A retrofit system using multi-spectral optical sensing and process analytics to optimize starch recovery, reduce water usage, and enhance process efficiency in industrial starch processing. Integrates with existing infrastructure for minimal disruption.
The inline multi-spectral monitoring system is a cutting-edge retrofit solution designed to enhance starch recovery and process efficiency in industrial settings. Utilizing multi-spectral optical sensing combined with turbidity measurement and real-time analytics, this platform provides continuous monitoring of starch fines, suspended solids, and overall wash-stage performance. By offering real-time visibility and data-driven insights, the system supports adaptive process optimization and improved water reuse, addressing key challenges in starch processing such as yield losses and process variability.
Currently at Technology Readiness Level 5, this system has been validated in relevant environments. Future validation is planned through a phased pilot to further assess improvements in starch recovery and wash efficiency, with potential expansion to additional facilities upon successful pilot results.
AquaMesh provides an integrated hardware and software stack designed to modernize water quality monitoring through resilient IoT infrastructure. The company’s ecosystem includes the AquaSpectra multi-parameter optical sensor for field deployment, the AquaLab benchtop analyzer, and the AquaLink hub, which bridges sensor traffic to the cloud. This hardware is supported by the AquaView platform, a web-based software suite that uses predictive AI to surface trends, detect anomalies, and generate automated compliance reports. By combining multi-parameter optical sensing with a robust mesh network, AquaMesh offers a more comprehensive data capture solution than traditional single-parameter sondes.
This technology is essential for teams managing critical water systems, including environmental research, stormwater management, and infrastructure monitoring. AquaMesh helps customers shift from manual data collection to continuous, autonomous sensing, reducing the need for on-site reviews through its AI-driven natural language query interface and predictive analytics. The system’s ability to forecast parameter shifts before they reach regulatory thresholds provides operators with actionable insights, improving compliance accuracy and enabling faster responses to water quality changes.