In industrial enterprises, utility systems—such as compressed air, circulating cooling water, central air conditioning, and heating boilers—are often referred to as the "powerhouse" of production. However, this "heart" is frequently a major energy consumer; while utility systems typically account for 30% to 60% of a plant's total energy consumption, they have long been plagued by issues such as inefficient "oversized equipment for light loads" operations, reliance on manual adjustments based on experience, and a lack of coordination between subsystems.

How can this "tough nut to crack"—improving efficiency while cutting costs—be resolved? Lanchuang Intelligent has developed the "Carbon Source Sentry" AI energy-saving agent, offering industrial enterprises a comprehensive energy efficiency optimization solution that spans the entire chain from "sensing" and "decision-making" to "execution."

 

 

 

In many factories, air compressors, water pumps, and chillers consume vast amounts of energy yet rely on fixed operating strategies or manual adjustments based on the experience of veteran operators. When production loads fluctuate, the energy supply side fails to respond in real-time, resulting in significant electrical energy waste due to redundant, inefficient operation.

Meanwhile, the problem of data silos is severe; systems for compressed air, circulating water, and refrigeration operate independently without coordination, meaning local adjustments can sometimes even reduce overall efficiency. Traditional energy management methods are no longer adequate to meet the urgent demands for quality improvement, cost reduction, and efficiency enhancement.

 

 

 

Powered by the Qingyuan industrial large model and the Squirrel cloud platform, the "Carbon Source Sentry" AI energy-saving agent establishes an integrated AIoT technical framework covering data acquisition, analysis, control, and optimization. Rather than merely retrofitting individual pieces of equipment, it utilizes real-time data collection across all utility system elements and deep AI algorithmic analysis to achieve a paradigm shift from "experience-driven" to "data-driven" operations. 

 

 

By deploying sensing devices such as current/voltage sensors, temperature sensors, pressure transmitters, and flow meters, the "Carbon Source Sentry" (Carbon Source Sentinel) creates a comprehensive map of the real-time operating status of compressed air systems (air compressors, dryers, air storage tanks), circulating cooling water systems (cooling towers, circulation pumps), central air conditioning and cooling sources (chillers, chilled water pumps), and heating boiler systems.

 

 

 

Load forecasting and dynamic optimization: Real-time analysis of production load fluctuations and climatic impacts allows for the automatic optimization of equipment operating parameters and combinations. This ensures energy supply precisely matches actual demand, eliminating "redundant energy supply."

 

Global collaborative scheduling: Breaking down silos between subsystems—such as compressed air, refrigeration, and circulating water—to achieve coordinated optimization across multiple equipment groups. The goal is overall system energy efficiency rather than merely localized energy savings.

 

 

Strategic commands are transmitted via industrial gateways and "Sentry Boxes" (integrated edge computing units) to execution-layer devices—such as variable frequency drive (VFD) controllers and electric valve controllers. This enables "autopilot" functionality for utility and auxiliary systems, automatically adjusting parameters like air compressor operating frequency, chilled water outlet temperature, and pump speeds to ensure sustained, high-efficiency operation.

This system offers a reference energy-saving rate of 15%–28% and an investment payback period of just 8–12 months. It is suitable for a wide range of industries—including machinery manufacturing, automotive parts, electronics assembly, food processing, and textile printing and dyeing—helping enterprises improve energy efficiency, intelligently detect leaks, precisely locate faults, and even track equipment-level carbon footprints.

 

Amidst the major trends of zero-carbon factory construction and green manufacturing, the intelligent upgrading of utility and auxiliary systems has become essential for industrial enterprises seeking to reduce costs, boost efficiency, and manage carbon emissions. The Carbon Source Sentry AI energy-saving agent leverages AI technology to transform utility systems from "major energy consumers" into "energy-saving pioneers," injecting powerful momentum into the green transformation of the industrial sector.