institute to help increase public awareness and understanding of nanotechnology concepts and implications. In the 1980s, two major breakthroughs sparked the growth of nanotechnology in modern era, the microscopes developers Gerd Binnig and Heinrich Rohrer at IBM Zurich Research Laboratory received a Nobel Prize in Physics in 1986. Binnig, Quate and Gerber also invented the atomic force microscope that year. Second, Fullerenes were discovered in 1985 by Harry Kroto, Richard Smalley, and Robert Curl, in the early 2000s, the field garnered increased scientific, political, and commercial attention that led to both controversy and progress. Controversies emerged regarding the definitions and potential implications of nanotechnologies, exemplified by the Royal Societys report on nanotechnology, challenges were raised regarding the feasibility of applications envisioned by advocates of molecular nanotechnology, which culminated in a public debate between Drexler and Smalley in 2001 and 2003. Meanwhile, commercialization of products based on advancements in nanoscale technologies began emerging and these products are limited to bulk applications of nanomaterials and do not involve atomic control of matter. Governments moved to promote and fund research into nanotechnology, such as in the U. S, by the mid-2000s new and serious scientific attention began to flourish. Projects emerged to produce nanotechnology roadmaps which center on atomically precise manipulation of matter and discuss existing and projected capabilities, goals, Nanotechnology is the engineering of functional systems at the molecular scale. This covers both current work and concepts that are more advanced, one nanometer is one billionth, or 10−9, of a meter. By comparison, typical carbon-carbon bond lengths, or the spacing between atoms in a molecule, are in the range 0. 12–0.15 nm. On the other hand, the smallest cellular life-forms, the bacteria of the genus Mycoplasma, are around 200 nm in length, by convention, nanotechnology is taken as the scale range 1 to 100 nm following the definition used by the National Nanotechnology Initiative in the US. The lower limit is set by the size of atoms since nanotechnology must build its devices from atoms and molecules
6.
Quantum computing
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Quantum computing studies theoretical computation systems that make direct use of quantum-mechanical phenomena, such as superposition and entanglement, to perform operations on data. Quantum computers are different from binary digital electronic computers based on transistors, a quantum Turing machine is a theoretical model of such a computer, and is also known as the universal quantum computer. The field of computing was initiated by the work of Paul Benioff and Yuri Manin in 1980, Richard Feynman in 1982. A quantum computer with spins as quantum bits was also formulated for use as a quantum space–time in 1968, there exist quantum algorithms, such as Simons algorithm, that run faster than any possible probabilistic classical algorithm. A classical computer could in principle simulate a quantum algorithm, as quantum computation does not violate the Church–Turing thesis, on the other hand, quantum computers may be able to efficiently solve problems which are not practically feasible on classical computers. A classical computer has a made up of bits, where each bit is represented by either a one or a zero. A quantum computer maintains a sequence of qubits, in general, a quantum computer with n qubits can be in an arbitrary superposition of up to 2 n different states simultaneously. A quantum computer operates by setting the qubits in a drift that represents the problem at hand. The sequence of gates to be applied is called a quantum algorithm, the calculation ends with a measurement, collapsing the system of qubits into one of the 2 n pure states, where each qubit is zero or one, decomposing into a classical state. The outcome can therefore be at most n classical bits of information, Quantum algorithms are often probabilistic, in that they provide the correct solution only with a certain known probability. Note that the term non-deterministic computing must not be used in case to mean probabilistic. An example of an implementation of qubits of a computer could start with the use of particles with two spin states, down and up. This is true because any such system can be mapped onto an effective spin-1/2 system, a quantum computer with a given number of qubits is fundamentally different from a classical computer composed of the same number of classical bits. This means that when the state of the qubits is measured. To better understand this point, consider a classical computer that operates on a three-bit register, if there is no uncertainty over its state, then it is in exactly one of these states with probability 1. However, if it is a computer, then there is a possibility of it being in any one of a number of different states. The state of a quantum computer is similarly described by an eight-dimensional vector. Here, however, the coefficients a k are complex numbers, and it is the sum of the squares of the absolute values, ∑ i | a i |2
7.
Internet of things
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In 2013 the Global Standards Initiative on Internet of Things defined the IoT as the infrastructure of the information society. Each thing is uniquely identifiable through its embedded computing system but is able to interoperate within the existing Internet infrastructure, experts estimate that the IoT will consist of almost 50 billion objects by 2020. Legal scholars suggest to look at Things as a mixture of hardware, software, data. These devices collect data with the help of various existing technologies. IoT is one of the platforms of todays Smart City, the term the Internet of Things was coined by Kevin Ashton of Procter & Gamble, later MITs Auto-ID Center, in 1999. This means that the fields of embedded systems, wireless sensor networks, control systems, automation. Mark Weisers seminal 1991 paper on ubiquitous computing, The Computer of the 21st Century, as well as venues such as UbiComp. In 1994 Reza Raji described the concept in IEEE Spectrum as small packets of data to a set of nodes. Between 1993 and 1996 several companies proposed solutions like Microsofts at Work or Novells NEST, however, only in 1999 did the field start gathering momentum. Bill Joy envisioned Device to Device communication as part of his Six Webs framework, the concept of the Internet of Things became popular in 1999, through the Auto-ID Center at MIT and related market-analysis publications. Radio-frequency identification was seen by Kevin Ashton as a prerequisite for the Internet of things at that point, Ashton prefers the phrase Internet for Things. If all objects and people in life were equipped with identifiers, computers could manage. Besides using RFID, the tagging of things may be achieved through such technologies as near field communication, barcodes, QR codes, for instance, instant and ceaseless inventory control would become ubiquitous. A persons ability to interact with objects could be altered based on immediate or present needs. According to Gartner, Inc. there will be nearly 20.8 billion devices on the Internet of things by 2020, ABI Research estimates that more than 30 billion devices will be wirelessly connected to the Internet of things by 2020. As such, it is clear that the IoT will consist of a large number of devices being connected to the Internet. In an active move to new and emerging technological innovation. The ability to network embedded devices with limited CPU, memory, on the other hand, IoT systems could also be responsible for performing actions, not just sensing things
8.
3D printing
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Objects can be of almost any shape or geometry and are produced using digital model data from a 3D model or another electronic data source such as an Additive Manufacturing File file. The term 3D printing originally referred to a process that deposits a binder material onto a bed with inkjet printer heads layer by layer. More recently, the term is being used in popular vernacular to encompass a variety of additive manufacturing techniques. United States and global technical standards use the term additive manufacturing for this broader sense. Early additive manufacturing equipment and materials were developed in the 1980s, but on July 16,1984 Alain Le Méhauté, Olivier de Witte and Jean Claude André filed their patent for the stereolithography process. It was three weeks before Chuck Hull filed his own patent for stereolithography, the application of French inventors were abandoned by the French General Electric Company and CILAS. The claimed reason was for lack of business perspective, Hull defined the process as a system for generating three-dimensional objects by creating a cross-sectional pattern of the object to be formed, but this had been already invented by Kodama. Hulls contribution is the design of the STL file format widely accepted by 3D printing software as well as the digital slicing, the term 3D printing originally referred to a process employing standard and custom inkjet print heads. The technology used by most 3D printers to date—especially hobbyist and consumer-oriented models—is fused deposition modeling, AM processes for metal sintering or melting usually went by their own individual names in the 1980s and 1990s. But AM-type sintering was beginning to challenge that assumption, by the mid 1990s, new techniques for material deposition were developed at Stanford and Carnegie Mellon University, including microcasting and sprayed materials. Sacrificial and support materials had become more common, enabling new object geometries. The umbrella term additive manufacturing gained wider currency in the decade of the 2000s, as the various additive processes matured, it became clear that soon metal removal would no longer be the only metalworking process done under that type of control. It was during this decade that the term subtractive manufacturing appeared as a retronym for the family of machining processes with metal removal as their common theme. The term subtractive has not replaced the term machining, instead complementing it when a term that covers any removal method is needed, both terms reflect the simple fact that the technologies all share the common theme of sequential-layer material addition/joining throughout a 3D work envelope under automated control. The 2010s were the first decade in which metal end use parts such as engine brackets, agile tooling uses a cost effective and high quality method to quickly respond to customer and market needs. It can be used in hydro-forming, stamping, injection molding, as technology matured, several authors had begun to speculate that 3D printing could aid in sustainable development in the developing world. 3D printable models may be created with a computer-aided design package, via a 3D scanner, or by a digital camera. 3D printed models created with CAD result in reduced errors and can be corrected before printing, allowing verification in the design of the object before it is printed, the manual modeling process of preparing geometric data for 3D computer graphics is similar to plastic arts such as sculpting
