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Japanese railway and Nokia collaborate on AI-based crossing trials

Odakyu Electric Railway is using Nokia’s scene analytics to detect abnormal events by applying machine-learning-based AI to images generated by railroad crossing cameras.

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Machida City in Tokyo is the site of the crossing trial
Machida City in Tokyo is the site of the crossing trial

Japanese private rail operator Odakyu Electric Railway has partnered with Nokia to carry out artificial-intelligence-based railroad crossing safety trials.

 

The pilot, which is underway at Tamagawa Gakuenmae No 8 railroad crossing in Machida City, Tokyo, will be conducted throughout March 2020. Odakyu is using Nokia’s SpaceTime scene analytics to detect abnormal events by applying machine-learning-based artificial intelligence to images generated by conventional railroad crossing cameras.

 

Edge computing resources

 

According to Nokia, by analysing available image feeds, scene analytics identifies potential issues in real-time. Running on edge computing resources, it can also greatly reduce required bandwidth at remote sites, which may have limited connectivity.

 

Odakyu Electric Railway has 229 crossing points across 120km of rail track, with 137 radar systems for object detection.

 

“Odakyu Electric Railway is renowned for being an early adopter of new technology and this trial illustrates the role that AI can play in delivering enhanced levels of vigilance,” John Harrington, head of Nokia Japan.

 

“This is a critical milestone for Nokia to help contribute not only to railway safety improvement but also to decrease operational costs and enhance performance.”

 

SpaceTime scene analytics, which was developed by Nokia Bell Labs, is also capable of providing real-time alerts for unauthorised entry into remote facilities.

 

“Network-connected cameras are one of the most prolific sources of IoT data that can provide valuable insights to help promote high safety standards.”

 

Nokia said it can detect and alert supervisors when personnel or equipment access unsafe locations in industrial settings or when heavy machinery is out of position creating a potential hazard.

 

“Network-connected cameras are one of the most prolific sources of IoT data that can provide valuable insights to help promote high safety standards,” Harrington added.

 

“By running machine learning analytics on camera feeds, and sending solely relevant scenes and events to operators, the full benefits of video surveillance can be realised in a wide variety of settings – with rail crossings a particularly relevant use case.”

 

Nokia claims it has deployed more than 1,300 mission-critical networks with customers in the transport, energy, large enterprise, manufacturing, webscale and public sector segments around the globe.

 

The Nokia Bell Labs Future X for industries architecture seeks to provides a framework for enterprises to accelerate their digitalisation and automation journey to Industry 4.0.

 

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