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.
The aim of the training is to explain what the 5G network is and what impact it has on smart technologies. I want to show you both the advantages and disadvantages of these technological relationships (5G / IoT) and show you the directions of development of the network, which - from the very beginning - was dedicated to the smart world.
The aim of the training is to explain what are - and what are not - Smart solutions (Internet of Things, AI, Blockchain, Virtual Reality, Metaverse) and to show the advantages and disadvantages of these technological worlds.
Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more complex as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, realizing that information is a strategic asset, and government needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve data-driven organizations to successfully accomplish mission, they are laying the groundwork to correlate dependencies across events, people, processes, and information.
High-value government solutions will be created from a mashup of the most disruptive technologies:
Mobile devices and applications
Cloud services
Social business technologies and networking
Big Data and analytics
IDC predicts that by 2020, the IT industry will reach $5 trillion, approximately $1.7 trillion larger than today, and that 80% of the industry's growth will be driven by these 3rd Platform technologies. In the long term, these technologies will be key tools for dealing with the complexity of increased digital information. Big Data is one of the intelligent industry solutions and allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured.
But accomplishing these feats takes far more than simply accumulating massive quantities of data.“Making sense of thesevolumes of Big Datarequires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information,” Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog.
The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it.
The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can get it when they want it and how they need it. Backing up massive quantities of data heightens the challenge.
Analyzing the data effectively is another major challenge. Many agencies employ commercial tools that enable them to sift through the mountains of data, spotting trends that can help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives think Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.).
Custom-developed Big Data tools also are allowing agencies to address the need to analyze their data. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers find a link that can alert doctors to aortic aneurysms before they strike. It’s also used for more mundane tasks, such as sifting through résumés to connect job candidates with hiring managers.
Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering.
For manufacturing professional, most critical aspect is to understand the advancement in the area of Industrial Internet of things, which includes predictive and preventative maintenance, condition based monitoring of the machines, production optimization, energy optimization, supply-chain optimization and uptime of manufacturing utilities etc.
Summary
An advanced training program covering the current state of the art in Internet of Things in Smart Factories.
Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help manufacturing managerial professionals
Live demo of model IIoT applications for smart factories
Target Audience
Managers responsible for business and operational processes within their respective manufacturing organizations and want to know how to harness IoT to make their systems and processes more efficient.
Duration 3 Days ( 8 hours / day)
Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined.
In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.
However the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.
Industrial IoT, or IIoT for manufacturing has been widely in use since 2014 and since then a large number of IIoT innovations have taken place. This course will introduce all the important aspects of innovations in Industrial IoT area.
This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business.
Course Objective
Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in smart factories for manufacturing sectors.
Studies of business and technology of some of the common IIoT platform like Siemens MindSphere and Azure IoT.
Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT, Mindsphere IIoT cloud in addition to other minor IoT clouds
Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc
Security issues and security solutions for IIoT
Mobile/Desktop/Web app- for registration, data acquisition and control –
M2M Wireless protocols for IoT- WiFi, LoPan, BLE, Ethernet, Ethercat, PLC : When and where to use which one?
Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane
Internet of Things (IoT)是一種網絡基礎設施,可以無線連接物理對象和軟件應用程序,允許它們相互通信並通過網絡通信,雲計算和數據捕獲交換數據。 在這個以講師為主導的現場培訓中,參與者將學習物聯網的基礎知識,因為他們逐步使用Raspberry Pi創建物聯網傳感器系統。 在培訓結束時,參與者將能夠:
In this instructor-led, live training in 台灣, participants will learn how to maximize the performance of Nginx as they set up, configure, monitor and troubleshoot Nginx for handling various forms of HTTP / TCP traffic. Topics covered include how to configure the most important parameters in Nginx, the OS and a virtual machine to gain maximum value out of Nginx.
Internet of Things (IoT) is an emerging technology domain that connects physical objects and software applications wirelessly for remote sensing and control. Augmented Reality (AR) is a technology that improves user experience by blending virtual computer-generated elements with the physical real-world environment. AR allows businesses to provide users with a real-time and real-world view of information. These are two technologies that have been seeing a rapidly growing adoption rate across multiple industries.
In this instructor-led, live training, participants will learn the fundamentals of IoT and AR and apply these learnings to their organizations' operations and strategies.
By the end of this training, participants will be able to:
Understand the fundamentals of IoT and AR
Learn how IoT and AR technologies work
Understand how IoT and AR technologies can be applied to their business' strategy
Make informed business decisions about IoT and AR
Audience
Managers
Entrepreneurs
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.
Internet of Things (IoT)是一種網絡基礎設施,可以無線連接物理對象和軟件應用程序,允許它們相互通信並通過網絡通信,雲計算和數據捕獲交換數據。 Java是一種通用語言,以“一次編寫,隨處運行”而聞名。由於其便攜性和效率,建議將Java用於物聯網。 在這個以講師為主導的現場培訓中,參與者將學習如何使用Java編寫物聯網解決方案。 在培訓結束時,參與者將能夠:
安裝和配置用於使用Java編程物聯網系統的工具和框架(Eclipse Open IoT Stack)
Internet of Things (IoT)是一種網絡基礎設施,可以無線連接物理對象和軟件應用程序,允許它們相互通信並通過網絡通信,雲計算和數據捕獲交換數據。 C是一種推薦用於物聯網的通用編程語言,因為它具有普遍性和低級編程優勢。 在這個以講師為主導的現場培訓中,參與者將學習如何用C編寫物聯網解決方案。 在培訓結束時,參與者將能夠:
Internet of Things (IoT)是一種網絡基礎設施,可以無線連接物理對象和軟件應用程序,允許它們相互通信並通過網絡通信,雲計算和數據捕獲交換數據。 Python是一種推薦用於物聯網的高級編程語言,因為它具有清晰的語法和大量的社區支持。 在這個以講師為主導的現場培訓中,參與者將學習如何使用Python編寫物聯網解決方案。 在培訓結束時,參與者將能夠:
Internet of Things (IoT)是一種網絡基礎設施,可以無線連接物理對象和軟件應用程序,允許它們相互通信並通過網絡通信,雲計算和數據捕獲交換數據。 Java Script是一種流行的面向對象編程語言,因其無處不在的性質而被推薦用於物聯網。 在這個以講師為主導的現場培訓中,參與者將學習如何使用Java Script編寫物聯網解決方案,同時逐步開發物聯網系統儀表板。 在培訓結束時,參與者將能夠:
Internet of Things (IoT)是一種網絡基礎設施,可以無線連接物理對象和軟件應用程序,允許它們相互通信並通過網絡通信,雲計算和數據捕獲交換數據。 Azure是一套全面的雲服務,提供物聯網套件,包括預先配置的解決方案,可幫助開發人員加速物聯網項目的開發。 在這個由講師指導的實時培訓中,參與者將學習如何使用Azure開發物聯網應用程序。 在培訓結束時,參與者將能夠:
了解物聯網架構的基礎知識
安裝和配置Azure IoT Suite
了解在編程物聯網系統中使用Azure的好處
實施各種Azure IoT服務(IoT Hub,功能,流分析, Power BI ,Cosmos DB,DocumentDB,IoT設備Management )
Internet of Things (IoT)是一種網絡基礎設施,可以無線連接物理對象和軟件應用程序,允許它們相互通信並通過網絡通信,雲計算和數據捕獲交換數據。 Blockchain是一個分散的數據庫系統,它將數據存儲在分佈在許多節點上的分類賬中。 將區塊鏈技術與物聯網結合使用,可以實現物聯網數據的可訪問性和供應,而無需集中控制。這種集成為商業組織開闢了一系列新的可能性和多種好處。 在這個以講師為主導的現場培訓(遠程)中,參與者將學習區塊鍊和物聯網如何在他們通過一系列動手實踐的實踐練習中一起工作。 在培訓結束時,參與者將能夠:
Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 12 B by 2019 and 100B+ by 2025.
In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.
The underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However, what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.
Over the last three years, engineering in IoT has seen massive changes primarily driven by Microsoft, Google and Amazon. These large behemoths have invested billions of dollars to develop IoT platforms that are more easy to manage and secure. Also, IoT edge has gained a lot of momentum in both research and deployment as only means for practical IoT implementation. 5G is also promising to transform the business of IoT. This has led to an unprecedented large swath of new areas of research funding in IoT.
However, Govt adaptation of IoT is slow due to security concerns at various levels. One of the major issue is, disagreement among different large IoT vendors on the matter of security. Microsoft Azure, Amazon AWS have pushed forward with its own security standards. Whereas NIST is placing a more comprehensive one. OWASP model of 10 layers of IoT security did some impact but overall failed to get much ground due to non-adoption from major IoT platform like Azure or Google.
Course Objective
Give introduction of all the technology stacks of IoT
Drawing the layers of vulnerability at each stack and between the stack
Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 12 B by 2019 and 100B+ by 2025.
In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet.
The underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However, what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT.
As DLT become more understood in recent years and its capability to solve enterprise business use cases become evident, technologist have been exploring Distributed Ledger Technology (DLT) (such as Blockchain or IOTA) to solve use cases that have been daunting industries for years. Unlike existing technologies, one of the key features of DLT is its unparalleled capability to provide, traceability, accountability and immutable records that can be accessed at any point in time. One application area of interest in DLT is securing heterogenous networks. The technology has to be secured, immutable and offer real time transaction.
Course Objective
Give introduction of migration of centralized cloud based IoT to decentralized edge based IoT (with example of smart car charging, P2P energy grids)
Drawing the layers of vulnerability at each stack and between the stack
Learning about the DLT (Blockchain and DAG – direct acyclic graph) in IoT initiatives in IBM, Samsung, IOTA foundation and some other large players.
Connected device is disrupting many business, power utility being no exception. Power Utility companies are essentially faced with four challenges from growth of IoT
Machines, Controllers, HMI, SCADA systems are increasingly becoming cloud connected by the vendors who promise to offer more analytics and insight via their data for predictive and preventative maintenance. But quarantine policy of the critical assets means these new IoT features from the Machine/Controller Vendors can’t be utilized by the Power Companies
With the ever decreasing cost of solar and wind power microgrid, Utility companies will soon see declining revenue from power generation. To compensate for the lost revenue of power production, the company has to aggressively pursue new areas of revenues such as Energy management of Home as a service, Energy storage as a service, offering grid service for EV charging, grid service for P2P energy trading between the homes, home and microgrid, microgrid to microgrid, microgrid to battery, home to battery etc. All of this need to be facilitated via smart metering, smart grid and smart & secured transactions only possible via DLT ( distributed ledger technology) like IOTA. Also Utilities are exploring to offer some of the smart city services to the city authority
For critical infrastructure like dams, ICOLD ( International Committee Of Large Dams) want to see Structural Health Monitoring (SHM) of the dams real time so that any impending danger of collapse of the dam or rock or tunnel can be informed in advance to vacate the people who may be affected
Also a new emerging area of revenue will be EV charging in Parking-How IoT can facilitate smart charging and smart parking?
Over the last three years, engineering in IoT has seen massive changes primarily driven by Microsoft, Google and Amazon. These large behemoths have invested billions of dollars to develop IoT platforms that are more easy to manage and secure. Also IoT edge has gained a lot of momentum in both research and deployment as only means for practical IoT implementation. 5G is promising to transform the business of IoT. This has led to an unprecedented large swath of new areas of research funding in IoT. This is why right now for any practicing engineer it is absolutely essential to understand IoT platforms developed for major players like AWS, Google and Specially Microsoft.
However, neither of the above platform offers exhaustive or a totally comprehensive solution for a scalable IoT. Just for Smart Metering to be deployed to millions of homes, additional technology to secure the smart meter, radio networks, IoT management technology and many other additional secured services will be required. Strategy, Price and Security of any IoT deployment must be optimal and acceptable. Given so much of interdisciplinary knowledge, it is almost difficult for any company to deploy a team which can meet all the requirements.
This course is a modest attempt to educate the key decision makers, developers, security experts about what are the challenges, risks and practical way to deploy IoT for their next generation power utility business.
In addition, with scalable deployment, managing IoT services for thousands of sensors and connections are emerging as a separate engineering subject of research. This area , formally known as managed IoT services is experiencing rapid growth as challenges for scalable IoT are much bigger than building them. This includes security of over the top firmware/software update, managing calibration of the sensors and systems, auto-diagnosis of any connection issue, narrowing down on root cause of API failures, tracking the hardware and service health of the distributed system etc.
Course objectives
Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in Power Utility Companies - Smart Metering, Smart Car, SHM ( structural health monitoring), Power Quality Diagnosis and Smart Contracts. Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and control plane applications.
IoT technology Stacks: Devices, Gateways, Edge, Edge Cloud, Public Cloud, IoT databases, Web & Mobile Applications for IoT, Centralized vs Decentralized IoT
IoT ecosystem for Business, third party device management, risk management of entire IoT ecosystem
M2M Wireless protocols for IoT- WiFi, SigFox,LORA, LPWAN, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one
Fundamentals of IoT Gateways- Risks, Management and Ecosystem
Mobile/Desktop/Web app - for registration, data acquisition and control –Available M2M data acquisition platform for IoT—AWS IoT, Azure IoT, Google IoT
Security issues and solutions for IoT- Review of security of all the technology stacks
Enterprise IoT platforms such as Microsoft Azure IoT suites, AWS IoT, Google IoT , Siemens MindSphere
Smart Metering, Open Smart Grid Protocols (OSGP), ANSI C 2.18 Protocols , NIST Standard for HAN ( Home Area Network), Home Plug Powerline Alliance , Security Standard for Smart Meter- IEC 62056
Distributed Ledge Technology ( DLT) such as Blockchain, HyperLedger and DAG ( Direct Acyclic Graph) for smart contract, P2P transactions, smart car charging
IoT for critical infrastructure like DAM, Transformer, Sub-station, High Tension Wire
This instructor-led, live training in 台灣 (online or onsite) is aimed at developers and programmers who wish to install, configure, and manage the Kaa platform to build IoT applications.
By the end of this training, participants will be able to build, develop, manage, and implement IoT applications for smart devices and machines using Kaa.
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