Industrial computer empowers smart mall: a practical case of dual improvement in operation and energy saving

1. Leapfrog improvement in operational efficiency
(1) Cashier settlement is more convenient
The mall has deployed intelligent cashier terminals centered around industrial computers on each floor and in the supermarket area. These terminals are integrated with high-definition touch screens, multi-mode scanners, and diversified payment modules, enabling integrated processing of product scanning, payment verification, and inventory synchronization. After the self-checkout area was put into use, customers can complete the entire process of product selection and payment in just 30 seconds, effectively diverting more than 70% of the customer flow from traditional cashier counters. The average waiting time during peak periods has been shortened from 15 minutes to less than 3 minutes, significantly improving customer satisfaction. The labor cost in the mall's cashiering process has also been reduced by 25%.
(2) Precise inventory management
The shopping mall has established an intelligent inventory management network through industrial computers, connecting weight sensors and radio frequency identification (RFID) devices distributed across various shelves in real-time with the back-end management system. The industrial computers continuously collect and analyze commodity inventory data. When the inventory of a certain product falls below a preset safety value, the system will automatically send a replenishment reminder to the warehousing department and update the inventory status on the online mall. Leveraging the data analysis capabilities of industrial computers, smart shelves can also accurately identify popular and unpopular products, providing data support for shelf display adjustments. Since implementation, the shopping mall's inventory backlog rate has decreased by 40%, the stock-out rate has been controlled below 3%, and the goods turnover rate has increased by 35%.
(3) Data-driven decision support
The industrial computer comprehensively collects multi-dimensional information such as customer movement data, merchandise sales data, and feedback data from promotional activities in the shopping mall, and conducts in-depth analysis through built-in algorithms. Based on these data, the shopping mall accurately outlines the consumption profiles of different customer groups, launches collaborative merchandise promotions for young customers, designs parent-child consumption packages for family customers, and increases the conversion rate of promotional activities by 50%. At the same time, by analyzing sales trends, the shopping mall predicts seasonal merchandise demand in advance, optimizes procurement plans, and increases the response speed of the supply chain by 30%, effectively reducing the operational risks caused by supply and demand imbalances.
(4) Precise marketing deployment
The shopping mall has deployed a digital signage system driven by industrial computers in public areas, elevator entrances, and near specialty counters. The industrial computers dynamically adjust the content displayed on the signage based on real-time crowd data, customer dwell time, and consumption preference analysis results. In the beauty section, during peak hours with a high concentration of young female customers, new product trial activities and beauty tutorials are played in a loop. In the sports brand section, limited edition sneaker release information is pushed in conjunction with popular sports events. This precision marketing model has increased the advertisement reach rate by 60%, and the sales of related promotional products have increased by 45%.
II. Remarkable achievements in energy conservation and consumption reduction
(1) Intelligent lighting adjusts as needed
The shopping mall adopts an industrial computer to link with a light sensor and a time controller, constructing an intelligent lighting control system. The industrial computer collects real-time data on indoor natural light intensity. During the strong light period from 10 am to 3 pm on sunny days, it automatically turns off 30% of the lighting fixtures in the central hall and window areas of the shopping mall. After the flow of people decreases at night, the illumination brightness in public areas is adjusted to 50% of the daily level through GPIO interface and PWM output technology. In addition, according to the functional requirements of different areas, the industrial computer also presets multiple lighting scene modes, achieving refined control of lighting energy. The lighting energy consumption in the shopping mall has been reduced by 30% compared to before.
(2) Intelligent optimization of air conditioning system
The intelligent control platform for central air conditioning, built around an industrial computer, integrates data from temperature sensors, humidity sensors, and passenger density sensors distributed across various areas of the shopping mall. Based on real-time monitoring of environmental parameters and passenger flow, the industrial computer dynamically adjusts the operating parameters of the chiller units, refrigeration pumps, and cooling pumps to achieve on-demand cooling and heating. For example, during non-peak hours on weekdays, the cooling capacity and air speed are automatically reduced based on the decrease in passenger flow; in areas with concentrated heat, such as the dining area, the cooling efficiency is specifically enhanced. According to statistics, after optimization by the industrial computer, the total energy saving rate of the central air conditioning system reaches 25%, saving approximately 800,000 yuan in electricity costs annually.
(3) Efficient control and management of equipment operation
The industrial computer monitors the real-time operating status of 30 elevators, 18 escalators, and various electromechanical devices in the shopping mall, recording key information such as equipment operation time, load rate, and energy consumption data. Based on these data, the system automatically generates equipment operation plans and maintenance schemes: during low passenger flow periods, the number of elevators in operation is reduced from 15 to 8, and escalators automatically switch to low-speed operation mode when not in use; according to equipment operation wear and tear data, maintenance is arranged in advance to avoid excessive operation or sudden malfunctions of the equipment. After implementation, the equipment idling rate in the shopping mall decreased by 60%, equipment maintenance costs were reduced by 20%, and the average service life of equipment was extended by 3 years.
Through the comprehensive empowerment provided by industrial computers, this mall has not only achieved a leapfrog improvement in operational efficiency and created a superior consumer experience, but also attained remarkable results in energy conservation and consumption reduction, providing a replicable and scalable practical example for the construction of smart malls.