Case Study:
Enhancing the restaurant industry with BI and AI technologies
Smart Management for Chain Restaurants — By leveraging AI-powered monitoring and BI-driven data analysis, we developed a highly efficient, secure, and scalable remote management system. This system empowers chain restaurants to optimize operations, reduce costs, and achieve precision management through data-driven decision-making.
Client & Requirements
Our client operates multiple restaurants across different regions in the United States. As the business expanded, managing vast amounts of data—including orders, deliveries, and sales—became increasingly complex. Traditional manual inspections and sample-based checks proved inefficient, offering limited oversight and slow response times.
To improve operational efficiency and reduce costs, the client sought to implement an intelligent video surveillance system that would:
- Enable centralized restaurant management and real-time monitoring
- Enhance security while reducing labor costs
- Integrate sales and order data to optimize decision-making
Solution overview
- Data-driven decision-making
- AI-powered analytics for intelligent monitoring
- Real-time surveillance and anomaly detection
- System scalability to support future expansion
BI Data Analysis & Visualization
To process and visualize complex sales data in real-time, we selected Apache ECharts as the primary charting library, alongside tools like Tableau and Power BI. This solution enables the client to:
- Generate interactive visual reports for deeper insights into store performance
- Identify trends and optimize business strategies
AI-Powered Remote Video Surveillance
By integrating AI-driven facial recognition and behavioral analysis, the system provides:
- Real-time monitoring and security supervision
- Anomaly detection to prevent losses
- Remote access, allowing managers to oversee operations from anywhere
Intelligent Operations Management
AI-powered cameras capture peak hours, customer traffic, and behavioral trends. This data is then visualized in BI dashboards, allowing restaurant owners to:
- Optimize staff allocation and improve service efficiency
- Enhance operational strategies based on real-time insights
Technologies
To ensure high efficiency and scalability, we designed a modular system architecture, where each component operates independently yet integrates seamlessly.
- Frontend Development: Built with TypeScript, ensuring maintainable, high-performance code with an intuitive user interface for data exploration via dashboards.
- Backend Architecture: Powered by Apache Superset, an open-source platform supporting multi-source data exploration and visualization.
- Real-Time Data Synchronization: We implemented efficient storage and synchronization mechanisms to ensure accurate, real-time business insights across all locations.
Team composition
- Two full-stack developers – Responsible for React, TypeScript, Apache Superset, and Apache ECharts, covering both camera integration and BI functionalities.
- One AI engineer – Specializing in AI-driven facial recognition for the camera system.
Project outcomes & business impact
After one year of development, the system was successfully deployed and has been running stably, delivering:
- Seamless data integration – Effortless access to key business metrics like sales revenue, order volume, and average service time.
- Enhanced efficiency – The flexibility and scalability of the system significantly improved operational decision-making and response times.
- High client satisfaction – The system received positive feedback for its ease of use and impact on business growth.
Future expansion
Following the project’s success, the client has proposed an extended collaboration to:
- Develop a mobile version for real-time business data access
- Incorporate advanced AI algorithms for predictive analytics
- Further enhance automation to support long-term operational strategies
Moving forward, we will continue optimizing the system to help the client achieve data-driven operational excellence.
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