ALPR for Road & Perimeters Security
Case Study: ALPR (Automatic License Plate Recognition), Road Safety And Perimeter Security Systems.
Background:
In the fast-paced telecommunications industry, ensuring the safety of workers during the construction and maintenance of tower infrastructure is paramount. A leading tower company, which specializes in erecting and leasing tower structures to telecom operators, aimed to elevate its safety protocols. To achieve this, they turned to innovative AI technology and partnered with us to deploy a state-of-the-art solution.
The Challenge:
SAIL is a public sector undertaking owned by the Ministry of Steel, India. The client wanted to enhance the security, safety and operational efficiency at the Rourkela Steel Plant by implementing video analytics solutions within its premises. One demand was to implement an automated vehicle license plate recognition system using the existing CCTV network at the plant to capture and analyze number plates in real-time.
The client also needed a video analytics system that could integrate with the CCTV system to recognize traffic light violations at key intersection within the plant premises. To ensure a high standard of security, the client also wanted an AI-automated system to detect unauthorized intrusions at the plant perimeter, and a gas leak detection system as well.
The Solution: RedX AI Automation Platform:
By leveraging computer vision, video analytics and advanced AI algorithms, we provided the client with a data-driven, real-time monitoring system to extract valuable insights from CCTV cameras, video footage, and sensors.
Impact & Results:
The deployment of the RedX platform transformed safety monitoring from a manual, error-prone process to an automated, efficient, and reliable system. The ground-based human tracing cameras provided comprehensive coverage of the site, enabling real-time detection and alerts for any safety gear non-compliance.
This not only streamlined the monitoring process but also significantly enhanced the safety culture among workers. The tower company experienced a marked reduction in safety incidents and non-compliance, highlighting the effectiveness of integrating AI technology into safety protocols.
Conclusion:
The integration of RedX at the tower company’s construction sites has set a new industry standard for safety and efficiency. This case study exemplifies our dedication to harnessing AI for meaningful applications, ensuring safer work environments, and leading the charge in technological innovation within traditional sectors.
This case study highlights our commitment to improving workplace safety through technological innovation, demonstrating how AI can be leveraged to make traditional industries safer and more efficient.