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case study

Effluent Ambient & Emmission Monitoring

Monitoring the quality of ambient air, noise, vibration, effluents, and industrial exhausts is crucial to ensure regulatory compliance, worker safety, and environmental sustainability. Key parameters include particulate matter (PM), CO₂, NOx, SOx, pH, turbidity, noise levels, and vibration intensity. IoT-based sensors can continuously collect real-time data, transmitting it to cloud platforms for analysis. Statutory bodies can access dashboards for compliance monitoring, while AI models analyze historical data to predict long-term environmental impacts. AI-driven simulations can help industries assess the effectiveness of mitigation measures, optimize operations, and reduce ecological footprints. By integrating IoT and AI, industries can achieve proactive environmental management and transparent regulatory compliance.

Effluent Ambient & Emmission Monitoring

The Pain

  • Effluent Ambient & Emmission Monitoring involve cotton of different quality as raw material.
  • Often different raw materials are mixed by mistake in the multiple stages of processing it into yarn.
  • There is no traceability and guidance on which cotton should go into which process unit.
  • This leads to serious quality issues and hence raw material wastage.

The Solution

  • This is confidential and exclusively developed for the Clien.

Benefits

  • 9.8% reduction in wastage of raw materials.
  • Improved production throughput by 7%.
  • Instant reporting of raw material mixing and stopping the machine.
  • Workers get guidance on how to move the output of one stage to another, preventing time wastage.