Pune-based Safe Cams has launched a Driver monitoring system working via Dash Cams for cars. This feature has been enabled in three products that the company sells in India - the SC200 AI, SCDS02, SC400. The SC200 AI and SC400 models can also be configured without the driver safety monitor cameras while the SCDS02 is exclusively built for driver safety monitoring purposes. These cameras leverage machine learning and computer vision technologies which are types of AI technologies to make sure the driver is paying attention to the road.
The Driver Safety Monitoring system has been designed to alert the driver whenever there are signs of drowsiness or any kind of distractions are detected using its dangerous driving behaviour warning mechanism.
"These DSM cameras have been developed by us based on extensive R&D done through open-source facial and gesture recognition software, which our team later modified to identify for specific markers such as eyes being closed, yawning, eyes not facing front, among others. A lot of time was spent by us in terms of training the AI to recognise these markers/triggers, as we wanted to ensure we were able to obtain a 98-99% accuracy rate on all our devices. We have decided to primarily market and sell the DSM-enabled devices to long-haul, high-value truck owners of India, who can see a quicker return on investment from our devices. We are also seeing interest from the local and state governments for this technology, and are in talks with companies involved in rapid-transit bus services. We are hoping that if our DSM cameras can be fitted to public transport services at scale, the risk of accidents occurring could be minimised dramatically," said Vanesh Naidoo, founder and CEO of Safe Cams Digital Eye.
It has been noted that around 11 per cent of all road accidents happen in India worldwide. Safe Cams hopes the launch of these driver safety monitors will enable some semblance of safety and cognisance which will help reduce accidents on the road.
A lot of the technology is based on computer vision which does facial tracking, eye tracking and having ambient awareness. Some salient features of the system include the following:
- A driver fatigue alarm detects if the driver's eye has been closed for between 1 and 3 seconds.
- A driver distraction alarm will take a look at the facial and head position to know if the driver is paying attention to the road.
- A smoking alarm will trigger an alert if the driver is smoking.
- Perhaps the most used alarm will be the one for mobile phone use. For this, the system uses gesture recognition.
- It will also trigger an alarm if it can't find facial features in the case no one is on the wheel.
- It also has a driver ID alarm identifying the driver. If there is a discrepancy an alarm will be triggered.
- There is also a speeding alarm that will trigger when the car crosses the speed limit using GPS data.
The cameras are connected over the cloud via a 4G network - they can also be handed to control centres of any fleet company to enable the management to monitor its own drivers.
