Advancing HVAC Quality and Performance through State-of-the-Art Sensing Technology

Abstract

This study explores the integration of advanced sensing technologies into HVAC systems to improve efficiency and performance, with a focus on Northwest Indiana casinos. The project addresses challenges faced by traditional systems, such as inconsistent temperature control, high energy consumption, and poor air quality, which impact guest comfort and operational costs. Using a controlled testing environment and EnergyPlus simulation software, the research modeled casino-specific HVAC loads while incorporating IoT-enabled sensors, infrared thermal imaging, and AI-based optimization. Infrared cameras identified inefficiencies such as air leaks and duct blockages, while Schlieren imaging visualized airflow distribution to address zoning problems. Data was collected in 5-minute intervals across a 1-hour period to evaluate thermal comfort, airflow consistency, and energy use. Results demonstrate a 15% reduction in simulated energy consumption, enhanced airflow uniformity, and improved indoor air quality through better ventilation control. This research highlights the potential for intelligent HVAC technologies to enhance sustainability, reduce operational costs, and elevate guest experiences in high-occupancy environments.

Introduction

Overview:
Casinos in Northwest Indiana (e.g., Ameristar, Horseshoe, Hard Rock) face significant HVAC challenges due to 24/7 operation, variable occupancy, and frequent structural changes. These factors lead to poor zoning, uneven airflow, and high energy consumption, affecting guest comfort and efficiency.

Current Limitations:
Interviews with HVAC professionals revealed only 20% of casinos use modern HVAC technologies like IoT sensors, AI-based predictive maintenance, or infrared thermal imaging. The majority (80%) still rely on traditional, reactive systems, revealing a regional gap in adopting intelligent HVAC solutions.

Research Gap:
While modern HVAC technologies show promise in residential and commercial buildings, few studies focus on entertainment venues like casinos that have complex zoning and fluctuating occupancy. This study addresses that gap by simulating casino-like conditions to evaluate the effectiveness of advanced HVAC systems.

Technologies Evaluated:

• IoT Sensors: For real-time monitoring of temperature, humidity, and occupancy.

• AI Algorithms: For predictive maintenance and adaptive temperature control.

• Infrared & Schlieren Imaging: For detecting air leaks, insulation gaps, and airflow paths.

• Simulation Tool: EnergyPlus was used to model occupancy-based HVAC behavior over a 24-hour period, based on ASHRAE standards.

Methodology:

Testing Environment:

• Simulated in a 3.05m x 3.05m room with constant environmental controls.

• Conducted at a residential location in Frankfort, Illinois due to access limitations in casinos.

Instrumentation:

• Infrared Camera (HIKMICRO Pocket2): Visualizes surface temperature and thermal leakage.

• Digital Anemometer: Measures air velocity at various duct distances.

Testing Conditions:

• Room Temp: 22°C ± 1°C

• Humidity: 45% ± 5%

• Thermal and airflow data collected every 5–10 minutes.

Performance Metrics:

• Energy Consumption (kWh)

• Temperature Differential (ΔT)

• Airflow Rate (m³/h)

• Visual heat mapping and airflow consistency used to identify inefficiencies.

Key Findings:

• Thermal Images: Showed areas of heat concentration and leakage in ductwork, pipes, and appliances. Simulated casino environments highlighted uneven heat distribution in multi-activity spaces.

• Airflow Tests: Demonstrated a sharp decline in airflow effectiveness as distance from ducts increased.

• Simulated Casino Room: Mimicked real-world conditions with high foot traffic; highlighted the benefits of zoning and dynamic temperature regulation.

Conclusion

This study demonstrates how infrared thermal imaging, digital airflow measurement, and energy simulation can be effectively used to evaluate and enhance HVAC performance in high occupancy environments. Through controlled testing and simulation using EnergyPlus, the experimental results revealed measurable improvements in airflow consistency, temperature regulation, and potential energy savings when applying sensor driven HVAC strategies. Infrared thermography identified zones of heat loss and insulation gaps, while airflow tests quantified the impact of distance on air velocity. These findings support the feasibility of using smart sensing tools to optimize HVAC performance in complex indoor spaces. Although these technologies remain underutilized in regional casinos across Northwest Indiana, this study provides evidence for their value. By modeling casino scale environmental dynamics, this research illustrates how AI driven predictive maintenance, Schlieren imaging, and thermal monitoring can address common inefficiencies particularly those caused by outdated zoning, poor airflow, and static system scheduling. The experimental framework developed in this study can serve as a replicable model for further research and commercial adoption in similar environments. Overall, this work bridges the gap between existing HVAC research and real-world commercial implementation by providing experimental evidence, simulation validation, and practical insights. It establishes a foundation for integrating modern HVAC innovations into casino facilities, with broader implications for high occupancy public venues seeking to enhance sustainability, reduce operating costs, and improve indoor environmental quality.

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Copyright

Copyright © 2025 Mohammad Attallah, Dr. Afshin Zahraee. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.