AI Edge in Construction: AI Box's Role in Building AVCiT's New Headquarters

Construction sites today operate under increasing complexity, stricter deadlines, and higher safety expectations. Stakeholders, including contractors, regulators, and development teams, require greater transparency and earlier detection of potential risks.

The construction of AVCiT's new headquarters reflected many of these industry-wide challenges. Due to the site's sheer scale and frequent operational changes, a more systematic approach to safety supervision was required. To address these needs, AVCiT adopted a smart-construction framework that incorporates its AI Box, an AI edge-computing solution that processes data directly on site. It was introduced to support a more structured approach to site oversight throughout the construction process.

1. AI Box's Integration Within the Smart Construction System

As part of the project's distributed collaboration system, AVCiT's AI Box was integrated with other site technologies, including IoT sensors, cloud computing, and big data tools, to create a unified view of safety and operational conditions. Within this setup, each AI Box processes video streams locally to identify and handle safety-related events in real time. This structure supported efficient data flow and provided the analytical foundation for the system’s operational roles throughout the construction phase.

2. Operational Role of AI Box During the Construction Phase

The AI Box supported several core functions during the construction phase, helping maintain consistent monitoring and daily oversight across the site.

2.1 Consistent and Comprehensive AI-Driven Safety Monitoring

AVCiT's AI Box device provides continuous, automated video analysis using a broad range of specialized algorithms. Together, these models provided detailed insight into daily activity and supported identification of potential safety risks.

*Personnel Management and Unsafe Behaviors

Algorithms monitored key aspects of worker safety and behavior, including helmet and reflective vest compliance, smoking in restricted areas and mobile phone use in hazardous zones. Additional models supported personnel counting and attendance tracking.

*Vehicle and Machinery Management

AI Box identified various types of construction vehicles, monitored truck-bed status such as uncovered or empty cargo beds, and tracked the movement of vehicles throughout the site. It also supported license plate recognition and inspection checks for large construction vehicles entering or exiting the area.

*Environmental and Material Monitoring

Environmental algorithms detected exposed soil piles, monitored materials placed around the site, and identified excessive dust generation, providing early awareness of conditions that could affect safety or regulatory compliance.

*Safety and Hazard Prevention

The system provided early detection of fire or smoke, liquid leaks from machinery or pipelines, and unauthorized intrusion into hazardous or restricted zones. These capabilities supported quicker awareness of safety hazards and strengthened overall site protection.

*Specialized Equipment Monitoring

For equipment such as tower cranes and cargo elevators, algorithms monitored parameters including amplitude, lifting height, rotation angle, door status, load conditions, and the presence of people or obstacles. These models supported safer operation of high-risk machinery.

2.2 Real-Time Event Detection and Alert Delivery

With analysis performed directly at the edge, the AI Box identified unsafe behaviors and hazardous conditions the moment they occurred and automatically pushed alerts to supervisors through AVCiT’s distributed platform.

2.3 Efficient Scalability as the Site Expands

As construction progressed, additional monitoring points were required. AI Box  could be installed with minimal setup, allowing the network to scale easily alongside project milestones. This kept the system adaptable and made it simple to extend coverage as new structures, access points, or temporary work areas were introduced.

2.4 Reliable Monitoring Through a Distributed Design

The distributed architecture of the AI Box reduced dependency on a single processing point. Video analysis occurred locally on each node, and the system continued functioning even if individual devices experienced temporary downtime. This helped maintain stability during busy periods, network disruptions, or changes to the site layout.

2.5 Seamless Integration with Other Technologies

AVCiT's AI Box operated alongside other digital systems on the construction site, allowing data from multiple sources to be combined and reviewed together. Its IP-based design made it flexible and easy to integrate, and the consolidated information supported supervision and safety management across different phases of the project.

Collectively, these functions ensured reliable and effective monitoring across all stages of construction and directly contributed to the results observed by the end of the project.

3. Outcomes Observed in the AVCiT HQ Project

3.1 Improved Accuracy in Safety and Activity Classification

The use of AI Box enabled more consistent and precise detection of safety-related behaviors and vehicle activity. Automated classification reduced the variability associated with manual observation, resulting in a clearer understanding of the site's conditions. This improved accuracy supported more reliable incident identification and contributed to a more stable safety-management process.

3.2 Faster Response to On-Site Risks

Real-time analysis at the edge allowed supervisors to receive alerts immediately when unsafe actions or hazardous conditions were detected. Earlier notifications supported quicker intervention and reduced the likelihood that minor issues would develop into more significant events. This benefit was observed across multiple stages of the construction timeline, particularly during periods of high activity.

3.3 Increased Operational Efficiency

By reducing the need for routine manual checks, the system allowed personnel to focus on higher-value tasks. Automated monitoring also supported more efficient allocation of supervisory resources as the site expanded. The decreased dependence on manual supervision contributed to smoother day-to-day operations and helped maintain better oversight during peak work periods.

4. Conclusion

As construction environments continue to evolve and adopt more digital technologies, edge-based AI systems offer a practical way to enhance visibility, support quicker on-site decision-making, and maintain stable operations across complex project phases.

The deployment of AI Box during the construction of AVCiT's new headquarters demonstrated the value of distributed AI edge computing in supporting real-time safety oversight and operational coordination. The system provided consistent monitoring across a large and frequently changing site, improved the speed and precision of hazard detection, and helped streamline routine supervisory tasks.

Discover how edge-based intelligence can improve visibility, responsiveness, and safety performance on complex worksites. Reach out to AVCiT to explore how our AI Edge Computing platform can assist your operations.

· Email: inquiry@avcit.com

· Phone: +86-20-8930-1184

· LinkedIn: AVCiT Technology

· YouTube: www.youtube.com/@avcittechnology

>