SIMS3: AI Powered Environmental Intelligence

SIMS3: AI-Powered Environmental Intelligence

Artificial Intelligence: The future of Environmental Monitoring

SIMS3 uses artificial intelligence to transform how organizations monitor, manage, and investigate odour and air quality issues. The platform brings together data from fixed stations, mobile mapping systems, satellite sources, and community inputs, then interprets that information through a complete suite of AI models.

How Can The

World's First AI Integrated AIR QUALITY MONITORING Platform

Assist your facility?

30 - 50% More Accurate Impact Predictions

AI-driven models dynamically adjust emission rates and dispersion behavior, significantly improving odour and air quality prediction accuracy compared to static inventories.

Rapid Detection of New and Changing Sources

SIMS3 identifies emerging or previously unknown emission sources within hours by analyzing sensor data, complaints, and meteorological patterns.

Validated Public Complaint Intelligence

Citizen odour complaints are automatically verified against real-world dispersion events, increasing confidence and eliminating false or misattributed reports.

Proactive Response Instead of Reactive Enforcement

Predictive AI alerts allow operators and authorities to mitigate impacts before exceedances or community complaints occur.

Smarter Use of Staff and Mitigation Resources

By pinpointing true contributors and high-risk periods, SIMS3 reduces unnecessary investigations and optimizes field and operational response.

Proven Scalability Across City-Wide Deployments

The SIMS3 AI architecture is designed to support thousands of sources and sensors without sacrificing performance or accuracy.

The SIMS3 AI Engine

At the core of SIMS3 is an interconnected network of AI agents that operate together to maintain and update the model.

Growth Beyond Traditional Monitoring

Traditional monitoring is limited to individual instruments and static inventories that quickly become outdated. Cities and industrial regions change rapidly, and emission behaviours shift with weather, season, and operations.

SIMS3 replaces static snapshots with a system that learns from every new data point. Its AI agents adjust emission rates, validate sensor data, detect new sources, and forecast future hotspots. This produces a live, defensible view of environmental impact.

Adaptive Emission Monitoring

SIMS3 uses Bayesian learning, machine learning regression, and sensor fusion to adjust emission inventories dynamically. Data from static stations, mobile UrbanScanner units, drone mapping, industrial analyzers, and public complaints is unified and interpreted automatically.

As conditions change across a facility or city, the model updates without requiring manual recalibration.

Predictive Intelligence and Proactive Management

Neural network models forecast the next several hours of odour and air quality conditions. This allows operators to:

Pattern Recognition and Cluster Detection

Using unsupervised learning, SIMS3 identifies odour clusters, behavioural trends, and emerging emission patterns. It can detect new sources as they appear, distinguish between overlapping plumes, and identify the likely industry category responsible for a signature.

Human-in-the-Loop Learning

SIMS3 combines AI analysis with human expertise. Engineers review events, tag validation samples, and add field measurements from instruments such as the SM100i. Each interaction strengthens future predictions and reinforces the model’s accuracy.

INTRODUCING THE

SIMS3
AI ASSISTANT

AI Help Tool
AI Operations Assistant
Automated Report Generation
Exceedance Interpretation
Unknown Source Analysis
Scenario Support

AI Help Tool

This interactive guidance system will provide users with real-time instruction on how to operate the SIMS3 platform. It explains any page or tool being viewed, provides step-by-step instructions, assists new staff with onboarding, and offers clarification on modelling terms, emission parameters, and workflows.

AI Operations Assistant

This AI tool was designed to assist and automate analysis and operations processes through simple user requests. Contains numerous user-friendly prompts and analytics.

Automated Report Generation

Creates automated regulation-aligned reports, including exceedance summaries, trend analysis, source contribution assessments, complaint investigations, and monthly and annual environmental performance metrics.

Exceedance Interpretation

Once an exceedance is detected, SIMS3 will provide a clear explanation of the cause, the most probable contributing sources, meteorological conditions at the time, and recommended next steps.

Unknown Source Analysis

Our built-in AI Analysis tool can be used to estimate the likely origins of any unexplained odour events. It does so by combining complaints, wind patterns, field data, and model predictions.

Scenario Support

Expores “What-if” questions such as boundary limit changes, facility expansions, or process adjustments to assist with planning or future mitigation efforts.

Scentroid's SIMS3

Comprehensive Data Fusion

Integrates data from multiple sources to improve model accuracy

Live City-Scale Modelling

SIMS3 supports deployments involving hundreds or thousands of emission sources.

The model updates every few minutes as new data is received, ensuring regulators and operators have an accurate, real-time understanding of environmental impact.

This approach has already been demonstrated at large metropolitan scales.

Traditional vs. AI Driven Modeling

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Traditional Models

Rely on Outdated Inventories

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Require Manual Adjustments

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Respond Slowly to Urban and Industrial Changes

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Provide Limited Insight into Complex Regions

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SIMS3 AI

Learns Continuously from Live Data

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Adjusts Emission Profiles Automatically

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Detects New Sources as they Appear

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Predicts Conditions before they Happen

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