IBM is a Niche Player according to 2020 Magic Quadrant of Gartner.
The IBM Watson IoT platform is primarily delivered as a managed collection of cloud services in the IBM Cloud
The industrial base for Watson IoT centers on manufacturing and transportation enterprises. Common use cases are predictive maintenance and asset monitoring. The industrial deployments are cloud-centric, with minimal examples of completely on-premises implementations. The Watson IoT platform is best-suited for cloud-centric deployments across a range of use cases spanning asset monitoring and process improvement.
Strengths
Watson IoT provides customers with a wide and deep set of functionalities to build IIoT-enabled business solutions.
Watson IoT analytics provides customers an easy-to-use graphical interface.
Cautions
Watson IoT has a more limited set of capabilities for edge deployments in factories and plants.
Deployment and ongoing management much more challenging for users.
Cognitive IoT is the use of cognitive computing technologies in combination with data generated by connected devices and the actions those devices can perform. http://www.ibmbigdatahub.com/blog/what-cognitive-iot?
Compute
Network
Storage
Data and analytics
Watson
Integration
DevOps
Security
Application services
Mobile
Internet of Things
Bluemix and Internet of Things
Experience a fully managed, cloud-hosted service designed to simplify and derive value from your IoT devices. See how companies are using Watson Internet of Things to transform their business from the inside out.
How it all fits together
Connect your device, send data to our cloud, set up and manage your devices, and use APIs to connect apps to your device data.
Start with your device – whether it’s a sensor, gateway, or something else – and let us help you connect it with one of our recipes.
MQTT and HTTP
Your device data is always secure when you connect to the cloud using open, lightweight MQTT messaging protocol or HTTP.
IBM Watson IoT Platform
The hub of the IBM IoT approach – set up and manage your connected devices so your apps can access live and historical data.
REST and real-time APIs
Use our secure APIs to connect your apps with data from your devices.
Your application and analytics
Create applications within IBM Bluemix, another cloud, or your own servers to interpret data.
How much will it (IBM Watson IoT Platform) cost?
The IBM Watson IoT Platform charges on three metrics.
Devices
The average number of devices you connect over the month. You get 20 free devices a month with each plan.
Data
The amount of data that devices exchange with the IBM Watson IoT Platform and associated applications.
You get free 100 MB data traffic a month with each plan (equivalent to 50,000 messages)
*assuming an average message size of 200 bytes
Siemens MindSphere® provides you with the required transparency and data-driven insights needed to make the right decisions and strengthen your digitalization strategy.
Siemens MindSphere enables you to drive your business success by understanding the things that matter. You need to connect all of your machines and aggregate the relevant data into one system so you can perform concise and powerful analysis, optimize your processes, reduce costs, and accelerate your time to market. With the help of a strong and secure IoT solution that offers scalability, global IoT connectivity, and an easy application deployment process, you can make reasoned decisions. With MindSphere being built on Mendix, you can quickly create custom, low-code applications to accelerate the time-to-value for your industry investments.
The Internet of Things (IoT)
What's more: With the numerous applications, services, and closed-loop digital twin capabilities of Mindsphere, you are able to reduce costs and accelerate your time to market by connecting your assets and harnessing the wealth of your data.
For more detailed information on development capabilities, visit mindsphere.io
Industrial IoT as a Service: Enable global access of cloud-based applications and solutions that quickly scale, expand, and integrate based on business needs.
Industrial IoT Solutions Fast: Access industrial-based applications to get immediate value from the wealth of data collected from the Internet of Things.
Industrial IoT Data in Context: Access new insights by combining and analyzing IoT data with information from PLM, CRM, ERP, SCM, SLM, and MES systems.
Integrated Edge to Cloud: Perform advanced streaming analytics at the edge or in the cloud to fast-track insights for critical and non-critical processes.
Closed-Loop Digital Twin: Collect live performance data from production lines as well as from connected products to create a fully-functional, closed-loop digital twin.
Gain insights that improve efficiency and profitability
Take advantage of apps and solutions that solve real problems
https://siemens.mindsphere.io/en
Connect and Monitor
Connect to get the key data from your assets and systems
The Connect and Monitor packaged solution helps manufacturers connect critical assets, gain complete operational transparency and take action to optimize asset performance and health. Benefit from the pre-packaged solution and smoothly start your MindSphere® journey.
The MindSphere Connect and Monitor Solution Package include the following:
MindAccess IoT Value Plan
Connect your entire fleet to MindSphere, securely send and store IoT data, and visualize and analyze connected assets with MindAccess IoT Value Plan.
Visual Flow Creator
Build your work flow to create rules, define key performance indicators (KPIs) and trigger actions, such as email notifications, if defined threshold values are exceeded.
Video
MindSphere : How to create dashboards in less than 10 minutes with Visual Flow Creator.
Create customized, advanced data visualizations and dashboards from complex data sets with this browser-based solution that utilizes Tableau®.
Key Services
Implementation: Implementation services involve connecting your data sources to MindSphere, including data collection, agent onboarding and data model configuration.
Support: Ongoing support and consultation to guide you through your digitalization journey and help you get the most out of your MindSphere solution. Receive support to create rules/KPIs in Visual Flow Creator and to develop dashboards utilizing Visual Explorer.
Modern analytic tools to better understand and improve your processes
The Analyze and Predict packaged solution gives manufacturers operational transparency to optimize maintenance and to predict and prevent unplanned asset downtime. Benefit from the pre-packaged solution to analyze your data and unleash the value of MindSphere®.
The MindSphere Analyze and Predict Solution Package includes the following:
MindConnect Integration
Combine existing databases, enterprise systems and cloud data sources with data collected on the shop floor to enable full contextual analysis of critical assets.
Predictive Learning
Build models using machine learning techniques to help predict future asset performance and optimize product quality.
Visual Flow Creator
Build your work flow to create rules, define key performance indicators (KPIs) and trigger actions, such as email notifications, if defined threshold values are exceeded.
Visual Explorer
Create customized, advanced data visualizations and dashboards from complex data sets with this browser-based solution that utilizes Tableau®.
Key Services
Implementation: Implementation services involve connecting your data sources to MindSphere, including data collection, agent onboarding and data model configuration.
Basic Enablement: Benefit from the experience of our experts to utilize and maximize the benefits of the MindSphere components.
Success Management: Ongoing support and consultation to guide you through your digitalization journey and help you get the most out of your MindSphere solution.
Configuration: Receive support to create rules/KPIs in Visual Flow Creator and to develop dashboards utilizing Visual Explorer.
Analytics consulting: Monthly review of the configurations of Visual Flow Creator and Visual Explorer to improve gained data insights.
Data Science consulting: Development and ongoing review of built models using the MindSphere Predictive Learning environment.
Build and operate powerful targeted applications to transform your business
The Digitalize and Transform packaged solution helps manufacturers build powerful, targeted applications for internal use and for selling to customers, enabling the development of new services and business models.
The MindSphere Digitalize and Transform Solution Package includes the following:
MindAccess DevOps Plan
Develop and operate MindSphere applications to strengthen your own digitalization strategy, and sell applications to customers.
The intelligent gateway for industrial IoT solutions
SIMATIC IOT2000
As part of Industry 4.0, networking of production and office IT continues to expand. Production data is collected and evaluated in the cloud to optimize production. Networking of existing plants is a major challenge in this regard, because the machines from different manufacturers and on different technological levels often do not speak the same data language. The solution is often time-consuming and complex retrofitting in these situations.
An intelligent gateway that harmonizes communication between the various data sources, analyses it and forwards it to the corresponding recipients, is a solution that can be easily implemented in these scenarios. It can be used to implement production concepts even for existing plants that are prepared to face the future
By 2025, 50% of industrial enterprises will use industrial Internet of Things (IIoT) platforms to improve factory operations, up from 10% in 2020.
Market Definition/Description
Gartner defines the IIoT platform market as a set of integrated software capabilities to improve asset management decision making within asset-intensive industries. IIoT platforms also provide operational visibility and control for plants, infrastructure and equipment.
IIoT Platforms
The IIoT platform cost-effectively collects higher volumes of high-velocity, complex machine data from networked IoT endpoints. The IIoT platform also orchestrates historically siloed data sources to enable better accessibility, and improve insights and actions across a heterogeneous asset group through specialized analysis of the data.
The IIoT platform:
Monitors IoT endpoints and event streams
Analyzes data at the edge and in the cloud
Integrates and engages IT and OT systems in data sharing and consumption
Enables application development and deployment
Can enrich and supplement OT functions for improved asset management life cycle strategies and processes
The IIoT platform, in concert with the IoT edge and through enterprise IT/OT integration, prepares asset-intensive industries to become digital businesses. Digital capabilities are achieved by enhancing and connecting their core business with customers, suppliers and business partners.
The IIoT platform software that resides on and near devices — such as controllers, routers, access points, gateways and edge compute systems — is considered part of the “distributed IIoT platform.”
The platform provider must exhibit demonstrable value in terms of integration and interoperability with such applications, which include:
Enterprise asset management (EAM)
Computerized maintenance management systems (CMMSs)
Fleet management
Condition-based maintenance (CBM)
Manufacturing execution systems (MES)
Maintenance, repair and operations (MRO)
Product life cycle management (PLM)
Application portfolio management (APM)
Field service management (FSM)
Building management systems (BMSs)
IIoT Platform Capabilities
The IIoT platform is composed of the following technology functions:
Device management — This function includes software that enables manual and automated tasks to create, provision, configure, troubleshoot and manage fleets of IoT devices and gateways remotely, in bulk or individually, and securely.
Integration — This function includes software, tools and technologies, such as communications protocols, APIs and application adapters, which minimally address the data, process, enterprise application and IIoT ecosystem integration requirements across cloud and on-premises implementations for end-to-end IIoT solutions. These IIoT solutions include IIoT devices (for example, communications modules and controllers), IIoT gateways, IIoT edge and IIoT platforms.
Data management — This function includes capabilities that support:
Ingesting IoT endpoint and edge device data
Storing data from edge to enterprise platforms
Providing data accessibility (by devices, IT and OT systems, and external parties, when required)
Tracking lineage and flow of data
Enforcing data and analytics governance policies to ensure the quality, security, privacy and currency of data
Analytics — This function includes processing of data streams, such as device, enterprise and contextual data, to provide insights into asset state by monitoring use, providing indicators, tracking patterns and optimizing asset use. A variety of techniques, such as rule engines, event stream processing, data visualization and machine learning, may be applied.
Application enablement and management — This function includes software that enables business applications in any deployment model to analyze data and accomplish IoT-related business functions. Core software components manage the OS, standard input and output or file systems to enable other software components of the platform. The application platform (for example, application platform as a service [aPaaS]) includes application-enabling infrastructure components, application development, runtime management and digital twins. The platform allows users to achieve “cloud scale” scalability and reliability and deploy and deliver IoT solutions quickly and seamlessly.
Security — This function includes the software, tools and practices facilitated to audit and ensure compliance. This function also establishes preventive, detective and corrective controls and actions to ensure privacy and the security of data across the IIoT solution.
According to a report by IDC, it is expected that the investment in IoT technology would reach $1 trillion by the end of 2020, which is an exceptional growth of connected devices. Many of them are smart devices. We are already using many apps and devices that are functioning based on IoT. Google Assistant or Microsoft Cortana allow us to automate the regular things based on IoT only., Businesses are investing in this technology, especially in smartphone development that uses IoT.
Internet of Things: A Simple definition by Vermesan (2013):
Internet of things is a network of physical objects
(Devayani Kulkarni's MS Thesis Internet of Things in Finnish Metal Industry, March 2018)
Cisco Keynote at IoT Evolution Expo Ft Lauderdale 2017
14 Mar 2017
Maciej Kranz of Cisco speaks at IoT Evolution Expo Ft Lauderdale 2017
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Cisco Live 2016: The Business of IoT: Go Fast and Grow Fast Now
13 Jul 2016
The Business of IoT: Go Fast and Grow Fast Now - Rowan Trollope, Jahangir Mohammed, and Sandy Hogan.
E-Technologies: Embracing the Internet of Things: 7th International Conference, MCETECH 2017, Ottawa, ON, Canada, May 17-19, 2017, Proceedings
Esma Aïmeur, Umar Ruhi, Michael Weiss
Springer, 09-Jun-2017 - Computers - 319 pages
This book constitutes the refereed proceedings of the 7th International Conference on E-Technologies, MCETECH 2017, held in Ottawa, ON, Canada, in May 2017.
This year’s conference drew special attention to the ever-increasing role of the Internet of Things (IoT); and the contributions span a variety of application domains such as e-Commerce, e-Health, e-Learning, and e-Justice, comprising research from models and architectures, methodology proposals, prototype implementations, and empirical validation of theoretical models.
The 19 papers presented were carefully reviewed and selected from 48 submissions. They were organized in topical sections named: pervasive computing and smart applications; security, privacy and trust; process modeling and adaptation; data analytics and machine learning; and e-health and e-commerce.
Industry X.0: Realizing Digital Value in Industrial Sectors
Eric Schaeffer
Kogan Page Publishers, 03-May-2017 - Business & Economics - 192 pages
Industry X.0 takes an insightful look at the business impact of the Internet of Things movement on the industrial sphere. Eric Schaeffer combines deep analysis with practical strategic guidance, and offers tangible and actionable recommendations on how to realise value in the current digital age. Based on extensive research and insights into the six core competencies that have been identified by Accenture, Industry X.0 explores critical aspects of the Industrial Internet of Things (IIoT), discussing and defining them in an engaging and accessible manner. These include managing smart data, handling digital product development, skilling up the workforce, mastering innovation, making the most of platforms and ecosystems, and much more.
Meticulously researched and clearly explained, Industry X.0 makes a stringent case for companies to actively shift mind-sets away from products, towards services, value and outcomes. Complemented by a wealth of case studies and real world examples, this book provides invaluable, practical 'how-to' advice for business organizations as they embark on their journeys into the era of the IIoT.
Simplify IT’s Six Levers
The following are the six levers for simplifying IT:
1. Intelligent Demand Management.
2. Application and Data Simplification.
3. Infrastructure-Technology-Pattern Reduction.
4. Simplified IT Organization and an Enabled IT Workforce.
5. Effective Governance and Simplified Processes.
6. A Shared-Services Model and Optimized Sourcing.
Smart House and Smart City
Industrial Internet
Smart Cars
Wearables
Home Healthcare
Business Rule Generation for IoT 3 layered architecture of Big Data — Physical (Sensors), Communication , and Data Intelligence
All about Sensors – Electronics
Basic function and architecture of a sensor — sensor body, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure, legacy and modern sensor network — all the basics about the sensors
Development of sensor electronics — IoT vs legacy, and open source vs traditional PCB design style
Development of sensor communication protocols — history to modern days. Legacy protocols like
Modbus, relay, HART to modern day Zigbee, Zwave, X10,Bluetooth, ANT, etc.
Business driver for sensor deployment — FDA/EPA regulation, fraud/tempering detection, supervision, quality control and process management
Different Kind of Calibration Techniques — manual, automation, infield, primary and secondary calibration — and their implication in IoT
Powering options for sensors — battery, solar, Witricity, Mobile and PoE
Hands on training with single silicon and other sensors like temperature, pressure, vibration, magnetic field, power factor etc.
Fundamental of M2M communication — Sensor Network and Wireless protocol
What is a sensor network? What is ad-hoc network?
Wireless vs. Wireline network
WiFi- 802.11 families: N to S — application of standards and common vendors.
Zigbee and Zwave — advantage of low power mesh networking. Long distance Zigbee. Introduction to different Zigbee chips.
Bluetooth/BLE: Low power vs high power, speed of detection, class of BLE. Introduction of Bluetooth vendors & their review.
Creating network with Wireless protocols such as Piconet by BLE
Protocol stacks and packet structure for BLE and Zigbee
Other long distance RF communication link
LOS vs NLOS links
Capacity and throughput calculation
Application issues in wireless protocols — power consumption, reliability, PER, QoS, LOS
Hands on training with sensor network
1. PICO NET- BLE Base network
2. Zigbee network-master/slave communication
3. Data Hubs : MC and single computer ( like Beaglebone ) based datahub
Review of Electronics Platform, production and cost projection
PCB vs FPGA vs ASIC design-how to take decision
Prototyping electronics vs Production electronics
QA certificate for IoT- CE/CSA/UL/IEC/RoHS/IP65: What are those and when needed?
Basic introduction of multi-layer PCB design and its workflow
Electronics reliability-basic concept of FIT and early mortality rate
Environmental and reliability testing-basic concepts
Basic Open source platforms: Arduino, Raspberry Pi, Beaglebone, when needed?
RedBack, Diamond Back
Conceiving a new IoT product- 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
Introduction to 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
A 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
4V- Volume, velocity, variety and veracity of Big Data
Why Big Data is important in IoT
Big Data vs legacy data in IoT
Hadoop for IoT-when and why?
Storage technique for image, Geospatial and video data
Distributed database
Parallel computing basics for IoT
Waspmote Plug & Sense! integrates more than 70 different sensors, adapting to any scenario such as smart parking, air and noise pollution, irrigation control, vineyard monitoring, etc.
With its waterproof enclosure Waspmote Plug & Sense! is suitable for outdoor deployment and, thanks to solar panels and its extreme low power consumption, can work autonomously for years.
Meshlium
Meshlium receives sensor data from Waspmote Plug & Sense! and forwards it directly to the Internet via Ethernet, Wi-Fi or 3G/GPRS protocols depending on the connectivity options available in the area.
In case connectivity fails, data can be stored in an internal data base. Meshlium is encased in a rugged, waterproof enclosure that protects it from the harshest conditions.
Meshlium to Cloud
Meshlium is ready to send sensor data to all the Cloud software platforms below. Just select the most suitable for you, get an account from the provider and configure your Meshlium.
If you are not ready to make a choice or prefer to implement your own Cloud solution, you can still configure Meshlium to store data into any data base on the Internet or inside the Meshlium device (see diagram below).
ETSI, the European Telecommunications Standards Institute, produces globally-applicable standards for Information and Communications Technologies (ICT), including fixed, mobile, radio, converged, broadcast and internet technologies. ETSI Mission: Deliver world-class standards for Information and Communication Technology (ICT), including telecommunications, for systems and services by using and providing state-of-the-art methodology and processes. https://www.youtube.com/user/ETSIstandards
IoT Security and Scalability on Intel® IoT Platform
Tags:Internet of Things
Secure, Scalable, Interoperable
The Intel® IoT Platform is an end-to-end reference model and family of products from Intel, that works with third party solutions to provide a foundation for seamlessly and securely connecting devices, delivering trusted data to the cloud, and delivering value through analytics.
The Bosch IoT Suite - foundation for your IoT application
The Bosch IoT Suite provides the foundation for service enablement, both in terms of connecting things to the Internet – reliably, securely, cost effectively and at scale – and in terms of delivering the backing application logic for value-added services. It is made up of a set of software services that provide all of key middleware capabilities needed to build a sophisticated IoT application from top to bottom. Customers can use any combination of these IoT services as needed to rapidly implement the desired solution.
Reliably and securely collect data from devices
Standardize integration of devices with the enterprise
Perform real-time, big data, and predictive analytics on IoT streams and events
Seamlessly extend enterprise applications and processes with IoT data
Allow enterprise and mobile applications to control devices
Use the connected product maturity model to identify the capabilities that make sense for your product portfolio. Then consult the connected product value curve model to locate and measure the cost and revenue benefits of those capabilities. http://www.ptc.com/internet-of-things/business-value
Cisco has announced that it intends to purchase Jasper Technologies, Inc. for $1.4 billion. Jasper has developed a specialized platform for cloud-based IoT management and it also as an extensive customer base.
Jasper provides cloud-based platforms that help companies manage Internet of Things services, connecting a wide variety of devices through cellular networks and then managing connectivity and collecting data through their Software as a Service (SaaS) platform. Customers can access their IoT data through a specialized Control Center.
Jasper has 3,500 customers, including the GPS company Garmin, greeting card giant Hallmark and the jet engine manufacturing division of GE.
Cisco will also retain Jasper CEO Jahangir Mohammed to run the new IoT software business unit at Cisco.
Cisco purchased OpenDNS last year. The company provides security services. The $635 million acquisition of OpenDNS, added additional cloud security abilities to Cisco’s existing security systems.
2013
Cisco estimates IoT value potential in the world economy to be $19 trillion in 2022.
An IoT platform facilitates communication, data flow, device management, and the functionality of applications. It links machines, devices, applications, and people to data and control centers. It employs better, quicker search engines and data storage systems with the capacity and sophistication to handle large volumes. Most of its elements are cloud-based and running on wireless connectivity, which may be established via third-party providers, application programming interfaces (APIs), cellular capabilities, or—most likely—a combination of these technologies.
IDC defines the IoT as a network of networks of uniquely identifiable endpoints (or "things") that
communicate without human interaction using IP connectivity. The ecosystem that supports the IoT
includes a complex mix of technologies not limited to modules/devices, connectivity, IoT platforms,
storage, servers, security, analytics software, and IT services. IDC expects that by 2020, spending on
the IoT will be $1.7 trillion. http://www.ibm.com/internet-of-things/files/US40999116.pdf - IDC report sponsored by IBM
Key Features Required in IoT Platforms
Device Management
“build-deploy-evolve” approach to app development
Bi-directional, ƒFlexible connectivity
Back up beyond the cloud
Machine Data analytics
Collaboration in the Supply Chain
Availability, scalability, and reliability
Maintainability
Flexibility and network agnosticism
Security and data privacy
Five key elements of the IoT platform
IDC
Device Management
Connectivity Management
Application Management
Dashboard and Reporting
Analytics
