IoT software RED OPTIMISE

reportingIOT platformanalysis and simulation

Overview
RED optimise by CAREL is a refrigeration analytics platform that collects and processes data from refrigeration systems across single or multiple food retail stores to generate shared operational insights supporting temperature control, energy efficiency and proactive maintenance.

Cooling intelligence for food retail operations
Designed for food retailers, RED optimise helps preserve product quality and continuity of cold chain operations while reducing energy consumption, operating costs and waste. The platform translates refrigeration system measurements into operational indicators that align with store-level and chain-level objectives.

Shared data for balanced decision-making
RED optimise aggregates information from cabinets and assets to provide a unified view of system status. Thermodynamic analysis and performance modelling convert technical signals into actionable guidance for processes such as temperature control, defrost management and anomaly prioritisation, enabling consistent decisions across teams and locations.

Proactive maintenance and performance analysis
The solution monitors KPIs based on product storage temperature, energy efficiency and individual asset operation. Cabinet performance indicators use predefined data subsets to detect abnormal conditions early. Decision algorithms assess KPIs, assign severity levels to refrigeration units and recommend operational actions to verify or resolve anomalies, enabling earlier technician intervention and protection of stored products.

Measurable value for optimized sites
By detecting deviations in system data and guiding timely corrective actions, RED optimise supports continuous site optimisation. Distributed intelligence across data, assets and teams enables more proactive maintenance, helping to reduce operating costs and waste, lower energy use and refrigerant‑related emissions, and maintain food safety for stored products.

Features / technical specifications

• Collects and processes refrigeration system data across single or multiple stores
• Applies thermodynamic analysis to translate technical data into operational guidance
• Supports key processes: temperature control, defrost management, anomaly prioritisation
• Provides KPIs based on product storage temperature, energy efficiency and asset operation
• Cabinet performance indicators use predefined data subsets to identify abnormal conditions early
• Decision-making algorithms assign severity levels and recommend operational actions
• Enables proactive maintenance and continuous optimisation of sites
• Targets reductions in operating costs, waste, energy consumption and refrigerant‑related emissions
• Designed for distributed intelligence and shared insights across teams and stores