Cartoons showing convergence of emerging technologies into Cyber-Physical-Social grids to provide support for large-scale Smart X applications. This is a very high level overview meant to capture some of the technology interactions for non-technical viewers.

1. Technology Convergence
for Smart X Applications
Bob Marcus
Co-Chair NIST Big Data PWG
robert.marcus@et-strategies.com
Tuesday, August 16, 16

2. Technology Convergence for Smart X Applications by Bob Marcus
Internet
of Things
Social
Mobile
Cyber-
Physical
Systems
Big Data Cloud
Smart X
Applications
Tuesday, August 16, 16

3. Relation between Technologies
Tuesday, August 16, 16

4. Big Data and Cloud Technology Relationship
Big Data Cloud
Big Data applications run on Cloud
Big Data stored in Cloud
Big Data Analytics
Running on Cloud
Big Data Analytics Cloud Platforms
Tuesday, August 16, 16

5. CPS and Internet of Things Relationship
Internet
of Things
Cyber-
Physical
Systems
Networking of Cyber-Physical Devices
Cyber-Physical
Systems of Systems
Networking of
Cyber-Physical Systems
Networked to Distributed Storage
and Computational Resources
Tuesday, August 16, 16

6. Mobie and Social Technology Relationship
SocialMobile
Interactions among
Mobile Users
Mobile, Social
Applications
Mobile interfaces
Coordination
across users
Tuesday, August 16, 16

7. Smart X Application using Combined Technology Relationships
Cyber-Physical
Systems of Systems
Mobile Social
Interfaces
Big Data Analytics
Running on Cloud
Data
Commands
Raw Data
Processed
Data
Commands
Data
Smart X Application
Tuesday, August 16, 16

8. Reference Links for Technology Convergence
Inventory of all Bob Marcus CPS Slides on Slideshare
http://www.slideshare.net/bobmarcus/inventory-of-my-cps-slide-sets
Tuesday, August 16, 16

9. IEEE International Conference on I-SMAC
From ismac2017.com/cfp.html
The main scope of the conference is the convergence of “IoT technologies for social,mobile,analytics and cloud” (I-SMAC)
including the topics below.
• IoT platform architecture
• IoT analytics
• Privacy preserving IoT data mining
• IoT and big data integrity and confidentiality
• Data and knowledge as a service
• Security and privacy applications
• Real-time and stream processing techniques and algorithms
• Batch processing engine and techniques
• Real-life case studies of value creation through advanced data analytics
• Proactive/predictive and advanced machine learning model
• Simplified and distributed data processing techniques
• Ubiquitous machine learning
• Smart home and independent living
• Fog and Edge computing of healthcare data
• Network Design and Architecture
• Software Architecture and Middleware
• Mobile Services
• Data and Knowledge Management
• Context-awareness and Location-awareness
• Security, Privacy and Trust
• Performance Evaluation and Modeling
• Networking and Communication Protocols
• Machine to Machine Communications
• Intelligent Systems for IoT and Services Computing
• Energy Efficiency
• Social Implications for IoT
• Future of IoT
• Technological focus for Smart Environments
• Next Generation Networks
• Smart City Examples and Case Studies
Tuesday, August 16, 16

10. IEEE International Conference on I-SMAC continued
From ismac2017.com/cfp.html
The main scope of the conference is the convergence of “IoT technologies for social,mobile,analytics and cloud” (I-SMAC)
including the topics below.
• Data Analysis andVisualization for Smart City, Green Systems and Transport Systems
• Architecture for secure and interactive IoT
• Intelligent Infrastructure and Guidance Systems
• Traffic Theory, Modeling and Simulation
• Sensor Networks, Remote Diagnosis and Development
• Transportation Management
• Pattern Recognition and Behavioral Investigations forVehicles, Green Systems and Smart City
• Health Informatics as a Service (HIaaS) for any Type of Health Informatics, Computation and Services
• Security as a Service including any Algorithms, Methodology and Software Proof-of-concepts
• Financial Software as a Service (FSaaS) including Risk and Pricing Analysis; Predictive Modeling
• Education as a Service (EaaS) including e-Learning and Educational Applications
• Business Process as a Service (BPaaS) including Workflows and Supply Chain in IoT
• Software Engineering Approaches, including Formal Methods,Agile Methods and Theoretical Algorithms for IoT
• Natural Science as a Service (NSaaS) including Weather Forecasting and Weather DataVisualization
• System Design and Architecture
• Mobile APIs,Apps, Systems and Prototype
• Gaming as a Service (GaaS)
• Framework (conceptual, logical or software)
• Analytics as a Service (AaaS) for any Types of Analytics
• Electronic, Logic, Robotic and Electrical Infrastructure, Platforms and Applications
• Energy-saving and Green IT Systems or Applications
• Integration as a Service (data; service; business; federated IoT)
• Scheduling, Service Duplication, Fairness, Load Balance for SaaS and Analytics
• Tenant Application Development including Customization,Verification, Simulation, and testing on SaaS and Analytics
• IaaS, PaaS and SaaS quality of service (QoS), security, reliability, availability, service bus mechanisms
• Social Networks and Analytics
• User Evaluations and Case Studies
• Wireless Systems and Applications
• e-Government, e-Commerce, e-Science and Creative Technologies for IoT
Tuesday, August 16, 16

11. SMAC (Social, Mobile,Analytics, Cloud) Stack
From https://www.cognizant.com/InsightsWhitepapers/dont-get-smacked.pdf
Tuesday, August 16, 16

12. IDC 3rd Platform
From http://www.idc.com/prodserv/3rd-platform/
Tuesday, August 16, 16

13. IOTBDS (IoT, Big Data, and Security) Conference
From www.iotbd.org/CallforPapers.aspx
Conference areas include many sub-topics related to:
AREA 1: BIG DATA RESEARCH
AREA 2: EMERGING SERVICES AND ANALYTICS
AREA 3: BIG DATA FOR MULTI-DISCIPLINE SERVICES
AREA 4: INTERNET OF THINGS (IOT) FUNDAMENTALS
AREA 5: INTERNET OF THINGS (IOT) APPLICATIONS
AREA 6: ITS TECHNOLOGIES
AREA 7: SECURITY, PRIVACY AND TRUST
•
Internet of Things (IoT) is a platform and a phenomenon that allows everything
to process information, communicate data, analyze context collaboratively and in
the service or individuals, organizations and businesses. In the process of doing
so, a large amount of data with different formats and content has to be
processed efficiently, quickly and intelligently through advanced algorithms,
techniques, models and tools.This new paradigm is enabled by the maturity of
several different technologies, including the internet, wireless communication,
cloud computing, sensors, big data analytics and machine learning algorithms.
Tuesday, August 16, 16