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Internet of Things (IoT), Machine to Machine (M2M) and Big Data Analytics Certification Course


Location: Online

Duration: 2 Days

From-To:  2016-07-28 to 2016-07-29

Product Description

Course Overview

The emerging paradigm of Internet of Things (IoT) has created both new smart services and economic opportunities for industries, businesses and communities. The IoT technology is revolutionizing the smart healthcare sector, energy sector, smart cities, smart transportation systems, smart security sectors, and e-governance systems by taking connectivity, data mining and communication to the next level. It is predicted that by 2020, about 7.6 billion people will be interconnected via 50 billion devices which is a good indication of worldwide diffusion of things and data connected to the internet via IoT technology. According to business analysts, IoT technology will lead to an economic growth of 4.6 trillion dollars in the Global Public Sector by 2020.

Due to unlimited opportunities for IoT entrepreneurships and businesses, a huge number of small and medium sized business owners and entrepreneurs have already welcomed the gold rush for IOT worldwide. Also due to the emergence of enormous open source IoT and M2M platforms, the development of IOT systems is quite cost effective and worthy to start the IOT businesses. The resilience to manage sizable production of IOT products has immensely encouraged the electronics product owners to integrate their devices and products with mobile applications and networks.

This course covers major aspects of IoT, Machine to Machine (M2M) Communication and Big Data Analytic techniques for IoT. This course will provide a solid base for Information & Communication Technology (ICT) engineers, researchers, marketing managers, IoT software application designers, embedded design engineers, and entrepreneurs to learn about state-of-the-art IoT applications for smart cities, smart healthcare sector, smart grid, smart transportation systems, smart security systems and e-governance.  In this course, we intend to guide the IoT enthusiasts/entrepreneurs with latest IoT technologies and business trends of the emerging IoT industry so that they will not only be able to establish smart Iot based business ventures but will also gain the knowledge to design IoT industrial applications using sophisticated cloud based IoT platforms and data analytics tools.

Key Benefits for Participants

This course will provide the following key benefits to the attendees:

  • Learn about sophisticated software and hardware tools for designing IoT industrial applications using cloud based IoT platforms which can potentially generate massive revenue streams.
  • Enhance their knowledge about big data analytic techniques for smart IoT applications
  • Brainstorm potential valuable business ideas linked with IoT based smart cities, smart homes, smart gird, smart health and smart transportation applications.
  • Extensive understanding of IoT technologies, protocols, standards and cloud based IoT platforms
  • Gain detailed knowledge about state-of-the-art IoT commercial products
  • Extensive understanding of mobile app platform for IoT, machine learning for IoT and Analytic engine for IoT
  • Gain comprehensive knowledge about marketing terms for Internet of Things based industrial products and applications.
  • Understand key ideas related to e-governance, public safety and disaster management

Course Objectives

This course has the following major objectives:

  • Provide comprehensive knowledge about IoT ecosphere, IoT applications, IoT standards, architecture, protocols and cloud based IoT platforms.
  • Deliver insights about IoT technology market trends, IoT businesses and deployment of IoT applications.
  • Detailed insight to Bluetooth Smart Technology, Sensor networks, ZigBee, Low Power WiFi, RFID, IEEE 802.15.4, IEEE 802.15.4e, 802.11ah and Relay Access Point (AP)
  • Discuss Mobile app platform for IoT, machine learning for IoT and Analytic engine for IoT
  • Detailed insights to Machine to Machine (M2M) communication
  • Comprehensive knowledge about Big Data analytic tools such as Hadoop.
  • Case studies of cloud based IoT platforms from various leading technology companies for smart healthcare, smart transportation, smart buildings, smart grid and e-governance.

Course Content

Why IoT is so important -Overview

  • IoT history and evolution
  • Case Studies from Nest, CISCO and top industries
  • IoT adaptation rate in North American & and how they are aligning their future business model and operation around IoT
  • Broad Scale Application Area
  • Smart House and Smart City
  • New devices: wearables, vehicles, homes, drones and robots
  • New interfaces: augmented reality, virtual reality, telepresence and haptic interfaces
  • Smart Home Healthcare
  • Business Rule Generation for IoT
  • Standards and requirements 
  • IoT enabling technologies 
  • 3 layered architecture of Big Data — Physical (Sensors), Communication, and Data Intelligence
  • Functionalities and structure


IoT Architecture and Technologies 

  • Key components: Hardware and firmware 
  • Device drivers and  application software 
  • Networking protocol structure 
  • Semantic Web 3.0 Standard for M2M and IoT 
  • Cloud connectivity 
  • ZigBee and RFID,Target Wake Time (TWT) 
  • SuperSpeed USB Inter-Chip (SSIC) 
  • Bluetooth Smart Technology 
  • UniPro, SPMI, BIF 
  • Bluetooth Smart Technology 
  • Relay Access Point (AP) 
  • Sensor networks

IoT Communication and Networking 

  • Serial communication 
  • Power consumption and optimization 
  • Wired connectivity, Ethernet/GigE 
  • Grouping of stations and Augmented Reality 

IoT Deployment and Management 

  • Mobile integration & Convergence  
  • Value chain and Business models 
  • Lifecycle solution management 
  • Real-time response and delay

New IoT products- Product requirement document  for IoT 

  • State of the present art and review of existing technology in the market place
  • Suggestion for new features and technologies based on market analysis and patent issues
  • Detailed technical specs for new products- System, software, hardware, mechanical, installation etc.
  • Packaging and documentation requirements
  • Servicing and customer support requirements
  • High level design (HLD) for understanding of product concept
  • Release plan for phase wise introduction of the new features
  • Skill set for the development team and proposed project plan -cost & duration
  • Target manufacturing price

Mobile app platform for IoT

  • Protocol stack of Mobile app for IoT
  • Mobile to server integration –what are the factors to look out
  • What are the intelligent layer that can be introduced at Mobile app level ?
  • iBeacon in IoS
  • Window Azure
  • Linkafy Mobile platform for IoT
  • Axeda
  • Xively

Machine learning for intelligent IoT

  • Introduction to Machine learning
  • Learning classification techniques
  • Bayesian Prediction-preparing training file
  • Support Vector Machine
  • Image and video analytic for IoT
  • Fraud and alert analytic through IoT
  • Bio –metric ID integration with IoT
  • Real Time Analytic/Stream Analytic
  • Scalability issues of IoT and machine learning
  • What are the architectural implementation of Machine learning for IoT

Analytic Engine for IoT

  • Insight analytic
  • Visualization analytic
  • Structured predictive analytic
  • Unstructured predictive analytic
  • Recommendation Engine
  • Pattern detection
  • Rule/Scenario discovery — failure, fraud, optimization
  • Root cause discovery

Security in IoT implementation 

  • Why security is absolutely essential for IoT
  • Mechanism of security breach in IOT layer
  • Privacy enhancing technologies
  • Fundamental of network security
  • Encryption and cryptography implementation for IoT data
  • Security standard for available platform
  • European legislation for security in IoT platform
  • Secure booting
  • Device authentication
  • Firewalling and IPS
  • Updates and patches

Database implementation for IoT : Cloud based IoT platforms

  • SQL vs NoSQL-Which one is good for your IoT application
  • Open sourced vs. Licensed Database
  • Available M2M cloud platform
  • Axeda
  • Xively
  • Omega
  • NovoTech
  • Ayla
  • Libellium
  • CISCO M2M platform
  • AT &T M2M platform
  • Google M2M platform

Few common IoT systems

  • Home automation
  • Energy optimization in Home
  • Automotive-OBD
  • IoT-Lock
  • Smart Smoke alarm
  • BAC ( Blood alcohol monitoring ) for drug abusers under probation
  • Pet cam for Pet lovers
  • Wearable IOT
  • Mobile parking ticketing system
  • Indoor location tracking in Retail store
  • Home health care
  • Smart Sports Watch

Big Data for IoT 

  • 4Vs of Big Data 
  • Why Big Data is important in IoT 
  • Big Data vs legacy data in IoT 
  • Hadoop for IoT-when and why? 
  • Storage techniques and Distributed database
  • Distributed database
  • Parallel computing basics for IoT

Big Data Analytics Techniques 

  • Introduction to R (statistical tool) 
  • Data exploration and visualization 
  • Cluster analysis and Decision Trees 
  • End to End Analytics

Hadoop Data Management

  • Hadoop Installation 
  • Introduction to HDFS and HBASE 
  • Hive Data Management

Cloud based IoT platforms 

  • Case studies of available M2M cloud platform 
  • Libellium, Ayla, Axeda 
  • CISCO M2M platform 
  • AT &T M2M platform

Common IoT systems

  • Home automation 
  • Energy optimization in Home 
  • Automotive-OBD 
  • IoT-Lock 
  • Smart Smoke alarm 
  • BAC ( Blood alcohol monitoring ) for drug abusers under probation 
  • Pet cam for Pet lovers 
  • Wearable IOT 
  • Mobile parking ticketing system 
  • Indoor location tracking in Retail store 
  • Home health care 
  • Smart Sports Watch

IoT Business Model – The Changing Customer Relationship

  • The new intimate relationship
  • Creating Values with IoT Businesses
  • The IoT business model continuum
  • Business model choices and examples
  • The business model as the feature
  • Risk Management
  • Sources of liability
  • The Information Security Plan
  • Privacy best practices

The IoT Business Plan – Strategic analysis and planning for your IoT business.

  • Analysis methodology for customer and desired outcome
  • Shifting boundaries of competition
  • First mover advantages
  • Barriers to entry
  • Department by department analysis
  • Human resource considerations
  • IOT Strategy
  • Summary of operator strategies
  • IOT Integration into Business Processes
  • Aligning IOT to Business & Product Strategy
  • IOT Solutions
  • Trends and analyses

.         IOT Application and Case studies

  • Data managers
  • Utilities
  • Municipalities
  • Mobile App Integration Services
  • Enterprise Mobility and cloud services
  • Social Media vs. Smart Mobile
  • Social Networking
  • Value chain and Business models
  • Cases studies of Scenario Transportation, ITS and Convergence of IT and Automation
  • Smart factory of the future
  • Smart Cities
  • Smart Environment
  • eHealth

Delivery Options

  • Online
  • Onsite

Who Should Attend

  • Technical managers and engineers who are specifically interested planning, designing, building, managing or  operating IoT technology and applications
  • Engineers who require in depth knowledge about cloud based IoT platforms and big data analysis.
  • Investors and IoT entrepreneurs
  • Managers and Engineers whose company is venturing into IoT space
  • Business Analysts & Investors


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