Artificial Intelligence is the machines which are designed and programmed in such a manner that they and think and act like a human. Artificial Intelligence becomes the important part of our daily life. Our life is changed by AI because this technology is used in a wide area of day to day services. These technologies reduce human effort. Now in many industries, people are using this technology to develop machine slaves to perform the different activity. Using the machine for the work speed up your process of doing work and give you an accurate result. It is very likely that areas in which the universal intelligence of the human level is not needed will reach maturity and produce reliable high-quality products in the next decade. Efforts to improve quality and expand boundaries for text and video understanding systems, and to give home robots greater reliability and overall utility, will lead to systems of common-sense linking learning and action together in all these modalities.Especially given the massive growth of machine-readable data on human activities and the need for machines that understand human values ​​if such machines are reliable and useful. Public and private sources of knowledge will become part of society.

Automation describes a wide range of technologies that reduce human intervention in processes. Human intervention is reduced by predetermining decision criteria, sub process relationships, and related actions — and embodying those predeterminations in machines.

Automation, includes the use of various equipment and control systems such as machinery, processes in factories, boilers, and heat-treating ovens, switching on telephone networks, steering, and stabilization of ships, aircraft, and other applications and vehicles with reduced human intervention Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories ,airpalnes , and ships typically use all these combined techniques. The benefit of automation includes labor savings, reducing waste, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision.

Computer engineering (CoE or CpE) is a branch of electrical engineering  that integrates several fields of  computer science and  electronic engineering required to develop computer hardware and software. Computer engineers usually have training in electronic engineering, software design, and hardware-software integration instead of only software engineering or electronic engineering. Computer engineers are involved in many hardware and software aspects of computing, from the design of individual microcontrollers, microprocessors, personal computers, and supercomputers, to circuit design. This field of engineering not only focuses on how computer systems themselves work but also how they integrate into the larger picture. Information technology (IT) is the use of computers to create, process, store, retrieve, and exchange all kinds of electronic data and information. IT is typically used within the context of business operations as opposed to personal or entertainment technologies. IT is considered to be a subset of information and communications technology (ICT). An information technology system (IT system) is generally an information system, a communications system, or, more specifically speaking, a computer system — including all hardware, software, and peripheral equipment — operated by a limited group of IT users.

 Computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no commonly accepted definition of computational intelligence.

Generally, computational intelligence is a set of nature-inspired computational methodologies and approaches to address complex real-world problems to which mathematical or traditional modeling can be useless for a few reasons: the processes might be too complex for mathematical reasoning, it might contain some uncertainties during the process, or the process might simply be stochastic in nature Indeed, many real-life problems cannot be translated into binary language (unique values of 0 and 1) for computers to process it. Computational Intelligence therefore provides solutions for such problems.

The methods used are close to the human's way of reasoning, i.e. it uses inexact and incomplete knowledge, and it is able to produce control actions in an adaptive way. CI therefore uses a combination of five main complementary techniques. The fuzzy logic which enables the computer to understand natural language, artificial neural networks which permits the system to learn experiential data by operating like the biological one, evolutionary computing, which is based on the process of natural selection, learning theory, and probabilistic methods which helps dealing with uncertainty imprecision.

Biosystems engineering is a field of engineering which integrates engineering science and design with applied biological  and environmental sciences. It represents an evolution of engineering disciplines applied to all living organisms not including biomedical applications. Therefore, biosystems engineering is 'the branch of engineering that applies engineering sciences to solve problems involving biological systems. Typical programmatic areas include: production of bioenergy; development of biosensors; environmental and ecological engineering; controlled-environment agriculture; food processing and food safety; agricultural engineering  (machinery, irrigation, storage), water quality, water quantity, and water recycle.

Agricultural engineering, also known as agricultural and biosystems engineering, is the field of study and application of engineering science and designs principles for agriculture purposes, combining the various disciplines of mechanical, civil, electrical, food science, environmental, software, and  chemical engineering to improve the efficiency of farms and  agribusiness enterprises as well as to ensure sustainability of natural and renewable resources. An agricultural engineer is an engineer with an agriculture background. Agricultural engineers make the engineering designs and plans in an agricultural project, usually in partnership with an agriculturist who is more proficient in farming and agricultural science.

Biological engineering or bioengineering is the application of principles of biology and the tools of engineering  to create usable, tangible, economically-viable products. Biological engineering employs knowledge and expertise from a number of pure and applied sciences, such as mass and heat transfer, kinetics, biocatalysts, biomechanics, bioinformatics, separation and purification processes, bioreactor design, surface science, fluid mechanics, thermodynamics, and polymer science. It is used in the design of medical devices, diagnostic equipment, biocompatible materials, renewable energy, ecological engineering, agricultural engineering, process engineering and catalysis, and other areas that improve the living standards of societies, new medical imaging technology, portable and rapid disease diagnostic devices, prosthetics, biopharmaceuticals, and tissue-engineered organs.

Chemical engineering is a certain type of engineering which deals with the study of operation and  design  of chemical plants as well as methods of improving production. Chemical engineers develop economical commercial processes to convert raw material into useful products. Chemical engineering uses principles of chemistry, physics, mathematics, biology, and economics to efficiently use, produce, design, transport and transform energy and materials. The work of chemical engineers can range from the utilization of nanotechnology and nanomaterial in the laboratory to large-scale industrial processes that convert chemicals, raw materials, living cells, microorganisms, and energy into useful forms and products. Chemical engineers are involved in many aspects of plant design and operation, including safety and hazard assessments, process design and analysis, modeling, control engineering, chemical reaction engineering, nuclear engineering, biological engineering, construction specification, and operating instructions.

Aerospace engineering is the primary field of engineering concerned with the development of aircraft and spacecraft. It has two major and overlapping branches: aeronautical engineering and astronautical engineering. Avionics engineering is similar, but deals with the electronics side of aerospace engineering. Automotive engineering, along with aerospace engineering and naval architecture, is a branch of vehicle engineering, incorporating elements of mechanical, electrical, electronic, software, and safety engineering as applied to the design, manufacture and operation of motorcycles, automobiles, and trucks and their respective engineering subsystems. It also includes modification of vehicles. Manufacturing domain deals with the creation and assembling the whole parts of automobiles is also included in it. The automotive engineering field is research -intensive and involves direct application of mathematical models and formulas. The study of automotive engineering is to design, develop, fabricate, and test vehicles or vehicle components from the concept stage to production stage. Production, development, and manufacturing are the three major functions in this field.

A mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in the natural sciences (such as physics, biology, earth science, chemistry) and engineering disciplines (such as computer science, electrical engineering), as well as in non-physical systems such as the social sciences (such as economics, psychology, sociology, political science). The use of mathematical models to solve problems in business or military operations is a large part of the field of operations research. Mathematical models are also used in music, linguistics, and philosophy (for example, intensively in analytic philosophy).

A model may help to explain a system and to study the effects of different components, and to make predictions about behavior.

Analysis is the branch of mathematics dealing with limits and related theories, such as differentiation, integration,measure, sequences, series, and analytical functions.

These theories are usually studied in the context of real and complex numbers and functions. Analysis evolved from calculus, which involves the elementary concepts and techniques of analysis. Analysis may be distinguished from geometry; however, it can be applied to any space of mathematical objects that has a definition of nearness (a topological space) or specific distances between objects (a metric space).

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data.

Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner imagined data science as a "fourth paradigm" of science and asserted that "everything about science is changing because of the impact of information technology" and the data deluge

1. Cloud Computing - Cloud computing is a network of resources a company can access, and this method of using a digital drive increases the efficiency of organizations. According to Forbes, 83 percent of enterprise workloads will be in the cloud by 2020, which means 2019 will show an increasing trend.

2. Mobile Apps and computing - Mobile phones, tablets, and other devices have taken both the business world and the personal realm by storm. Mobile usage and the number of applications generated have both skyrocketed in recent years. Now, 77 percent of Americans own smartphones — a 35 percent increase since 2011.

3. Big data analytics - Big data is a trend that allows businesses to analyze extensive sets of information to achieve variety in increasing volumes and growth of velocity. Examination of data to understand markets and strategies is becoming more manageable with advances in data analytics programs.
 

4. Automation - Another current trend in the IT industry is automated processes. Automated processes can collect information from vendors, customers, and other documentation. Machine learning can enhance these automated processes for a continually developing system. Automated processes for the future will extend to groceries and other automatic payment methods to streamline the consumer experience.

Multimedia generally refers to images, graphics, texts, and sounds. As an important information carrier, images have features such as intuitive images and rich content. They are an important way of expressing information. Image processing technology has become a major content of multimedia processing technology. Image processing is used to find out various patterns and aspects in images. Pattern Recognition is used for Handwriting analysis, Image recognition, Computer-aided medical diagnosis, and much more

Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intilligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

A subset of machine learning is closely related to computational statitics, which focuses on making predictions using computers; but not all machine learning is statistical learning. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised. Some implementations of machine learning use data and neural networks  in a way that mimics the working of a biological brain. In its application across business problems, machine learning is also referred to as predictive analytics.

Computer security, cybersecurity, or information technology security (IT security) is the protection of computer systems and networks from information disclosure, theft of or damage to their  hardware, software, or electronic data, as well as from the disruption or misdirection of the services they provide. The field is becoming increasingly significant due to the continuously expanding reliance on computer systems, the Internet and wireless network standards such as Bluetooth and Wi-Fi, and due to the growth of "smart" devices, including smartphones, televisions, and the various devices that constitute the Internet of things (IoT). Cybersecurity is also one of the significant challenges in the contemporary world, due to its complexity, both in terms of political usage and technology. Its primary goal is to ensure the system's dependability, integrity, and data privacy.

Different types of Computer Security

• Physical Security. Physical Security – This type of computer security is one of the simplest and easiest to interpret. Network Security. Network Security – Firewall is one of the most important computer security.
• Executable Security.

Educational technology (commonly abbreviated as edutech, or edtech) is the combined use of computer hardware, software, and educational theory and practice to facilitate learning. When referred to with its abbreviation, edtech, it is often referring to the industry of companies that create educational technology. In addition to practical educational experience, educational technology is based on theoretical knowledge from various disciplines such as communication, education, psychology, sociology, artificial intelligence, and computer science. It encompasses several domains including learning theory, computer-based training, online learning, and m-learning, where mobile technologies are used.

The smart network is a collection of connected devices that allows the transfer of data and gathers different kinds of information such as who’s connected. With our expertise, we can detect all available data coming from new or historic devices in your organization and bring it together in one dashboard. This data can then be captured and analyzed. The analysis will automatically discover certain trends and needs (machine learning). The output or result is data presented in the form of one or more API’s. We use these API’s to create apps & dashboards to feed business intelligence systems for process automation. Unifying and transforming this data will unleash new possibilities for your organization. This is what we call The Smart Network. The Smart Network makes your data more accessible. The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers(UIDS) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. A thing in the internet of things can be a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low or any other natural or man-made object that can be assigned an Internet Protocol (IP) address and is able to transfer data over a network. Increasingly, organizations in a variety of industries are using IoT to operate more efficiently, better understand customers to deliver enhanced customer service, improve decision-making and increase the value of the business.

Intelligent systems are technologically advanced machines that perceive and respond to the world around them. Intelligent systems can take many forms, from automated vacuums such as the Roomba to facial recognition programs to Amazon's personalized shopping suggestions. One way that such systems can perceive their environment is through vision. The study of how computers can understand and interpret visual information from static images and video sequences emerged in the late 1950s and early 1960s. It has since grown into a powerful technology that is central to the country's industrial, commercial, and government sectors. The key factors that have contributed to this growth are the exponential growth of processor speed and memory capacity as well as algorithmic advances. The field of intelligent systems also focuses on how these systems interact with human users in changing and dynamic physical and social environments. Early robots possessed little autonomy in making decisions: they assumed a predictable world and perfumed the same action(s) repeatedly under the same conditions. Today, a robot is considered to be an autonomous system that can sense the environment and can act in a physical world in order to achieve some goals.