Thursday December 12, 2019
Home Lead Story Indian Railwa...

Indian Railways to use artificial intelligence

Earlier, railways used a manual maintenance system

0
//
Indian Railways is one of the most important and controversial transport in India. Wikimedia Commons
Indian Railways is one of the most important and controversial transport in India. Wikimedia Commons

New Delhi. November 21, 2017:

Aiming to reduce the possibilities of signals failing, Indian Railways has undertaken remote condition monitoring of the system, a new approach for the national transporter, to predict failures through the effective use of Artificial Intelligence.

The Signalling system is vital for safe train operations and the railways completely depend on the health of its signalling assets along with real-time information.

Currently, the railways follow a manual maintenance system and adopt find-and-fix methods rather than predict-and-prevent approach.

“Now, we are introducing remote condition monitoring using non-intrusive sensors for continuous online monitoring of signals, track circuits, axle counters and their sub-systems of interlocking, power supply systems including the voltage and current levels, relays, timers,” said a senior Railway Ministry official involved with the project.

The system entails the collection of inputs on a pre-determined interval and sending this to a central location.

As a result, any flaws or problems in the signalling system would be detected on a real-time basis and rectified to avoid possible delays and mishaps.

The failure of signals is one of the major reasons for train accidents and delays.

Currently, remote monitoring of signalling is operational in Britain.

The system envisages data transfer through a wireless medium (3G, 4G and high-speed mobile) and data based on these inputs will be utilised, with help of Artificial Intelligence (AI), for predictive and prescriptive Big Data analytics.

This will enable prediction of signalling asset failures, automated self-correction and informed decisions on intervention strategies, said the official.

The railways have decided that trial is taken up in two sections of Western Railway and South Western Railway at Ahmedabad-Vadodara and Bengaluru-Mysuru.

Depending on the feedback, the system would gradually be extended to other sections. (IANS)

Next Story

AI-based Algorithm to Help Doctors Treat Traumatic Brain Injury

AI-based algorithm to treat brain injury developed

0
Artificial Intelligence brain
An AI-based algorithm will help doctors treat patients with severe traumatic brain injury (TBI). Pixabay

Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) based algorithm that could help doctors treat patients with severe traumatic brain injury (TBI).

The algorithms can predict the probability of the patient dying within 30-days with an accuracy of 80-85 per cent, said the study published in the journal Scientific Reports.

“A dynamic prognostic model like this has not been presented before. Although this is a proof-of-concept and it will still take some time before we can implement algorithms like this into daily clinical practice, our study reflects how and into what direction modern intensive care is evolving”, said Indian-origin researcher and study author Rahul Raj from Helsinki University Hospital in the Finland.

Traumatic brain injury is a significant global cause of mortality and morbidity with an increasing incidence, especially in low-and-middle income countries.

The most severe TBIs are treated in intensive care units (ICU), but in spite of the proper and high-quality care, about one in three patients dies.

Brain Injury
Traumatic brain injury is a significant global cause of mortality and morbidity. Pixabay

This is why researchers at Helsinki University Hospital (HUS) started to develop an artificial intelligence (AI) based algorithm that could help doctors treat patients with severe TBI.

At its best, such an algorithm could predict the outcome of the individual patient and give objective data regarding the condition and prognosis of the patient and how it changes during treatment.

“We have developed two separate algorithms. The first algorithm is simpler and is based only upon objective monitor data. The second algorithm is slightly more complex and includes data regarding the level of consciousness, measured by the widely used Glasgow Coma Scale score,” said study researcher Eetu Pursiainen.

As expected, the accuracy of the more complex algorithm is slightly better than for the simpler algorithm.

Also Read- Air Pollution Identified as a Life-threatening Illness: Study

“Still, the accuracy of both algorithms is surprisingly good, considering that the simpler model is based upon only three main variables and the more complex upon five main variables”, Pursiainen said.

In the future, the algorithms still have to be validated in national and international external datasets, the researchers concluded. (IANS)