Industrial Sensor Analytics & Fault Prediction

RNDSquare partnered with them to design and build the complete keg monitoring and prediction platform, covering embedded hardware, firmware, edge processing, and cloud analytics. Smart sensor modules were engineered to capture temperature, pressure, motion, and cleaning-cycle signals from kegs in real-world brewery and distribution environments. Edge logic validated and filtered sensor data before transmission to ensure reliability under intermittent connectivity and harsh operating conditions. The cloud platform aggregated real-time and historical data to model keg lifecycle behavior, detect anomalies such as temperature excursions, pressure deviations, delayed returns, or cleaning violations, and generate early warnings before issues impacted quality or operations. Deployment followed a structured rollout, starting with pilot installations and calibration, followed by data validation and analytics tuning based on real usage patterns, and finally enabling dashboards, alerts, and reporting for brewery operations and quality teams.

This partnership enabled the solutions provider to bring a differentiated, production-grade keg monitoring and prediction offering to market without building an internal product engineering team. Breweries gained visibility into keg health, location, and usage, enabling better asset utilization, reduced losses, improved quality control, and regulatory compliance. Ongoing platform refinement and support ensured the solution scaled across customers, regions, and growing keg fleets while remaining operationally stable and commercially viable.