Automated Helmet Detection

For Reliance Petroleum Limited, we built an AI-powered automated helmet detection system using computer vision technology. The software is built with deep learning algorithm that has been trained on traffic camera footage to detect people wearing a helmet and those who are not.


Reliance Petroleum Limited is a company owned by Reliance Industries Limited, one of India's largest private sector companies. With a strategically located network of 1380+ retail outlets spread across the country, the retail business provides value to its customers through a 100% automated network, backed by superior technology.


According to a recent survey, 1214 road crashes occur every day in India. Two-wheelers account for 25% of the total road crash deaths. Deaths of two-wheeler riders in crashes have more than doubled in a decade, between 2009 and 2019. Even though two-wheelers offer the least protective features for their occupants, they have become popular for being the most affordable and easiest mode of transport.

Our client, with a large network of retail outlets spread across the country, wanted to encourage two-wheeler drivers to wear helmets to ensure their safety. The company designed several incentive programs for its customers who regularly wear helmets in two-wheelers. Manually recording vehicle numbers of customers wearing helmets is not a feasible option in busy gas stations. Hence, the client wanted to automate the process of detecting helmet-wearing riders.


Based on the business requirements, we built an AI-powered automated helmet detection system using computer vision technology.



The software is built with deep learning computer vision algorithms that have been trained on traffic camera footage to detect people wearing a helmet and those who are not. The algorithm is capable of detecting people, motorcycles, and helmets. This pipeline is designed to flag alerts when a violation is found. If a person riding a two-wheeler is identified as not wearing a helmet, then the image of the vehicle is captured and stored in a database. Daily or weekly status reports or violation logs can be generated from the database using a central dashboard. One key feature of the system is its near real-time performance achieved by a highly optimized software stack developed for Intel-based hardware.

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Frequently Asked Questions

What are the benefits of automated helmet detection systems?

The benefits of implementing automated helmet detection systems are as follows:

  • Enhanced Safety: Automated helmet detection systems improve safety by identifying individuals without helmets in settings where they are required or recommended, such as construction sites and sports arenas.
  • Prompt Intervention: These systems enable quick action by alerting personnel or triggering automated responses when someone is detected without a helmet, leading to timely enforcement measures.
  • Efficient Monitoring: Automated systems use advanced technology to monitor helmet compliance accurately, reducing the need for manual monitoring and improving accuracy.
  • Deterrence Effect: The presence of automated systems deters individuals from disregarding helmet requirements, as they know their actions will be detected and recorded.
  • Data Analytics & Insights: These systems generate valuable data on helmet usage, allowing administrators to identify patterns, make informed decisions, and develop targeted interventions.
  • Cost-Effectiveness: While the initial investment may be high, automated systems help organizations save costs by preventing accidents, injuries, and the need for constant manual monitoring.
  • Increased Productivity: Automated helmet detection systems increase productivity by reducing the time and effort required for manual monitoring. Moreover, this allows personnel to focus on other important tasks, improving overall efficiency in the monitored environment.
  • Compliance Monitoring & Reporting: These systems provide comprehensive records and reports on helmet compliance, offering organizations valuable insights into adherence to safety regulations. This data can be used for audits, compliance monitoring, and demonstrating regulatory compliance to relevant authorities or stakeholders.

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Helmet detection

Deep learning technology

Automated number plate detection

Trained using traffic camera footage

Technologies Used