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Transforming Real-Time Systems: From Observation to Action in Dynamic Environments

Explore the evolution of real-time systems that harness vast data streams through ubiquity in sensor networks. This transformative approach emphasizes continuous observation, automated learning, and instant decision-making across full-scale environments. Delve into historical milestones like MIT's Whirlwind and LINC, which set the foundation for today's adaptive, interactive models. By simulating systems from aircraft to biomedical research, we engage in a process that blends context, analysis, and actionable insights, prompting questions about 'what if' scenarios in an ever-evolving landscape.

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Transforming Real-Time Systems: From Observation to Action in Dynamic Environments

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  1. REAL TIME

  2. Now Digitized: Sense/Observe Collect/Distribute Analyze Simulate Live, Full-scale Giga-Places Peta-Bytes, Tera-OPS Femto-time Learn Observe Decide Real-time, massive analysis Automated learning Vast, evolving knowledge stores Interoperable, pervasive networking Ubiquitous sensors Act

  3. What If? What is “real time”? Too Late In Time Now Then Real Time Systems: Live, always-on, reactive, interactive, stable, controllable, adaptive

  4. What If? What If? Later Now Then Rate-1 Rate-1 Rate-1

  5. Time Frames and Operation Rates • Observation time – measure, discriminate • Analysis time – communicate, contextualize, understand • Decision time – choose, formulate, distribute • Action time – energize,drive

  6. Sample rates vary with applications

  7. It all begins with simulation… Model of System e.g. airplane Simulator with Human Sensors* *Sensors may be people

  8. MIT Whirlwind (c1951) first real time computer. Begot SAGE (Semi-Automatic Ground Environment)

  9. Sample rate versus utility

  10. Wes Clark, Lincoln Laboratory, and LINC, first PC. LINC: Laboratory Instrument Computer c. 1962Real time processing for bio-medical research.

  11. Real time Sensinge.g. laboratory control, simulators Observers, Model Builders e.g. Scientists REAL WORLD System Sensors* Channel to effect behavior *Sensors may be people

  12. LINC 2007 Vintage Computer Fair(At age 45 … turns 50 next year)

  13. Some other real time computers • Whirlwind: Bright Boys • 1962 LINC that influenced PDP-5 • 8/1963 PDP-5 for interfacing a Canadian research reactor to a PDP-4 (controller) • RT-11 from OS/8 begot CPM >> DOS • RSX-11

  14. Sensing… Observations by human operators Sharing of data To effect change REAL WORLD System Sensors* *Sensor/effector may be people

  15. Real time Control Plain old closed loop control Model of REAL WORLD System Advice (t+1) Controller (Processing, policies and people) REAL WORLD System Sensors* Effectors* *Sensor/effector may be people

  16. Real time and Control with/wo Real World Modeling Model of REAL WORLD System Advice (t+1) Controller (Processing, policies and people) Delays and Noise Sensors* REAL WORLD System Effectors* Delays and Noise *Sensor/effector may be people

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