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Media verified Verified Outcome TRL 9

HPC-Driven Real-Time Broadcast Analytics

domain Client: A premier global motorsport organization handshake Provider: AWS schedule Deploy: Q4 2023 (Review)
85 Impact
Enterprise Ready
Evidence Score: 5/10
Strength: High

Executive Summary

ANALYST: COI RESEARCH

To engage younger demographics and modernize a traditional broadcast product, the organization leveraged High-Performance Computing (HPC) and machine learning models. The system processes millions of data points per second from vehicle sensors to generate live race predictions (e.g., overtake probability, tire degradation) overlayed on the global broadcast feed.

rate_review Analyst Verdict

"Demonstrates the convergence of media and IoT/Edge computing. The implementation successfully moved from post-event analysis to real-time predictive storytelling, though it relies heavily on the cloud provider's proprietary ML stack."

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Full Audit Report Available Includes Risk Register, Technical Specs & Compliance Data.

warning The Challenge

The sport faced stagnating viewership and a perception of being 'hard to follow' for casual fans. Legacy on-premise data centers could not process the telemetry data (1.1 million data points per second) fast enough to provide meaningful context or graphics during the live race window.

psychology The Solution

A cloud-native architecture was adopted to ingest sensor data via Kinesis and process it using SageMaker. Complex aerodynamic computational fluid dynamics (CFD) simulations were moved to HPC clusters to redesign car regulations, while lighter models powered the live 'Insights' graphics API for broadcasters.

settings_suggest Technical & Deployment Specs

Integrations
F1 Car Telemetry, Broadcast Graphics Engine
Deployment Model
Hybrid Cloud
Data Classification
Telemetry (Non-PII)
Estimated TCO / ROI
High
POC Summary (2018-06-01 to 2019-03-01)

"Started with basic tire performance visuals before advancing to complex overtake predictions."

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
Connectivity Latency Critical Redundant track-to-cloud fiber links; edge caching.
Model Hallucination Low Probabilistic framing of stats (e.g., '40% chance').

trending_up Impact Trajectory

Audited value realization curve

Processing of ~1.1M data points per second Verified Outcome
Primary KPICFD simulation time reduced by ~70%
Audit CycleGlobal broadcast latency for graphics <300ms

policy Compliance & Gov

  • Standards: GDPR (Fan Data), Sporting Regulations
  • Maturity (TRL): 9
  • Evidence Score: 5/10
  • Data Class: Telemetry (Non-PII)

folder_shared Verified Assets

description
Verified Case Study
PDF • Version 1
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Technical Audit
PDF • Audited
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Security Architecture

The "Blind Verification" Protocol

How we verified these outcomes for A premier global motorsport organization without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-741
Evidence: Direct SQL Logs
Public
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2. Verified Asset

Outcome: Verified
Ref ID: #COI-741

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