Uploaded October 2025 | Updated September 2026, 2 weeks ago

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Speaker: Ninad Mehta | Duration ca. 33 min incl. Q&A

Indoor air pollution often presents a more severe challenge than outdoor pollution, underscoring the critical need for effective air filtration systems in various environments, from residential buildings to industrial facilities. Traditional methods for predicting air filter blockages, such as periodic manual inspections or simple threshold-based detection, are frequently inefficient and can lead to unexpected system failures or suboptimal performance.

This webinar explores an innovative approach to enhance predictive maintenance:
- The use of machine learning (ML) algorithms combined with data from differential pressure sensors to accurately predict filter blockages in vacuum systems.
- Detailed insights into how this predictive methodology can significantly enhance the predictive maintenance of HVAC systems, moving from reactive to proactive intervention.
- Benefits including improved air quality, reduced maintenance costs, and extended equipment lifespan.

#PredictiveMaintenance
#HVACSystems
#MachineLearning

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Timestamps:
00:08 Introduction
00:46 Presentation
27:54 Questions and Answers