Smart Emissions Monitoring for US Energy Company

Delivered a 4-week design sprint that targeted 50% improvement in emissions detection accuracy while reducing response times for regulatory compliance. The solution eliminated manual calculations and late nights for field teams through intelligent data integration and low-connectivity-optimized alerts.

Role: Design Lead | Timeline: 4 weeks | Year: 2023

Situation: A major US oil and gas company faced mounting regulatory pressure for emissions monitoring across onshore wells. False positives eroded trust in sensor data, while manual calculations and disparate datasets created operational bottlenecks. Field teams struggled to prioritize responses within prescribed timeframes, and competing demands with inefficient tools compromised compliance efforts.

Task: Lead rapid design sprint to create an intelligent monitoring solution integrating multiple data sources, reducing false positives, and empowering field teams with actionable insights for regulatory compliance.

Action: I led stakeholder workshops to define reduced scope prioritizing critical functionality from initial research. Conducting interviews with field engineers, production managers, and quality teams, I discovered the importance of cross-referencing operational and environmental data for accurate baselines. I designed a unified dashboard with continuous sensor data, robust filtering, and aerial imagery for context. Recognizing low-connectivity constraints, I created lightweight SMS-style alerts containing essential information. I developed an anomaly detection engine concept that classified emission events and automated complex calculations, and facilitated journey mapping sessions that identified necessary service architecture and parallel work streams for phased implementation.

Result: Stakeholders praised the research-driven approach and ability to balance ambitious vision with actionable deliverables in just 4 weeks. The solution concept targeted 50% improvement in correct emission alert identification—cutting false positives in half and rebuilding trust in automated detection. The design projected significant reduction in time between alert detection and field action, enabling faster regulatory compliance responses. By reducing manual calculations and consolidating disparate datasets, the platform would eliminate late nights and manual work for field teams while improving operational decision-making for emissions management across the company's onshore operations.