Internet of Things (IoT) PDF

Introduction to Industry Revolution 4.0 ≈ ≈ ≈ ≈ Internet of Things (IoT) IoT What is Internet of Things? You can put any text here You can put any text here De nition 1: Internet of Things (IoT) is de ned as a system of interrelated computing devices, mechanical and digital m...

Introduction to Industry Revolution 4.0 ≈ ≈ ≈ ≈ Internet of Things (IoT) IoT What is Internet of Things? You can put any text here You can put any text here De nition 1: Internet of Things (IoT) is de ned as a system of interrelated computing devices, mechanical and digital machines, objects (Things) that are able to transfer data over a network (e. g, Internet) without requiring human-to-human or human-to-computer interaction. De nition 2: The Internet of Things (IoT) is an interconnected web of sensor-enabled devices that communicate between each other and a series of intermediary collection points. De nition 3: The Internet of Things (IoT) is a system of capturing, transmitting, managing and analyzing data in order to monitor events, identify relationships, predict outcomes and improve performances. De nition 4: The IoT can be de ned as a network in which Cyber-Physical Systems (CPSs) cooperate with each other through unique addressing schemas. The Internet of Things (IoT), sometimes referred to as the Internet of Objects, will change everything—including ourselves. This may seem like a bold statement, but consider the impact the Internet already has had on education, communication, business, science, government, and humanity. Clearly, the Internet is one of the most important and powerful creations in all of human history. Chapter 2 Page 2 IoT The Internet of Things (IoT) A Cyber-Physical System (CPS) still sounds familiar to us today. Machines can exchange data and, in a lot of applications, can sense the changes in the environment around them. Fire alarms are a good example of that. The Internet of Things, is thought to be what truly has initiated Industry 4.0. The Internet of Things is what enables objects and machines such as mobile phones and sensors to “communicate” with each other as well as human beings to work out solutions. The integration of such technology allows objects to work and solve problems independently. Of course, this is not entirely true as human beings are also allowed to intervene. Chapter 2 Page 5 IoT IoT and Economy 90% of cars will be connected to the Internet since sensors are being manufactured in vast amounts to provide better facilities. Manufacturers and industrialists in every sector are having systems that monitor, track progress, and automate many complex processes in manufacturing. Many companies consider the IoT devices as a clear value add for their business. In 2021, companies invested $158 Billion in IoT since many companies consider the IoT devices as a clear value add for their business. It is expected that by 2030, $14 trillion industrial IoT devices will be added to the global economy that will help the global economy to increase after a weak productivity growth. So, Why Now? 1. It became simpler for IoT hardware and software to connect all types of devices to the Internet. 2. Currently, IoT network capabilities have been expanded and a large-scale data analytics tools have been produced to manage and analyze data from IoT devices. 3. The cloud growth has signi cantly contributed in making the modern IoT possible, since its considered cheaper and store information in the correct time. Cloud structure simpli es the process of of oading storage and computing tasks from IoT devices to cloud servers; this makes the IoT devices cheaper, leaner and meaner. Chapter 2 Page 7 IoT How Does IoT Work? Collecting Data Sensor User Interface Gateways 1. Sensors 2. Connectivity 3. Data Processing 4. User Interface Connectivity Technically, 4 main components: 1. Sensors: Cloud Data Processing The main task of sensors is to collect data from the surrounding environment. The sensor is part of the front end of the IoT system. They are directly or indirectly connected to the IoT network after signal conversion and processing. Sensors are different, and different IoT applications require different types of sensors. Examples: Temperature sensor. Light sensor. Moisture sensor. Motion sensor. Image sensor (camera). Usage Example: By using moisture sensors in agriculture, information could be automatically generated about the soil moisture to ensure that crops get exactly the right amount of water. Sensors Chapter 2 Page 13 Devices that detect and respond to some type of input from the physical environment. Produces an output signal for the purpose of sensing of a physical phenomenon. Report & Noti cation Components of IoT IoT 2. Connectivity: Data collected from sensors needs to be sent to the cloud to be processed there. It needs a way to get there! Sensors are being connected to the cloud through several connectivity methods. Choosing the best connectivity option in the IoT system is important, since each method differs with its power consumption, range covered (distance), data transfer rate (speed) and overall ef ciency. Cellular: Is the technology that connects physical objects to the Internet using the same cellular network currently used by smartphones. This technology can connect IoT devices using existing mobile networks. Thus, it eliminates the need to invest and develop a separate dedicated network infrastructure just for IoT devices. Wired (Ethernet): Is the traditional network technology for connecting computers to each other and to the Internet via cables. Within an IoT system, Ethernet can be used to connect stationary or xed IoT devices. For example, the Ethernet cables are used for connecting the computers with the routers to provide the Internet connectivity. Satellite: As the name implies, this form of connectivity uses satellites to connect sensors/devices to the cloud. Today’s communications satellites are much more robust and featured incredible coverage. It has an advantage in remote areas that other communication types such as cellular or Wi-Fi cannot reach, and in places that have underdeveloped infrastructure or none at all, such as the middle of the ocean. Short-Range Wireless (Wi-Fi and Bluetooth): Are technologies that access or provides network connectivity using radio waves without the use of wires. Wi-Fi range is up to 100 meters. Bluetooth range is up to 10 meters. Disadvantage: Consume high power. LPWAN Low-Power Wide-Area Network: As its name implies, it allow for low power consumption over a wide area (long range). Because of its high range with low power consumption, it is a recommended technology for smart cities, smart home and many smart devices for industrial automation and IoT. Chapter 2 Page 14 IoT 3. Data Processing: Once the data gets to the cloud, software performs some kind of processing on it. Examples: The IoT technology has the ability to ensure that the temperature reading on devices such as AC or heaters are suitable. (using temperature sensors). It can also recognize objects such as intruders in your house using computer vision on videos. (using camera sensors). However, when the temperature is too high or if there is an intruder in your house the user interaction is required. 4. User Interface: User interfaces are the visible, tangible part of the IoT system which can be accessible by users. IoT user interface can alert the user by sending email, text, or noti cation in bad conditions. IoT system could also perform some actions automatically rather than notifying the person. For example, going back to the farming example, after collecting the soil moisture information, irrigation system could automatically turn on based on the soil moisture level. Chapter 2 Page 15 IoT Advantages of IoT Better Time Management: Data Collection/Monitoring: We can look up the latest news on our phones during our daily commute, or check a blog about our favorite pastime, purchase an item in an online shop, we can do almost all the things from the palm of our hands. Eventually, we end up with much more time for us. It helps us Know the precise quantity of supplies or the air quality in your home. You can know what to get from the grocery while you are out, without having to check on your own. It can also provide more data that could not have previously been possible to collect easily. Automation and Control: Access to Information: You can easily gain the required information in real-time, from (almost) any location you are at. You only need a smart device and internet connection. Due to physical objects being connected and controlled Examples: control in the workings. Without human interference, the machines are digitally and centrally with wireless technology structure, there is a huge amount of automation and communicating with each other providing faster and timely output operations. We use Google Maps to see our location, instead of asking a person in real life. Cost-effective (Saving Money): Booking tickets is simpler than ever. Information is also easily accessible, even from the latest scienti c research, or business analysis. It is only a click away. By IoT technology you are able to track the quality and viability of things at home while IoT mainly aids to be helpful to people in their daily life by making their devices communicate with each other in an ef cient manner thereby saving and conserving energy and cost. Allowing the data to be communicated and shared between devices and then translating it into our required way, makes our systems ef cient. knowing the i.e., expiration date of products. Communication (Speedy Operations): Much of available data enables us to complete multiple tasks with amazing speed. For example, IoT makes automation effortless. Smart industries automate repetitive tasks, thus allowing employees to invest their time and effort into more challenging things. Chapter 2 Page 16 IoT Disadvantages of IoT Complexity of Operation: IoT is a diverse and complex network. Any failure or bugs in the software or hardware will have serious consequences. Even power failure can cause a lot of inconvenience. Privacy/Security: Privacy and security are big concerns that must be taken into consideration regarding IoT. With all of this IoT data being transmitted, the risk of losing privacy increases. Safety: The software can be hacked and your personal information misused. For example, your medicine prescription can be changed or your account details on a bank can get hacked. Compatibility: As devices from various manufacturers will be interconnected to each other, the issue of compatibility in tagging and monitoring increases. This disadvantage can be overcome if manufacturers make a common standard, but there is still a possibility that the technical problems may still persist. Chapter 2 Page 17 IoT IoT Challenges and Solutions Challenges Solutions Sensing Complex Environment Sensing is essential. Without sensing, there would be no IoT. The entire IoT system starts with sensors, these devices or nodes would measure anything and everything to create data that is sent to other nodes or to the cloud. Variety and Options of Connectivity Simplifying the connectivity options is critical. Once the sensor data is collected by low-powered nodes, it must be sent somewhere. In most cases, it goes to a gateway, which is a midpoint between the Internet/cloud or other nodes in an IoT system. Low power and resource consumption are vital. For the IoT to connect virtually every aspect of our lives, require large excessive amount energy, low power is paramount. Power is Critical Security is vital IoT is Complex (Nature of IoT) Cloud is important Security is crucial for widespread adoption. With more devices becoming ‘smart,’ it will enable more potential security gap access points. We must nd ways to build the most advanced hardware security mechanisms while keeping them small, low cost, low power but strong access control and authorization. IoT needs to be made easy for inexperienced developers. Many of the connected devices within the IoT are nodes containing microcontrollers, sensors, wireless devices and actuators that collect data, all gathering power through energy as carried out. Managing cloud connectivity is key. Once the data passes through a gateway, in most cases it heads to the cloud where that data can be analyzed, reviewed and put into action. The value of IoT comes from data running on cloud services, yet another point of complexity in the IoT world. Chapter 2 Page 18 IoT Terms Related to IoT Internet of Services (IoS): Nowadays, every electronic device is more likely to be connected to either another device, or to the internet. Smart phones, tablets, laptops, TVs or even watches are becoming more and more interconnected. With the huge development and diversity in electronic and smart devices, more and more complexities are added. IoS means, everything that is needed to use software applications is available as a service on the Internet, including the software itself, the tools to develop the software. It aims at creating a wrapper that simpli es all connected devices to make the most out of them by simplifying the process. It is the customer’s gateway to the manufacturer. Smart Factory: De ned as: a factory where Cyber-Physical Systems communicate over the IoT and assist people and machines in the execution of their tasks. Smart factories are a key feature of Industry 4.0 It can be fed with soft information regarding the object being manufactured such as drawings and models. Adopts a so called Calm-system, which is a system that is able to deal with both the physical world as well as the virtual world. Calm systems are called “background systems” because they operate behind the scene. They are aware of the surrounding environment and the objects around it. IoS Everything that is needed to use software applications is available as a service on the Internet, including the software itself, the tools to develop the software. Calm System is a system that is able to deal with both the physical world as well as the virtual world. Chapter 2 Page 19 Arti cial Intelligence Chapter 3 Arti cial Intelligence AI De nitions You can put an text here AI: Arti cial Intelligence is the simulation of human intelligence processes by machines, that include learning, reasoning, self-correction and solving problems. It is an important part in technology industries, and this eld is improving more and more over the years. Involves the development of complex algorithms - Machines that simulate intelligent incorporated to the computer infrastructure behaviour. which can perform tasks like: - Collection of technologies that allow the - Visual awareness computers to think like humans. - Speech recognition - Science of making intelligent machines. - Language translation - Decision making Chapter 3 Page 2 Arti cial Intelligence Motivation Arti cial intelligent machines help us to deal with complex tasks that the human couldn’t do. That’s why we need arti cial intelligent in our life. Tasks that can the intelligent machines do: Reasoning and solving problems: using algorithms step by step to solve big and hard problems. Planning: using algorithms to set goals that will be achieved. Learning: unsupervised learning when the machines doesn’t need person to control. Social intelligent: the machines that can understand the human emotions and understand what's going on. You can put an text here Chapter 3 Page 3 Arti cial Intelligence Types of AI AI systems can be divided (based on capabilities) into three types: 1. Narrow/Weak AI 2. General AI 3. Super AI https://medium.com/@selecticalinfotech/understanding-arti cial-intelligence-3bdcde2993c3 AI systems can be divided (based on functionalities) into four types: 1. Reactive Machines AI 2. Limited Memory AI 3. Theory of Mind AI 4. Self-Aware AI Chapter 3 Page 7 Arti cial Intelligence AI systems can be divided (based on capabilities) into three types: 1. Narrow/Weak AI: Not intelligent enough, a machine that handle one particular task. Examples: -Video games (chess). -Virtual assistants such as Apple's Siri, Microsoft Cortana, Amazon's Alexa. You ask the virtual assistant a question, it answers it for you. Uses natural language and voice queries to answer questions. 2. General AI: A machine that handle many tasks, considered to be human-like. Tend to be more complex, they are programmed to handle situations in which they may require problem solving without having a human intervene. Examples: -Self-driving cars and robots in hospital operating rooms. -Google Alpha Go it has the ability to train itself purely through self-play. 3. Super AI: Is a level of Intelligence of systems at which machines could surpass human intelligence, and can perform any task better than human with cognitive properties. Some key characteristics include the ability to think, reason, solve the puzzle, make judgments, plan, learn, and communicate by its own. Still a hypothetical concept of AI. Development of such systems in real is still world challenging task. Chapter 3 Page 8 Arti cial Intelligence AI systems can be divided (based on functionalities) into four types: 1. Reactive Machines AI: Are the fundamental types of AI systems. Are quite reactive and they are not able to use previous experiences to advise current decisions or to con gure memories. Example: IBM’s chess-playing computer Deep Blue that defeated chess grandmaster Garry Kasparov is a reactive machine that sees the chessboard pieces and reacts to them. 2. Limited Memory AI: Train themselves from previous data and can make decisions for a speci c period of time, but they cannot add it to a library of their experiences. The memory of such systems is short-lived. Example: Is mostly used in self-driving cars. They detect the movements of vehicles around them constantly. The static data such as lane marks, tra c lights and any curves in the road will be added to the AI machine. This helps autonomous cars to avoid getting hit by nearby vehicles. 3. Theory of Mind AI: Is a very advanced technology. In terms of psychology, the theory of mind represents the understanding of people and things in the world that can have emotions which alter their own behavior. Still, this type of AI has not been developed completely in the society. But research shows that the way to make advancements is to begin by developing robots that are able to identify eye and face movements and act according to the looks. Chapter 3 Page 9 Arti cial Intelligence Example 1: One real-world example of the theory of mind AI is Kismet. Kismet can mimic human emotions and recognize them, but can’t follow glimpses or carry attention to humans. Example 2: Another example is Sophia from Hanson Robotics. Cameras are used in Sophia's eyes, with the help of computer algorithms, allow her to see. She can sustain eye contacts, recognize individuals, and follow faces. 4. Self-Aware AI: Is a supplement of the theory of mind AI. Only exists hypothetically. Is not developed yet, but when it happens, it can con gure representations about themselves. It means particular devices are tuned into cues from humans like attention spans, emotions and also able to display self-driven reactions. https://www.pngwing.com/en/free-png-xxmuo Chapter 3 Page 10 Arti cial Intelligence How Does AI work? In order for the machines to simulate intelligent behaviour, they have to achieve human-level performance in all cognitive tasks. These cognitive tasks include: Natural language processing: For communication with humans. Knowledge representation: To store information e ectively & e ciently. Automated reasoning: To retrieve & answer questions using the stored information. Machine learning: To adapt to new circumstances. Computer vision: To perceive objects (seeing). Robotics: To move objects (acting). Chapter 3 Page 12 Arti cial Intelligence Components of AI Models/Algorithms: Machine Learning. Deep Learning. Neural Networks. Programming languages for building models: https://appen.com/blog/ai-vs-deep-learning-vs-machinelearning-everything-youve-ever-wanted-to-know/ C/C++ Python Java TensorFlow (platform) Software/Hardware for training and running models: Parallel processing tools (like Spark). Cloud data storage and computing platforms. Graphics Processing Units (GPUs). GPUs Cloud data storage Machine learning : deep learning: GPU computing is the use of a GPU (graphics processing unit) as a co-processor to accelerate CPUs for generalpurpose scienti c and engineering computing. used to store data the ability of devices to learn without programming. is what is based on deep neural networks. Chapter 3 Page 13 Arti cial Intelligence Advantages of AI Error Reduction: Decreasing mistakes. Di cult Exploration: Handle di cult tasks in harsh areas i.e., can be put to mining and fuel exploration process. Virtual Assistants: In daily Application. We have our lady Siri or Cortana to help us out. Repetitive Jobs: Speed of computations i.e., faster than humans, multitasking. No Breaks: Don’t need any breaks and refreshments. Absence of Emotions: Makes the AI system think logically. Chapter 3 Page 15 Arti cial Intelligence Disadvantages of AI Risk of loss of important data. Can’t think out of box: AI systems cannot make the judgment of right or wrong as machines do not have any emotions and moral values. Can’t be improved with experience. Replacement of human’s job leads to increase unemployment. No Original Creativity: Human creativity and imagination is di cult to be replicate. Addiction: Humans can become too dependent i.e., we depend on machines to form everyday tasks. High Costs. Chapter 3 Page 16 Arti cial Intelligence Challenges of AI 1. Building trust, Higher expectations. 2. Software malfunction: Software or hardware crashes. 3. Technologies and expertise are too expensive. 4. Removing human responsibility. AI Development Areas Chapter 3 Page 17 Arti cial Intelligence Interesting to watch Not mandatory You can put an text here Chapter 3 Page 26 Robotics Chapter 4 Industry Revolution 4.0 Robotics What is Robotics? What is Robot? De nitions: A reprogrammable multifunctional manipulator designed to move material, parts, tools or specialized devices through various programmed motions for the performance of a variety of tasks. — Robot Institute of America 1- A machine that can interact with and respond to its surrounding environment. 2- Machines that simulate intelligent behaviour. 3- Collection of technologies that allow the computers to think for themselves. 4-Science of making intelligent machines. Chapter 4 Robotics De nitions: Characterized by three central capabilities: the ability to Sense, the ability to Act, and the ability to Plan. Robotic systems can be de ned as interconnected, interactive, cognitive and physical tools that are able to: Perceive the environment using sensors. Reason about events. Make plans using algorithms implemented in computer programs. Perform actions enabled by actuators. Sense Act Plan Chapter 4 Robotics We are here Collaborative Robot: Industry 4.0 Robots that work in direct cooperation with humans inside a de ned workspace, in both, industrial and non-industrial environment. Chapter 4 Robotics Robots Components Sensors: Are measuring instruments (devices) which measures quantities such as position, velocity, force, torque, proximity, temperature, etc. Used to collect information about the internal state of the robot or to communicate with the outside environment. Robots are often equipped with external sensory devices such as a vision system (cameras), touch and tactile sensors etc, which help to communicate with the surrounding environment. Controller: The controller functions in a manner analogous to the human (intelligent) brain. It is a computer system (software) that receives data from the sensors, then controls the motions of the actuator and coordinates these motions with the sensory feedback information. With the help of this controller, the robot is able to carry out the assigned tasks. Actuators: Are the muscles of the manipulators. Three types depending on the source of energy: Electric, Hydraulic or Pneumatic. Common types of actuators are: servomotors, stepper motors, pneumatic cylinders. Manipulator: The robot consists of what is called a manipulator having several joints and links, Just like the human arm. Locomotion Device: A device that enables a robot to move or navigate in its environment. This can include Wheels, Tracks, Legs, and propellers. Endeffector: It is expected to perform tasks normally performed by the palm and nger arrangements of the human arm. Chapter 4 Robotics Robo Law (Isacc Asimov) 1. A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2. A robot must obey orders given it by human beings except where such orders would con ict with the First Law. 3. A robot must protect its own existence as long as such protection does not con ict with the First or Second Law. Chapter 4 Robotics Robotics Applications Example 1 Autonomous Mobile Platforms: Speci cations: Used in internal transport: No hardwired infrastructure Work around people Free staff Improve customer services Obstacle avoidance Robotics as-a-service business model Health care Food & Beverage Industry (F&B) Construction Tourism Logistics Retail Security Manufacturing Education Entertainment https://simplexity.news/en/how-can-autonomous-mobile-robots-streamline-supply-chains/ Chapter 4 Robotics Robots Guide: Chapter 4 Robotics Robotics Advantages 1. Better cost effective and faster to use over humans: Maximize capital intensive equipment in multiple work shifts. Automation, less susceptible to work stoppages, Accident reduction, Quality improvement. 2. Designed to collaborate with humans in jobs: Easier and simpler for robots to do some jobs. Sometimes the only possible way to accomplish some tasks and reduce hazardous exposure. Robots can explore inside gas tanks, inside volcanos, travel the surface of Mars or other places too dangerous for humans to go where extreme temperatures or contaminated environments exist. 3. Greater exibility, re-programmability. 4. Some are Lightweight and can be transported. 5. Improvement of working environment. 6. Increase the economic growth of the country. Chapter 4 Robotics Chapter 4 Robotics Robotics Disadvantages 1. Replacement of human labor…. Greater unemployment. 2. Signi cant re-training costs for both unemployed and users of new technology. 3. Can store large amounts of data but the storage, access, retrieval is not as effective as the human brain. 4. Hidden costs because of the associated technology that must be purchased and integrated into a functioning cell. Typically, a functioning cell will cost 3 -10 times the cost of the robot. 5. Cost much money in maintenance & repair. The programs need to be updated to suit the changing requirements. Chapter 4 Robotics Robotics Challenges 10 Biggest Challenges in Robotics: Chapter 4 Robotics 1. New materials & fabrication methods: Tremendous work is already being done with arti cial muscles, soft robotics, and assembly strategies that will help develop the next generation of autonomous robots that are multifunctional and power-ef cient. Materials that couple sensing, actuation, computation, and communication must be developed. These advances could lead to robots with features such as body support, weight reduction, impact protection, morphological computation, and mobility. 2. Creating bio-inspired robots: To create robots that perform more like the ef cient systems found in nature. Development in this area have remained largely unchanged for 30 years – a battery to match metabolic conversion, muscle-like actuators, self-healing material, autonomy in any environment, human-like perception, and computation and reasoning. https://hum3d.com/robot/ Chapter 4 Robotics Boston Dynamics 3. AI that can reason: We still have a long way to go to replicate and exceed all the facets of intelligence that we see in humans. AI that can learn complex tasks on its own with minimal training data is also critical. 4. Better power sources: Robots, typically, are energy-inef cient. Improving the battery life is a major issue, especially for drones and mobile robots. Work is certainly being done to make the components of a robot more power ef cient. Robots that need to operate wirelessly in unstructured environments will eventually extract energy from light, vibrations, and mechanical movement. Work is being done to improve battery technology beyond the nickel-metal hydride and lithium ion options currently available. Chapter 4 Robotics 5. Communication in robot swarms (groups): Robot swarms are tricky because they need to sense not only the environment, but also each robot in the swarm. They need to communicate with the other robots, too, while acting independently. https://www.sky labs.com/project-ideas/latest-projects-based-on-swarmrobotics 6. Navigating unmapped environments: Just look at self-driving cars, for example. Mapping and navigation techniques will continue to evolve, but future robots need to be able to operate in environments that are unmapped and poorly understood. For navigation unmapped environments, the grand challenge is to handle failures and being able to adapt, learn, and recover. The robots need to have signi cant levels of autonomy leading to complex self-monitoring, self-recon guration, and repair. 7. Brain Computer Interfaces: Brain Computer Interfaces (BCIs) enable some device and machines to be controlled by your mind. BCIs could be quite useful in augmenting human abilities in the future, but developing the technology for wider adoption is the challenge. The equipment for sensing brain signals is expensive and cumbersome, and the data processing can be tricky. There’s also a long period of training, calibration and learning. https://www.techslang.com/how-does-a-braincomputer-interface-work/ Chapter 4 Robotics 8. Social robots for long-term engagement: Humans are, generally, skillful at interpreting social behavior. Robots are not. The three biggest challenges of building social robots that truly interact with humans are modeling social dynamics, learning social and moral norms, and building a robotic theory of mind. Today’s social robots have been designed for short interactions, which isn’t how human relationships work. Social robots must expand from moment-to-moment engagements to long-term relationships. 9. Medical robotics with more autonomy: Medical robotics represents one of the fastest growing sectors. But the challenge is building reliable systems with greater levels of autonomy. A long-term challenge is to enable one surgeon to supervise a set of robots that can perform routine procedure steps autonomously and only call on surgeons during critical, patient-speci c steps. 10. Ethics: Five ethical problems: 1. Sensitive tasks that should require human supervision could be delegated entirely to robots. 2. Humans will no longer take responsibility for failures. 3. Unemployment and de-skilling of the workforce. 4. AI could erode human freedom. 5. Using AI in unethical ways. Chapter 4 Robotics Fourth Industrial Revolution Course Materials Reference Book: Schwab, K. with Davis, N. (2017). The Fourth Industrial Revolution. Currency. Publisher: Currency (2017) ISBN: 9781524758868 Course Materials Preparation: Lecture notes, videos, class discussions, student activities, case studies, and project guidelines for the Fourth Industrial Revolution course were prepared and edited by Dr. Khaled Hamdan ([email protected]), Dr. Nabeel Al-Qirim ([email protected]). PDF le Content Contributor: Dr. Asmaa Hosni: [email protected] Reviewed by: Mr. Marwan Fayyad ([email protected]) Graphic Designed by: Basheir Al-Rei Klaus Schwab (2017). The Fourth Industrial Revolution. Publisher: Currency (January 3, 2017), ISBN-10: 9781524758868; ISBN-13: 978-1524758868; ASIN: 1524758868 Mitchell, L., & Groenewald, G. (2010). The pre-industrial cape in the twentyrst century. South African Historical Journal, 62(3), 435–443.