Internet of Things (IoT) Courses Online

About

The Internet of Things (IoT) involves the internet-connected devices we use to perform the processes and services that support our way of life. Another component set to help IoT succeed is cloud computing, which acts as a sort of front end. Cloud computing is an increasingly popular service that offers several advantages to IoT, and is based on the concept of allowing users to perform normal computing tasks using services delivered entirely over the internet.[1][2][3] A worker may need to finish a major project that must be submitted to a manager, but perhaps they encounter problems with memory or space constraints on their computing device. Memory and space constraints can be minimized if an application is instead hosted on the internet. The worker can use a cloud computing service to finish their work because the data is managed remotely by a server. Another example: you have a problem with your mobile device and you need to reformat it or reinstall the operating system. You can use Google Photos to upload your photos to internet-based storage. After the reformat or reinstall, you can then either move the photos back to you device or you can view the photos on your device from the internet when you want.

Contents

• Introduction to cloud computing
• Concept
• Characteristics
• Service and deployment
  • Service models
  • Deployment models

About

The Internet of Things (IoT) is an integrated part of the future internet where physical and virtual things that can interact with objects, animals, or people receive unique identifiers. It also has self-configuring capabilities that are able to transfer data over an internet network without need of interaction.[1] The Internet of Things has been in development for decades, but the concept wasn't named until 1999. The first internet appliance, for example, was a Coke machine at Carnegie Melon University in the early 1980s. The programmers could connect to the machine over the internet and were able to check the status of the machine and determine whether or not there would be a cold drink awaiting them, should they decide to make the trip down to the machine.[1] Nowadays, IoT is applied to many systems that can benefit humans, including machine-to-machine systems, cloud systems, human-to-machine systems, and big data systems. "Big data" is a buzzword used to describe the massive volume of both structured and unstructured data that accumulates across many enterprises today, data the remains difficult to process and manage by traditional database and software techniques.[2] Big data is important and has the potential to help companies make faster and more intelligent decisions while also improving company operations.[3] A simple example of big data in use: retailers can track user web clicks to identify behavioral trends that improve campaigns, pricing, and product stocking.

Contents

• Introduction to big data
• Internet of Things and big data
• Big data operations
• Applications of big data
  • Manufacturing
  • Internet of Things
  • Information security
• Advantages and disadvantages of big data
  • Advantages
  • Disadvantages

About

MQTT (originally an acronym for MQ Telemetry Transport) is an open  Organization for the Advancement of Structured Information Standards (OASIS) and ISO standard (ISO/IEC 20922) lightweight, a publish-subscribe network protocol that transports messages between devices. The protocol usually runs over TCP/IP; however, any network protocol that provides ordered, lossless, bi-directional connections can support MQTT. It is designed for connections with remote locations where a "small code footprint" is required or the network bandwidth is limited.

Content

• Overview
• MQTT broker
• Message types
  • Connect
  • Disconnect
  • Publish
• MQTT v5.0
• Quality of service (QoS)
• Real-world applications

About

Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.

Deep-learning architectures such as deep neural networks, deep belief networks, repeated neural networks and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, language process, audio recognition, social network filtering, artificial intelligence, bioinformatics, drug style, medical image analysis, material examination and board game programs, wherever they need created results akin to and in some cases surpassing human knowledgeable performance.

Content

• Introduction to Deep Learning
• Various neural network architectures in IoT
• Predictive power in IoT solutions
• Predictive maintenance
• Frameworks for image recognition and the indoor location
• Speech recognition in IoT applications
• Security for IoT solutions

About

Welcome to the course Internet of everything. The web of everything (IoE) is the organized association of individuals, cycle, information and things. As more individuals, information and things come on the web, we need to create abilities and innovative cycles to bridle the immense measures of data being produced by all these associated individuals and things. 

The Internet of everything, and all the associated things on the web, are staying put. There is impressive publicity in the media – great and bad – that makes it hard to work out if this connectedness is something worth being thankful for or something awful. Or then again, would it be a good idea for us to be unconcerned about the web of everything? What is obvious from media inclusion is that the web of everything has just been related with worldwide security alarms, while for some, it is the cool innovative must-have. 

The objective of this course is to acquaint you with basic ideas and advances that empower the IoE and assist you with understanding its advantages just as likely dangers. The course presents basic material and is proposed to be effortlessly finished by anybody with an essential enthusiasm for PC innovations. By finishing this course, you won't turn into an IoE master, however you will end up being an educated person...

About

Content is an eminent example of the features that contributed to the success of wireless Internet. Mobile platforms such as the Snapdragon™ processor have special hardware and software capabilities to make acquisition, processing and rendering of multimedia content efficient and cost-effective.

Content

• Principles of Video and Audio codecs
• File formats and codec settings for quality and bandwidth management
• Develop basic media player applications

About

MQTT (Message Queuing Telemetry Transport) is an open OASIS and ISO standard (ISO/IEC 20922) lightweight, a publish-subscribe network protocol that transports messages between devices. The protocol usually runs over TCP/IP; however, any network protocol that provides ordered, lossless, bi-directional connections can support MQTT. It is designed for connections with remote locations where a "small code footprint" is required or the network bandwidth is limited.

Content

• Overview
• MQTT broker
• Message types
  • Connect
  • Disconnect
  • Publish
• MQTT v5.0
• Quality of service (QoS)
• Real-world applications

About

industrial internet of things is interconnected sensors, instruments, and other devices networked together with computers' industrial applications, including manufacturing and energy management. This connectivity allows for data collection, exchange, and analysis, potentially facilitating improvements in productivity and efficiency as well as other economic benefits. The IIoT is an evolution of a distributed control system (DCS) that allows for a higher degree of automation by using cloud computing to refine and optimize the process controls.

Content

• History
• Standards and Frameworks
• Application and Industries
  • Automotive industry
  • Oil and gas industry
  • Agriculture industry
• Security

About

The Internet of things (IoT) describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet.

Things have evolved due to the convergence of multiple technologies, real-time analytics, machine learning, commodity sensors, and embedded systems. Traditional fields of embedded systems, wireless sensor networks, control systems, automation (including home and building automation), and others all contribute to enabling the Internet of things. In the consumer market, IoT technology is most synonymous with products pertaining to the concept of the "smart home", including devices and appliances (such as lighting fixtures, thermostats, home security systems and cameras, and other home appliances) that support one or more common ecosystems, and can be controlled via devices associated with that ecosystem, such as smartphones and smart speakers. IoT can also be used in healthcare systems.

There are a number of serious concerns about dangers in the growth of IoT, especially in the areas of privacy and security, and consequently, industry and governmental moves to address these concerns have begun including the development of international standards.

Content

• Introduction
• Applications
  • Consumer applications
  • Organizational applications
  • Industrial applications
  • Infrastructure applications
  • Military applications
  • Product digitization
• Trends and characteristics
  • Intelligence
  • Architecture
  • Complexity
  • Size considerations
  • Space considerations
  • A solution to "basket of remotes"
• Enabling technologies for IoT
  • Addressability
  • Application Layer
  • Short-range wireless
  • Medium-range wireless
  • Long-range wireless
  • Wired
  • Standards and standards organizations
• Politics and civic engagement
• Government regulation on IoT
• Criticism, problems, and controversies
  • Platform fragmentation
  • Privacy, autonomy, and control
  • Data storage
  • Security
  • Safety
  • Design
  • Environmental sustainability impact
  • Intentional obsolescence of devices
  • Confusing terminology
• IoT adoption barriers
  • Lack of interoperability and unclear value propositions
  • Privacy and security concerns
  • Traditional governance structure
  • Business planning and project management