Engineering Applications Of Artificial Intelligence - Hoshino Shiro

Engineering Applications Of Artificial Intelligence


Engineering Applications Of Artificial Intelligence Rapid technological advancement has increased the need for AI. Science and technology disciplines need “smart” traits.

AI dominates computer science and informatics and can disrupt other fields. AI and electrical engineering intersected to create fields like:

Pattern recognition, robotics, and image processing. AI can work with management to create a decision-support system (Decision Support System). AI and psychology combine to form cognition and psycolinguistics. AI applications include:

Engineering Applications Of Artificial Intelligence


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1.Specialist (Expert system)

The Expert System comprises of expert knowledge and rules that seek and match knowledge until a problem is solved. This knowledge contains facts and reasoning. The 1978 Prospector program for geology uses the knowledge of geology professionals. MYCIN aids in medical diagnosis.


Industry is developing smart robots. This robotic advancement encourages study in visual processing, problem-solving, and robot control. Visual processing helps the robot’s abilities. Theoretical proof relates to problem-solving. This is due to a higher-level, more flexible programming language.


The five senses help humans perceive their surroundings and solve problems. Simple human dilemma. For robots, this work requires environmental sensors. Sensors help robots function. Robotic sensor systems use many sensor approaches. This robot is used for Pattern Recognition (Pattern and recognition). To inspect the direction of an object’s surface, detect its motion, determine its surface, etc.


Intelligence-based problem-solving is studied extensively. This involves how to express the problem, the needed information, and the inference used to achieve the answer.

5.Speech ID

Through speech recognition, humans can speak to computers. With AI in this discipline, a computer can recognize a person’s voice and follow directions.

6.Science, Computer

AI researchers have created several methods to handle complex computer and science challenges. Most of their discoveries are now in computer science and science, not AI. Many components of artificial intelligence are employed in computers and research, making it difficult to separate them. An artificial neural network is used to predict future events. GUI (Graphical User Interface), mouse coordinate computation on the monitor, automatic storage management, dynamic programming, and object orientation programming were invented by AI researchers.


In the health industry, artificial intelligence systems have been deployed, including a genetic algorithm that simulates evolutionary processes and genetic engineering without using “victims.” This approach can be used for DNA matching, which is used to identify people. Expert systems, a branch of AI, are used to diagnose patients’ ailments, making doctors’ jobs easier.


Machines are ubiquitous in industry. In industry, machines are utilized for dangerous and complex activities. Moving heavy objects, cutting iron and steel are examples. Jobs requiring precision and consistency in production have been automated. Humans have poor concentration and stamina. Such conditions endanger workers, producers, and customers. This industry has implemented AI systems. Quality Control, another AI application in industry, uses an image processing system.


In transportation, artificial intelligence is used in many ways, such as an automatic gearshift control system that uses Fuzzy Logic. Decision support systems, which employ GPS as a navigation assistance, can also determine the shortest path. A recent AI system can drive automatically and parallel park without human help.


In telecoms, AI systems are utilized for searching workforce heuristics, scheduling tens of thousands of workers, and deciding salary based on job quality. The system’s AI automates everything.
Rapid game development necessitates new rules. If a player completes a game, the rules will remain the same when that person starts over. Unlike today’s games. The game’s algorithm can remember the player’s playing pattern and employ different rules the next time they play. So the game is more fun and difficult.
AIBO and ASIMO, intelligent robot canines and human-like robots that can interact with humans, are popular AI-powered games. AIBO and ASIMO can interact with humans through voice, thanks to speech recognition.


Music’s evolution is often influenced by the available technology. For example, digital music can capture and replay sounds. AI can create song compositions, sound processing, and music theory. AI in music focuses on sound processing.


In the military, artificial intelligence can be used to simulate war situations, design plans, and calculate the possibility of many methods against battlefield conditions simultaneously.


Prospective pilots are trained using AI-powered flight simulators. This device can simulate dozens of flight factors. Using this simulator to educate potential pilots to fly airplanes reduces expenses and accident risk.


Automobile chassis and body design is more complex now. CFD is used in design and testing. CFD calculates car-design variables. One of them is computing air flow across the car’s thousands of air channels.
These are some real-world AI uses; there are many more. This paper should encourage readers to design AI systems.

AI Robotics

Artificial Intelligence is a robot controller algorithm. The definition of smart varies on which side is viewed.

How does the human mind work? Can non-humans think? (2004) Nobody has answered these two questions properly. Intelligent statements, which are used to test human thinking abilities, have always been a topic of discourse because humans make intelligent judgments. Humans still want to give machines intelligence.

Alan Turing, a British mathematician who began his career in the 1930s, is considered the first pioneer in constructing intelligent machines. He wrote about universal machines in 1937. During World War II, he helped create the German military’s Enigma encrypting machine. Turing created a computer after the war. He created the first chess program for a computer at Manchester University. The Turing Machine still has applications today. His predictions about future computer breakthroughs have been proven. His prediction that machines may conduct dialogues with humans in the 2000s. Turing’s writings don’t use the phrase artificial intelligence, but scholars think he invented it.

Warren McCulloch, a philosopher and medical expert from Columbia University, and Walter Pitts, a young mathematician, initially used the phrase artificial intelligence (AI) in 1943. (Negnevitsky, 2004). They proposed a notion of artificial neural network (ANN) that each neuron can be ON or OFF. Theoretically and empirically, they stimulated this neuron model. The experiment showed that their neural network model is akin to a Turing machine and can solve every computational function.

Although they proved their usefulness, later studies showed that the ON-OFF model of their ANN wasn’t completely appropriate. Neurons’ activity is nonlinear and not ON-OFF. McCulloch was the second person after Turing to persist in AI and intelligent machine engineering. In the 1970s, ANN development slowed. Mid-1980s researchers reexamined this hypothesis.

FL is another AI algorithm as well-known as ANN. If ANN is based on how the human biological brain functions (from within), then FL represents human thinking from the outside. ANN is based on a theoretical biological model, while FL is pragmatic. FL represents human thought logically in language.

In the 1930s, philosopher Lukazewicz produced the first scientific study of human thinking. He suggests mathematical representations of fuzzy logic in human height, old, and hot judgments (tall, old, & hot). Classical logic expands 1 or 0, yes or no, by adding a true value between 0 and 1.
Lotfi Zadeh, a Berkeley professor, published Fuzzy Sets in 1965. Today’s FL and AI fuzzy system research often cites Zadeh’s article. He can explain FL using arithmetic and visuals. Because this FL research focuses on control systems (Zadeh is an electrical engineering professor), the mathematical assertions are primarily created in computer programming.
Genetic algorithm (GA) is another growing AI approach. This GA application is called evolutionary computation (EC) based programming. Holland created the EC (1975). Using Darwin’s theory, he proposed GA-based programming. Nature, like us, can adapt and learn “without being told” Nature blindly selects good chromosomes. As with ANN, GA investigations went dormant before researchers turned to EC theory.
GA involves encoding and evaluation. Davis (1991) described numerous encoding algorithms. No encoding method can tackle all problems equally well, according to literature. Many EC researchers employ bit string approach.
Figure 4.1 illustrates AI in robotic control. AI-controlled robot closed-loop
AI is used to intelligently retrieve the controller’s dynamic attributes. P, I, D or combination controls cannot adapt to system dynamic changes during operation since P, I, and D parameters only offer the best control effect under the same system conditions initially tuned. Later, it is argued that this classical control is not yet intelligent because it cannot handle nonlinearity qualities or dynamic changes in the robot system itself, load, or external disturbances.
There are various research on how to make P, I, and D dynamic, such as adaptive control, but we will only cover constructing intelligent control systems using ANN, FL, EC, or GA.
Show the AI utilized as a robot controller. AI can be used to identify robotic system models, environmental or disturbance models, robotic task models such as trajectory planning, etc. In this situation, AI is used indirectly in the controller (indirect).


Robot manipulator displays robot movement. This mechanical system uses frames and joints to produce controlled movement. Industry uses only two types:
R=rotation about an axis
Prismatic joint (P) is axis shift
With the two types of joints mentioned, a manipulator can have two, three, or even six degrees of freedom, or independent directions in which a gripper/tool can move. The robot’s construction can be described by its coordinate axes:
Three-axis Cartesian robot
Robot with 2 linear and 1 rotating axes
1 linear axis, 2 rotation axes: spherical robot
Three-axis robot


Robot has three linear axes (prismatic). Each axis can move to x-y-z. This robot’s easy position control and sturdy structure are advantages.

  1. Robot Cylinder
    A cylindrical robot has a rotatable Horizontal Arm and Vertical Arm. Cylindrical robots move faster than Cartesian robots’ end effectors, however the speed depends on the load’s moment of inertia.
  2. RobotSphere
    This robot has a Rotary Base, Elevated Pivot, and Telescopic Arm like a tank. This robot is more flexible.

Robot Articulated

Three Revolute Joints connect this robot’s arms. Elbow joint links forearm to upper arm. Upper Arm and Base are connected by Shoulder Joint. Robot’s structure.

SCARA robot (Selective Compliance Assembly Robot Arm)
Robot Assembly uses Cartesian, cylindrical, or spherical coordinates. Some applications just require vertical motion, such as a robot that mounts components on a PCB. These robots have two-articulated arms with linear and rolling wrists.

Robot performances include:
Resolution is the smallest manipulator motion change the control system can order.
Accuracy is variation from known input.
Repeatability is a robot’s ability to restore its end effector to its initial position.
Robots are more flexible than traditional machines. The movement pattern is also programmed.

Drive Robot
The mover allows the robot to move and lift the end effector’s load.

Common propulsion includes:

  1. Hydraulics
  2. Air-powered
    Electric drive:
    Stepper motors

Robot Cartesia

This robot has 3 linear axes (prismatic). All axes can shift to the x-y-z area. This robot has intuitive position control and a sturdy frame.
Cylindrical robot
Cylindrical robots have a horizontal arm and a vertical arm that may revolve on the base. Compared to Cartesian robots, cylindrical robots move faster than the end effector, however the speed relies on the load’s moment of inertia.
Spherical robot
Similar to a tank, this robot has a Rotary Base, Elevated Pivot, and Telescopic Arm. This type of robot is flexible.

  1. Robotic Arm

It has three arms joined by two Revolute Joints. The Elbow joins the Forearm and Upper Arm. Shoulder Joint links Upper Arm to Base. The robot’s design.

  1. SCARAbot (Selective Compliance Assembly Robot Arm)
    Robot Assembly coordinates might be Cartesian, cylindrical, or spherical. In other applications, only a vertical axis of motion is needed, such as a PCB assembly robot. Such robots have two-articulated arms with linear and rolling wrist movements.

A few robot performances to know are:
The control system’s resolution is the smallest change in manipulator motion it can command.
The amount of variance from a known input is accuracy.
Repeatability is the robot’s ability to restore the end effector to its initial position.
When compared to conventional machineries, robots are more flexible. Programmers plan the movement pattern.

Robot Drive
The robot needs a mover so it can move and elevate the end effector.

Propulsion types include:
Hydraulic drive
Pneumatic drive

  1. Electric drives:
    DC Stepper Motor

Optical sensors detect objects using light. Usually LDR, photo diode, photo transistor.
Bimetallic plate, thermistor, NTC, PYC detect heat and convert it to an electrical signal.
Touchscreen e. Useful for detecting touch. Piezo, matrix, and pneumatic sensors.
vision sensor Vision sensor detects, identifies orientation and objects.

Configuring digital control systems
Digital control systems are more popular than analog due to various advantages. Noise-resistant, programmable digital control signals are noise-resistant.

v Open loop, where end effector output doesn’t affect following data processing.
Closed loop where end effector position influences data processing and decision making.
v End-effector movement and robot End effector position can be programmed two ways in robot movement.
v Point-to-point control In this situation, the end effectors’ starting and finishing positions are known.
v CPC End-effector path is apparent. a paint-spraying robot

  1. Spyke
  1. FSS
    Fuzzy controllers are fuzzy logic applications. Fuzzy applications use fuzzy controllers, fuzzy categorization, and fuzzy diagnostics (fuzzy diagnosis). This paper describes fuzzy technology’s challenges and the differences between fuzzy controllers, fuzzy classification, and fuzzy diagnostics.
  2. Japanese Humanoid Robot
    Japanese robot tech is infinite. Japan is back with a fresh breakthrough after a dancing-walking robot. Humanoid robots serve tea and wash glasses in Japan.
    Japan is developing robots that learn from mistakes. Professor Tomomasa Sato continues humanoid robot research. Professor installs two robots in a living room in one scenario. Professor Tomomasa Sato sat down and turned on a lamp. Tomomasa Sato summoned HRP-2W. The robot has an apron and gloves. The robot answers Professor Sato’s questions.
    Professor Sato’s HRP-2W does his bidding. HRP-2W poured the test from a plastic bottle into a glass. Professor Sato only saw the two-legged robot after that. Humanoid robot helps humans.
  3. Robot Soccer

Two German businesses unveiled a new robot for bomb disposal and reconnaissance. World Cup security innovations.
The organizing committee continues to ensure World Cup safety. Also, top-notch event security. Bomb-proof robots. Two German businesses, Robowatch and Diehl, have launched a new reconnaissance/bomb disposal robot.
The 38-kilogram machine will aid fire brigades, police, and special forces in a terrorist attack.
The robot can tour a room, discover bombs, and communicate data to security forces. Asendro is a small robot that looks like a miniature tank. Asendro can crawl over wooden floors, pivot, and spread camera-equipped arms.
Asendro can climb stairs and cut fuses. The robot’s cameras can broadcast images 2 kilometers away for 2 to 4 hours. Robowatch and Diehl say the 55,000-200,000 euro robot is tiny, nimble, faster, and more versatile than similar models.
Robowatch previously made a World Cup robot. Ofro Detect was launched in Berlin’s Olympia stadium 10 months ago. At least 20 robots will protect the stadium perimeter and parking lot in Berlin on 9 July 2006.

  • Japan’s robotics industry is booming. Assistant and doctor-replacement robots. Dance-bots are here.
    University of Tokyo scientists have created a dance-following robot. Dancing robots exist.
    Shin’ichiro Nakaoka and University of Tokyo colleagues created a dancing HRP-2 robot. Motion capture technology lets a robot follow a person’s dance moves.
    The robot’s talent is unquestionable, yet there are issues. Programming a robot to follow difficult maneuvers while maintaining balance.
    According to Vnunet and detikINET, the robot will soon dance ‘Swan Lake’ Scientists say the robot can’t keep up with the ballet, which jumps and leaves its legs in the air.
    The robot has danced ‘Aizu-Bandaisan,’ a traditional Japanese dance with more body movements than legs.

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