Innovation Potential and Challenges in Smart Ecosystems

Transcription

1 Innovation Potential and Challenges in Smart Ecosystems Dr. Joerg Doerr Fraunhofer IESE Kaiserslautern, Germany 9 th Silicon Saxony Day Dresden

2 Digital Society Private Life: Isolated Mobile Devices, Social Media & Co.

3 Digital Society Business Life: Integration Enables Innovation! in Information Systems as well as in Embedded Systems

4 Trends and Implications New business models that did not work in the past start to work now (Apple Store, Micropayment,..) Private life pushes business life Physical objects go digital Machinery, things, living objects like plants and animals Usage of Big Data to exploit available data Uncertainty at runtime

5 IT Mega Trend: Integration Big Data / Data Analytics

6 Digital Ecosystems Software Ecosystems deliver innovations through integrated software systems are typically driven by multiple organizations at their own pace to interact with shared markets operate through the exchange of data, functions, or services with mutually influencing parts Smart Ecosystems integrate non-trivial information systems supporting business goals integrate non-trivial embedded systems supporting technical goals function as one unit to achieve a common, superior goal and share context-dependent information

7 Biological and Digital Ecosystems Survival of the Fittest Biological Ecosystems Software Ecosystems Smart Ecosystems Subjects living organisms organizations organization Objects systems systems Value fitness potential to produce viable offspring fitness potential to earn money (directly or indirectly) fitness potential to earn money (directly or indirectly) Resources entities manpower money code manpower money code entities Environment physical digital physical digital

8 Integration of IS and ES - Differences Key Goals Optimization of Business Processes Optimization of Technical Processes (sensors and actuators) Optimization of both, Business Processes & Technical Processes with Equal Rights Software Engineering IS-Driven (Information Systems 2.0) ES-Driven (Embedded Systems 2.0) ES/IS-Integration Key Qualities (Examples) may include embedded data in workflows may use information systems for data storage, e.g., in the cloud Participative Engineering: Across Organizations (sometimes with Equal Rights) Security Safety Safety & Security

9 Smart Ecosystems A Trend Across Domains Industry 4.0 Smart Farming V2X and C2X Smart Ecosystems ehealth eenergy

10 Research in Smart Ecosystems Key Challenges Diversity Big Data Uncertainty Lifecycle Management Complexity Guaranteed Qualities e.g., Safety and Security

11 Uncertainty Runtime Devtime System Context

12 Complexity Smart Ecosystems will be the largest artifacts created by human beings Dynamics and longevity require high degree expertise in managing complexity

13 Diversity Many data producers and data consumers Guarantees for Quality of Service (despite the openness) Design for interoperability Flexible and interoperable architectures (open architectures) Level of interoperation enables Integration based on compensates restricted by Interoperability

14 Guaranteed Qualities (Safety & Security) Demands from safety-critical embedded systems and socio-technical systems will be merged! Interplay of guarantees are expected: e.g., in highly coupled systems security problems can cause safety problems Integrated modeling approaches are needed

15 Utilizing Big Data in Smart Ecosystems The Need for Data Usage Control Crowd Data Miner Visualization Data Generator Ecosystem Simulator Global Analysis, Algorithms, Data Fusion, Analysis Database Virtual Runtime Environment Standardized Modelling for Analyses and data Data Miner & Generator Data Miner & Generator Visualization Visualization Organisation 1 Algorithms & Analysis Runtime Environment Data Usage Control Data Usage Control Organisation N Algorithms & Analysis Runtime Environment Models Models Data Sources Data Sources

16 Smart Ecosystems Think Big, Start Small

17 Smart Ecosystems How to Engineer a Vision Assess your Potential & Ability to join/drive an Ecosystem! Form an Ecosystem Vision Establish the System Missions (Re-) Engineer the System Operate the System & Govern Ecosystem

18 Farming Tomorrow It Becomes Smart Interconnected and Integrated Software Systems Smart Ecosystems

19 Living Lab Smart Farming A Testbed for Smart Ecosystems Research

20 cmp Weather Data Prov ider «Component» Customer Right Management «Component» Farmer Weather Monitoring Component «Component» Weather Serv ice Platform «Component» Notification Sender «Component» Farmer Weather Request Planning Component SMS RMI RMI «ArchiMate_CommunicationPath» «ArchiMate_CommunicationPath» «ArchiMate_CommunicationPath» «uses» «Component» Sensor Selector Android Pad Sensor Simulation & Control Panel «External System» «Component» Request Handler «uses» 1..* «Component» Notification Request «uses» «uses» 1..* Outgoing «Component» Weather Sensor type-specific Adapter «uses» «uses» «uses» «uses» Yahoo Weather Serv ice «External System» Living Lab Smart Farming Demonstrator Concept Showcases with domainspecific farming demonstrators SEE-IT Work Monitor shows how software engineering works Active showcase internals are highlighted while being executed Vehicles / Machinery Sensors & Actuators Requirements Safety Architecture Security Mobile Platforms Desktop Applications Source Code Simulation

21 Smart Ecosystems Revolutionize Our Society The Digital Society 2.0 Which impact do Smart Ecosystems have for our future society, the digital society 2.0? More intelligence, more comfort, larger diversity, in private life as well as in our business world New business models More Challenges: Avoiding or dealing with the growing separation of communities: participating and non-participating members in the society Keeping the Pace

22 Impact for Economy / Companies Huge potential for new business AND huge threat to existing players Change in thinking is needed! Think collaborative! Think innovation! Think speed & continuous change! Think quality! Need for engineering increases, but must adapt to these challenges!

23 Takeaways Companies and Society can strongly benefit from Smart Ecosystems Opportunity and threat at the same time for companies Software is the USP Processing power and communication bandwidth are mandatory prerequisites Context-sensitivity, intelligence and added value are delivered by software. Software Engineering is Key to Success achieve the right goals right at the right time with the right level of quality at development time and at run time Challenges in Smart Ecosystems require guaranteed qualities Fraunhofer IESE provides strong competences for Smart Ecosystem challenges

24 Dr. Jörg Dörr Fraunhofer IESE