1. VIRTUAL REALITY
Virtual Reality (VR), which can be referred to as immersive multimedia or computer-simulated life, replicates an environment that simulates physical presence in places in the real world or imagined worlds.
Virtual reality can recreate sensory experiences, which include virtual taste, sight, smell, sound, and touch.
Virtual reality is often used to describe a wide variety of applications commonly associated with immersive, highly visual, 3D environments.
The development of CAD software, graphics hardware acceleration, head-mounted displays, datagloves, and miniaturization have helped popularize the notion.
In the book The Metaphysics of Virtual Reality by Michael R. Heim, seven different concepts of virtual reality are identified: simulation, interaction, artificiality, immersion, telepresence, full-body immersion, and network communication.
People often identify VR with head mounted displays and data suits .
1. “Virtual Reality is a way for humans to visualize, manipulate and interact with computers and extremely complex data. It allows us to interact with computer – simulated objects, entities and environment as if they actually exist”.
2. “VR is computer – simulated reality that had its origin in efforts to build more natural, realistic, multisensory human / computer interfaces”.
3. “VR is also called ‘tele-presence’, when VR systems to work alone or together at a remote site. Example: virtual surgery where surgeon and patient may be on either side of the globe”.
HISTORY :
n 1961, Philco Corporation engineers developed the first HMDknown as the Headsight. The helmet consisted of a video screen along with a tracking system. Then they linked to a closed circuit camera system. Then somewhat similar HMD was used for helicopter pilots. While flying in the dark these were of great help.
In 1965, a computer scientist named Ivan Sutherland envisioned what he called the “Ultimate Display.” After using this display a person imagines the virtual world very similar to the real world.
During 1966, an HMD was built by Sutherland, which was tethered to a computer system.
TECHNOLOGY USED
1. Most up to date virtual reality environments are displayed either on a computer screen or with special stereoscopic displays, and some simulations include additional sensory information and focus on real sound through speakers or headphones targeted towards VR users.
2. Some advanced, haptic, systems now include tactile information, generally known as force feedback in medical, gaming and military applications.
3. Virtual reality covers remote communication environments which provide virtual presence of users with the concepts of telepresence and telexistence or a virtual artifact (VA) either through the use of standard input devices such as a keyboard and mouse, or through multimodal devices such as a wired glove oromnidirectional treadmills.
4. The simulated environment can be similar to the real world in order to create a lifelike experience—for example, in simulations for pilot or combat training—or it differs significantly from reality, such as in VR games.
Method:
The method does not produce true 3-dimensional images, but it does provide a 3-dimensional effect by presenting a different view to each eye of an observer so that scenes do appear to have depth.
Users can construct the two views as computer generated scenes with different viewing positions, or we can use stereo camera pair to paragraph some object or scene.
When users have simultaneous look at the left view with left eye and the right view with the right eye, the two views merge into a simple image and we perceive a scene with depth.
The method does not produce true 3-dimensional images, but it does provide a 3-dimensional effect by presenting a different view to each eye of an observer so that scenes do appear to have depth.
Users can construct the two views as computer generated scenes with different viewing positions, or we can use stereo camera pair to paragraph some object or scene.
When users have simultaneous look at the left view with left eye and the right view with the right eye, the two views merge into a simple image and we perceive a scene with depth.
USE
1. Heritage and archaeology :
- Virtual reality enables heritage sites to be recreated extremely accurately, so that the recreations can be published in various media. The original sites are often inaccessible to the public, or may even no longer exist.
- This technology can be used to develop virtual replicas of caves, natural environment, old towns, monuments, sculptures and archaeological elements.
- The first use of a VR presentation in a heritage application was in 1994, when a museum visitor interpretation provided an interactive "walk-through" of a 3D reconstruction of Dudley Castlein England as it was in 1550. This consisted of a computer controlled laserdisc-based system designed by British-based engineer Colin Johnson.
2. Education :
- Strides are being made in the realm of education, although much needs to be done. The possibilities of VR and education are endless and bring many advantages to pupils of all ages.
- Few are creating content that may be used for educational purposes, with most advances being done in the entertainment industry, but many understand and realize the future and the importance of education and VR.
3. Fiction :
- Many science fiction books and films have imagined characters being "trapped in virtual reality".
- A comprehensive and specific fictional model for virtual reality was published in 1935 in the short story Pygmalion's Spectacles by Stanley G. Weinbaum. A more modern work to use this idea was Daniel F. Galouye's novel Simulacron-3, which was made into a German teleplay titled Welt am Draht ("World on a Wire") in 1973.
- Other science fiction books have promoted the idea of virtual reality as a partial, but not total, substitution for the misery of reality, or have touted it as a method for creating virtual worlds in which one may escape from Earth.
4. Motion pictures :
- Rainer Werner Fassbinder's 1973 film Welt am Draht is based on a virtual reality simulation inside a virtual reality simulation
- In 1983, the Natalie Wood / Christopher Walken film Brainstorm revolved around the production, use, and misuse of a VR device.
- Total Recall (1990 film), directed by Paul Verhoeven and based on the Philip K. Dick story "We Can Remember It for You Wholesale"
5. Business :
- For some businesses, fully immersive virtual reality a la CAVE system is the way forward. They like the fact that they can use this to test drive a product in the early stages of development but without any additional costs (or risks) to themselves.
- This is particularly useful for companies who produce dangerous or potentially harmful products which need to be evaluated before use. They can test their product within a virtual environment but at no risk to themselves or their employees. And virtual reality technology has advanced to the stage where it has a high degree of realism and efficiency.
- Some companies use virtual reality to help with data analysis and forecasting trends in order to gain an edge over their competitors. One example of this is a system developed by researchers at the University of Warwick which is designed to help businesses gain a greater understanding of their data.
- There are companies who use virtual worlds as a means of holding meetings with people who are based in various locations. This is often a low cost solution to the problem of communication with large numbers of employees in remote locations.
6. Medicine :
- Virtual Diagnosis : It is used for visualisation purposes when formulating a diagnosis. Reaching a diagnosis means conducting a series of tests which produce complex sets of data. But virtual reality can be used to create a visual explanation of this data which is easier to read, understand and interpret.
- Virtual Emergency : It is also used when training front line professionals, e.g. first responders to deal with small and large scale emergencies. A series of virtual environments can be developed which contain different scenarios, e.g. road traffic accident which the first responders have to deal with. This is where they learn decision making skills as well as the practical hands on skills required in this type of situation. Another option is disaster training such as a chemical spillage or an outbreak of an infectious disease which often results in large numbers of casualties.
- Augmented reality can allow people with disabilities to experience places and tasks that are otherwise unavailable to them.
- A person in a wheelchair can play a basketball game with the aid of virtual reality games.
- A person undergoing psychotherapy to confront a past event can do so safely in a virtual reality world without the fear of physical harm.
LATEST DEVELOPMENTS IN VIRTUAL REALITY :
Virtual Worlds
Virtual worlds combine the power of 3D graphics and the internet, giving users the ability to create new versions of themselves literally within a virtual world.
Second Life, arguably the most popular of these games, has seen massive successes, which includes creating millionaires out of some of their long-time and most dedicated players. This is made possible by their own currency and exchange rates.
Virtual worlds have become so popular, laws have been extended to include property acquired on them.
Input Devices
In a similar thread of thought, modern input devices have been massively influenced by virtual reality and may become the corner stone of further virtual reality developments. Some of these include:
- Microsoft's Kinect – This device uses a camera to track a player's movements, which are then reflected in-game.
- Wii Controls – The Wii, mostly due to its controls, took the world by storm. Using a controller, which can be latched to the hand, movement becomes a form of input.
ADVANTAGES :
- Virtual reality creates a realistic world
- It enables user to explore places.
- Through Virtual Reality user can experiment with an artificial environment.
- Virtual Reality make the education more easily and comfort.
- Computer-aided design allows architects to build and envision a structure to eliminate any potential problems before money is spent actualizing the design.
- 1. The quipments used in virtual reality are very expensive.
- 2. It consists of complex technology.
- 3. In virtual reality environment we cant move by our own like in the real world.
2. ARTIFICIAL INTELLIGENCE
Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behaviour.
John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines".
Major AI researchers and textbooks define this field as "the study and design of intelligent agents",in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.
AI research is highly technical and specialized, and is deeply divided into subfields :
- Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers.
- AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems.
- Others focus on one of several possible approaches or on the use of a particular tool or towards the accomplishment of particular applications.
GOALS OF ARTIFICIAL INTELLIGENCE :
1. Deduction, reasoning, problem solving
- Early AI researchers developed algorithms that imitated the step-by-step reasoning that humans use when they solve puzzles or make logical deductions.By the late 1980s and 1990s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.
- For difficult problems, most of these algorithms can require enormous computational resources – "combinatorial explosion": the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size. The search for more efficient problem-solving algorithms is a high priority for AI research.
- AI has made some progress at imitating this kind of "sub-symbolic" problem solving: embodied agent approaches emphasize the importance of sensorimotor skills to higher reasoning; neural net research attempts to simulate the structures inside the brain that give rise to this skill; statistical approaches to AI mimic the probabilistic nature of the human ability to guess.
2. Knowledge representation
- Knowledge representation and knowledge engineering are central to AI research. Many of the problems machines are expected to solve will require extensive knowledge about the world.
- Among the things that AI needs to represent are: objects, properties, categories and relations between objects; situations, events, states and time; causes and effects; knowledge about knowledge (what we know about what other people know); and many other, less well researched domains.
- A representation of "what exists" is an ontology: the set of objects, relations, concepts and so on that the machine knows about. The most general are called upper ontologies, which attempt to provide a foundation for all other knowledge.
An ontology represents knowledge as a set of concepts within a domain and the relationships between those concepts.
Among the most difficult problems in knowledge representation are:
- Default reasoning and the qualification problem :Many of the things people know take the form of "working assumptions."
- The breadth of common sense knowledge :The number of atomic facts that the average person knows is astronomical.
- The sub symbolic form of some common sense knowledge :Much of what people know is not represented as "facts" or "statements" that they could express verbally.
3. Planning :
- Intelligent agents must be able to set goals and achieve them. They need a way to visualize the future (they must have a representation of the state of the world and be able to make predictions about how their actions will change it) and be able to make choices that maximize the utility (or "value") of the available choices.
- In classical planning problems, the agent can assume that it is the only thing acting on the world and it can be certain what the consequences of its actions may be.
- However, if the agent is not the only actor, it must periodically ascertain whether the world matches its predictions and it must change its plan as this becomes necessary, requiring the agent to reason under uncertainty.
- Multi-agent planning uses the cooperation and competition of many agents to achieve a given goal. Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence.
4. Learning
- Machine learning is the study of computer algorithms that improve automatically through experience and has been central to AI research since the field's inception.
- Unsupervised learning is the ability to find patterns in a stream of input. Supervised learning includes both classification and numerical regression.
- Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories.
- Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change. In reinforcement learning the agent is rewarded for good responses and punished for bad ones. The agent uses this sequence of rewards and punishments to form a strategy for operating in its problem space.
- Within developmental robotics, developmental learning approaches were elaborated for lifelong cumulative acquisition of repertoires of novel skills by a robot, through autonomous self-exploration and social interaction with human teachers, and using guidance mechanisms such as active learning, maturation, motor synergies, and imitation.
5. Natural language processing (communication)
- Natural language processing gives machines the ability to read and understand the languages that humans speak.
- A sufficiently powerful natural language processing system would enable natural language user interfaces and the acquisition of knowledge directly from human-written sources, such as news wire texts.
- Some straightforward applications of natural language processing include information retrieval .
- A common method of processing and extracting meaning from natural language is through semantic indexing.Increases in processing speeds and the drop in the cost of data storage makes indexing large volumes of abstractions of the user's input much more efficient.
6. Perception
- Machine perception is the ability to use input from sensors (such as cameras, microphones, tactile sensors, sonar and others more exotic) to deduce aspects of the world.
- Computer vision is the ability to analyse visual input. A few selected sub problems are speech recognition, facial recognition and object recognition.
7. Motion and manipulation
- Artificial Intelligence is required for robots to be able to handle such tasks as object manipulation and navigation, with sub-problems of localization(knowing where you are, or finding out where other things are), mapping (learning what is around you, building a map of the environment), and motion planning (figuring out how to get there) or path planning (going from one point in space to another point, which may involve compliant motion – where the robot moves while maintaining physical contact with an object).
8. Long-term goals
Among the long-term goals in the research pertaining to artificial intelligence are: (1) Social intelligence, (2) Creativity, and (3) General intelligence.
(1)Social intelligence
- Emotion and social skills play two roles for an intelligent agent.
- First, it must be able to predict the actions of others, by understanding their motives and emotional states. This involves elements of game theory, decision theory, as well as the ability to model human emotions and the perceptual skills to detect emotions.
- Also, in an effort to facilitate human-computer interaction, an intelligent machine might want to be able to display emotions—even if it does not actually experience them itself—in order to appear sensitive to the emotional dynamics of human interaction.
- Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects.
- It is an interdisciplinary field spanning computer sciences, psychology, and cognitive science.
(2) Creativity
- A sub-field of AI addresses creativity both theoretically (from a philosophical and psychological perspective) and practically (via specific implementations of systems that generate outputs that can be considered creative, or systems that identify and assess creativity).
- Related areas of computational research are Artificial intuition and Artificial thinking.
(3) General intelligence
- Many researchers think that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them.
- A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.
APPROACHES OF ARTIFICIAL INTELLIGENCE :
- 1. Cybernetics and brain simulation :
- --Cybernetics is relevant to the study of systems, such as mechanical, physical, biological, cognitive, and social systems.
- --Cybernetics is applicable when a system being analyzed incorporates a closed signaling loop; that is, where action by the system generates some change in its environment and that change is reflected in that system in some manner (feedback) that triggers a system change, originally referred to as a "circular causal" relationship.
- Top-down: it subdivides, in a recursive manner, a given problem into a series of sub-problems that are supposedly easier to solve.
- Knowledge-based: it relies on a symbolic description of the world, such as a set of rules.
- It is bottom-up: it relies on elementary behaviors, which can be combined to implement more complex behaviors.
- It is behavior-based: it does not rely on a symbolic description of the environment, but rather on a model of the interactions of the entities with their environment.
- 2. Symbolic Approach :
--When access to digital computers became possible in the middle 1950s, AI research began to explore the possibility that human intelligence could be reduced to symbol manipulation.
--The research was centered in three institutions: Carnegie Mellon University, Stanford and MIT, and each one developed its own style of research. John Haugeland named these approaches to AI "good old fashioned AI" or "GOFAI".
2 Approaches to Symbolic AI :
3. Situated or Behavioral AI Approach :
In order to address these issues, another approach to decisional AI, approach known as situated or behavioral AI, has been proposed. It does not attempt to model systems that produce deductive reasoning processes, but rather systems that behave realistically in their environment. The main characteristics of this approach are the following:
The goal of situated AI is to model entities that are autonomous in their environment. This is achieved thanks to both the intrinsic robustness of the control architecture, and its adaptation capabilities to unforeseen situations.
IMPLEMENTATION PRINCIPLES OF AI:
1. Modular decomposition
The most important attribute of a system driven by situated AI is that the intelligence is controlled by a set of independent semi-autonomous modules. In the original systems, each module was actually a separate device or was at least conceived of as running on its own processing thread. Generally, though, the modules are just abstractions. In this respect, situated AI may be seen as a software engineering approach to AI, perhaps akin to object oriented design.
Situated AI is often associated with reactive planning, but the two are not synonymous. Brooks advocated an extreme version of cognitive minimalism which required initially that the behavior modules were finite state machines and thus contained no conventional memory or learning. This is associated with reactive AI because reactive AI requires reacting to the current state of the world, not to an agent's memory or preconception of that world. However, learning is obviously key to realistic strong AI, so this constraint has been relaxed, though not entirely abandoned.
2. Action selection mechanism
The situated AI community has presented several solutions to modeling decision-making processes, also known as action selection mechanisms.
The first attempt to solve this problem goes back to subsumption architectures, which were in fact more an implementation technique than an algorithm.
However, this attempt paved the way to several others, in particular the free-flow hierarchies and activation networks.
A comparison of the structure and performances of these two mechanisms demonstrated the advantage of using free-flow hierarchies in solving the action selection problem.
However, motor schemas and process description languages are two other approaches that have been used with success for autonomous robots.
APPLICATIONS OF AI :
2. Diagnosis (artificial intelligence)
3. Game theory and Strategic planning.
4. Game artificial intelligence and Computer game bot.
5. Natural language processing, Translation and Chatterbots.
6. Nonlinear control and Robotics.
3. INFORMATION SUPER HIGHWAYS :
The information superhighway or infobahn was a popular term used through the 1990s to refer to digital communication systems and the Internet telecommunications network. It is associated with United States Senator and later Vice-President Al Gore.
The McGraw-Hill Computer Desktop Encyclopedia defines the term as "a proposed high-speed communications system that was touted by the Clinton/Gore administration to enhance education in America in the 21st Century. Its purpose was to help all citizens regardless of their income level.
The Internet was originally cited as a model for this superhighway; however, with the explosion of the World Wide Web, the Internet became the information superhighway" .
One of the most significant developments in the late 1990s, that has changed the perspective of present day managers is the emergence of information superhighways. As the highways carry the traffic to far flung-areas at a high speed, the modern information superhighways carry information all over the globe. The trend towards open, high-speed, digital networks with fibre optics and satellite links and the widespread use of the internet and its technologies have made the concept of an information superhighway technically feasible and captured the interest of both business and government. In this concept, local, regional, nationwide, and global networks will be integrated into a vast network of networks, with more advanced interactive multimedia capabilities than the Internet.
Definition:
The information superhighway is high speed digital telecommunication networks that are national or worldwide in scope and accessible by the general public rather than restricted to use by members of a specific organization or set of organizations such as a corporation.
NEED :
1. The information superhighway is needed to create an information infrastructure that would dramatically increase business efficiency and competitiveness by improving economic communications, electronic commerce and collaboration, and information gathering.
2. It involves new ways to obtain and disseminate information that virtually eliminate the barriers of time and place.
The customers are now able to perform the following tasks with information superhighways:
Processing of banking transactions.
Easily access to huge multimedia library.
Send real time video message to friends and relatives.
Watch movies and programs on demand.
Direct to home (DTH) facility, etc.
