Basic familiarity with Internet-of-Things (IoT) and/or Blockchain Concepts
Overview
Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, allowing them to communicate with each other and exchange data via network communications, cloud computing, and data capture.
Blockchain is a decentralized database system which stores data in ledgers distributed across many nodes.
Using blockchain technology with IoT allows accessibility and supply of IoT data without the need for central control. This integration opens up a suite of new possibilities and multiple benefits for business organizations.
In this instructor-led, live training (remote), participants will learn how blockchain and IoT can work together as they step through a series of hands-on live-lab exercises.
By the end of this training, participants will be able to:
Understand how blockchain and IoT can work together to provide solutions for their organization
Explore various tools and resources to implement a blockchain-based IoT solution for their organization
Audience
Developers
Managers
Format of the Course
Part lecture, part discussion, exercises and heavy hands-on practice.
Note
To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
Overview of Internet-of-Things (IoT) Technology
Overview of Blockchain Technology
Benefits of Integrating IoT and Blockchain Technology
Overview of the Flowchain Framework: A Case Study on Building a Blockchain for the IoT
Required Architecture for Blockchain and IoT Integration
IoT Device Interoperability and How It Affects the Blockchain Implementation
Applying Blockchain’s Distributed Ledger for IoT
Implementing Blockchain’s Consensus System for IoT
Using the Flowchain SDK to Implement an Iot and Blockchain Solution for Your Organization
Overview of Other IoT and Blockchain Tools and Solutions for Your Organization
The aim of the training is to introduce into the world of the Internet of Things (smart solutions) and blockchain as well as to show the advantages and disadvantages of these technological worlds.
During the training, you will get acquainted with the existing, ready-made tools thanks to which you can implement these smart solutions in your company (contrary to appearances – it does not have to be very difficult) and you will gain the ability to consciously choose the best solutions.
By learning about practical examples of both IoT and Blockchain applications, you will gain unique skills related to smart technologies on the Polish market (e.g. you will learn good practices related to implementation).
You will gain specific knowledge – technical and business – that will allow you to find yourself in the technological market, you will learn practical tips necessary to start a conscious digital transformation and you will gain knowledge that will strengthen your business skills in the smart area.
The training will be especially useful:
for managers who want to know the business benefits of adapting smart solutions,
for people who want to strengthen their knowledge in the field of modern technologies,
for managers who plan to transform the company but do not know where to start and whether it is profitable,
for people who need specifics: how the technology works, what are its advantages and disadvantages, how much can I earn on it, how much are the costs,
for employees who will have to start working with smart solutions in a short time,
for decision-makers to be aware of what and how to talk to sellers about IoT / blockchain
TRAINING DISTINCTIONS
Practical knowledge gained in large-scale projects
Technical and business perspective
Common pitfalls and best practices
Course Outline
What is the Internet of Things?
What stacks / layers / elements does the IoT consist of?
UX layer
Technological layer
Market layer
Business layer
Physical Layer
What’s your business?
What you need to know before a smart transformation
How to conduct an effective assessment and audit of your company?
What to look for when choosing a manufacturer / buying IoT?
What is blockchain technology and where is it used?
Is blockchain for me?
Advantages and disadvantages of blockchain integration – on the example of a specific company
What is the essence of communication and what acronyms do you need to know to freely navigate the world of blockchain / IoT?
dApp,
RPC,
MQTT,
COAP
What is the interoperability problem (why some devices don’t work with others)?
Open IoT solutions
Closed IoT solutions
What are the problems with smart devices and blockchain?
User Experience
Legislation
Ethics
Work methodology
How to use IoT and blockchain (example):
Amazon (order blockchain)
MediLedger network (medical blockchain)
Alibaba / Walmart (nutritional blockchain)
Wien Energie (city blockchain)
Everledger (blockchain of diamonds and precious resources)
Deloitte (order blockchain)
Which supplier to choose (overview of available companies in the USA, Europe and Asia)?
Artificial intelligence (AI) and machine learning are often used interchangeably, but machine learning is a subset of the broader category of AI.
Put in context, artificial intelligence refers to the general ability of computers to emulate human thought and perform tasks in real-world environments, while machine learning refers to the technologies and algorithms that enable systems to identify patterns, make decisions, and improve themselves through experience and data.
Computer programmers and software developers enable computers to analyze data and solve problems — essentially, they create artificial intelligence systems — by applying tools such as:
machine learning
deep learning
neural networks
computer vision
natural language processing
Below is a breakdown of the differences between artificial intelligence and machine learning as well as how they are being applied in organizations large and small today.
What Is Artificial Intelligence?
Artificial Intelligence is the field of developing computers and robots that are capable of behaving in ways that both mimic and go beyond human capabilities. AI-enabled programs can analyze and contextualize data to provide information or automatically trigger actions without human interference.
Today, artificial intelligence is at the heart of many technologies we use, including smart devices and voice assistants such as Siri on Apple devices. Companies are incorporating techniques such as natural language processing and computer vision — the ability for computers to use human language and interpret images — to automate tasks, accelerate decision making, and enable customer conversations with chatbots.
What Is Machine Learning?
Machine learning is a pathway to artificial intelligence. This subcategory of AI uses algorithms to automatically learn insights and recognize patterns from data, applying that learning to make increasingly better decisions.
By studying and experimenting with machine learning, programmers test the limits of how much they can improve the perception, cognition, and action of a computer system.
Deep learning, an advanced method of machine learning, goes a step further. Deep learning models use large neural networks — networks that function like a human brain to logically analyze data — to learn complex patterns and make predictions independent of human input.
How Companies Use AI and Machine Learning
To be successful in nearly any industry, organizations must be able to transform their data into actionable insight. Artificial Intelligence and machine learning give organizations the advantage of automating a variety of manual processes involving data and decision making.
By incorporating AI and machine learning into their systems and strategic plans, leaders can understand and act on data-driven insights with greater speed and efficiency.
AI in the Manufacturing Industry
Efficiency is key to the success of an organization in the manufacturing industry. Artificial intelligence can help manufacturing leaders automate their business processes by applying data analytics and machine learning to applications such as the following:
Identifying equipment errors before malfunctions occur, using the internet of things (IoT), analytics, and machine learning
Using an AI application on a device, located within a factory, that monitors a production machine and predicts when to perform maintenance, so it doesn’t fail mid-shift
Studying HVAC energy consumption patterns and using machine learning to adjust to optimal energy saving and comfort level
AI and Machine Learning in Banking
Data privacy and security are especially critical within the banking industry. Financial services leaders can keep customer data secure while increasing efficiencies using AI and machine learning in several ways:
Using machine learning to detect and prevent fraud and cybersecurity attacks
Integrating biometrics and computer vision to quickly authenticate user identities and process documents
Incorporating smart technologies such as chatbots and voice assistants to automate basic customer service functions
AI Applications in Health Care
The health care field uses huge amounts of data and increasingly relies on informatics and analytics to provide accurate, efficient health services. AI tools can help improve patient outcomes, save time, and even help providers avoid burnout by:
Analyzing data from users’ electronic health records through machine learning to provide clinical decision support and automated insights
Integrating an AI system that predicts the outcomes of hospital visits to prevent readmissions and shorten the time patients are kept in hospitals
Capturing and recording provider-patient interactions in exams or telehealth appointments using natural-language understanding