In-cabin monitoring in public transport. The next big thing

In-cabin monitoring in public transport. The next big thing?

Are in-cabin monitoring systems in public transport the next big thing?

Compared to driver-state monitoring systems (DMS), or even occupant monitoring systems (OMS) for which we have experienced huge advances in terms of safety regulations and technology in recent years, the approach to in-cabin monitoring systems for public transport is relatively recent but closer than many might think.

Potential legislation - Again a matter of in-vehicle safety

Once again, security is in the spotlight for these new interior monitoring use cases, but this time new variables enter the scene: autonomous public transport systems, new smart public transport solutions, and the behaviors of the occupants when using these transports.

Fully autonomous transportation solutions are scaling quickly:

  • The demand for autonomous public transportation that only carries passengers is increasing (metros, trains, shuttles).
  • Analysts’ predictions regarding the future of large-scale use of autonomous robo-taxis and robo-buses.

New public transportation services:

  • Sporadic pay-as-you-drive vehicles where there is no vehicle owner, or in other words, there is no person in charge. 
  • Driver-for-rent services where passengers are unknown.

All these new urban and interurban public transportation solutions add new challenges for the safety of both the occupants and the operation of the vehicle itself. This means that, in the same way, that it already applies to driver monitoring systems, it is a matter of time before this regulation is extended and applied to public transport with the aim of guaranteeing the safety of the occupants, the protection of the vehicle from occupant’s improper use or external threats.

In-cabin monitoring for public transport: use cases

Safety for all occupants and vehicle, not just the driver (there may be no driver at all!):

Occupant safety and security monitoring

  • Person detection: Seat occupancy, seat belt detection, people counting.
  • Child detection: Abandoned child, child seat, and seatbelt detection.
  • Equipment detection: Person with or without a mask, safety vest, and other wearables.
  • Behavior detection: Smoke detection, violent or antisocial behavior.
  • Pet, object, and event detection: Pets detection, fire detection, abandoned backpacks or other suspicious objects, threat detection.

Vehicle safety and use

  • Special, adapted, and other devices detection: Wheelchair, pram, electric scooter, bicycle.
  • Improper behavior and use detection: smoking, littering, weapons or other dangerous objects, alcohol, vandalism, and nudity.

Data and compliance to (potential) legislation

New in-cabin monitoring systems for public transportation will bring huge data challenges for in-vehicle technology developers and current monitoring systems. They need to accurately and reliably monitor passengers in environments much larger than a car’s cabin, with more people and more possible events. Add to this the well-known challenges of gathering data provoked by worldwide issues around data privacy and consent, data variability and bias, or simply data that is impossible to find in the real world in order to build a legislation-compliant system. Data needs will skyrocket!

And you, how do you plan to generate all the data required for designing, training, and system fine-tuning without spending the budget of your company for the next 10 years?

About Anyverse

Anyverse™ is the hyperspectral synthetic data generation platform for advanced perception that accelerates the development of autonomous systems and state-of-the-art sensors capable of supplying and covering all the data needs throughout the entire development cycle. From the initial stages of design or prototyping, through training/testing, and ending with the “fine-tuning” of the system to maximize its capabilities and performance.

Anyverse™ brings you different modules for scene generation, rendering, and sensor simulation, whether you are:
– Designing an advanced in-cabin perception system
– Training, validating, and testing in-cabin systems AI, or
– Enhancing and fine-tuning your in-cabin perception system,
Anyverse™ is the right solution for you.

The data you generate with Anyverse™ helps you build a robust in-cabin monitoring system capable of sensing a wide variety of drivers ready to operate under any circumstance, identifying driver and occupants’ state and behaviors, detecting driver distraction, fatigue, unresponsive drivers, and much more.

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