I often feel Artificial Intelligence (AI) is still directionless although we do see a lot of Work In Progress (WIP). AI in transportation is not just about autonomous aircrafts, cars, trucks and trains. There is much more that can be done with AI. Recently IBM helped to create an app that would use Watson Visual Recognition to inform travelers about congestion on London bus routes. In India, the state transport corporation of Kolkata took a technological leap by deploying artificial intelligence to analyze commuter behavior, sentiment, suggestions and commute pattern. This deployment is identical with what Indian cab aggregators Uber and Ola have been doing for quite a few years now.
BOT, the AI technology being used by West Bengal Transport Corporation (WBTC), will receive the inputs from commuters via Pathadisha, the bus app that was introduced to analyze inputs and then provide feedback to both passengers and officials in WBTC to suggest future improvements in the service. Furthermore this app has a simple driver and conductor interface that will enable commuters to know whether there a seat is available in a bus or one has to stand during the journey. This input is expected to work on a real-time basis. A simple color band will indicate the seat status: green means seats are available, amber if seats are occupied and red if the bus is jam-packed.
AI is expected to make our travel smoother and more efficient. User and Entity Behavior Analytics (UEBA), Advanced Health Analytics along with Machine Learning (ML), Deep Learning (DL) will be extensively used by Internet of Things (IOT) in predictive analytics and availability of real-time inputs. In the most recent developments AI is predicting whether public bus drivers are likely to have a crash within three months. If the prediction is ‘yes’, they are sent for training. In the future AI along with IOT will replace drivers and create more opportunities for humans in real-time transportation control and governance.
AI could also help us detect to find emergencies during travel. Aircrafts, buses and trains could be fitted with cameras capable of biometric analysis that observe the facial expressions of passengers. This data could provide real-time input on their safety and well-being. Israel’s Tel Aviv-headquartered Beyond Verbal which was founded in 2012 on the basis of 21 years of research, specializes in emotions analytics. Its technology enables devices and applications to understand not just what people type, click, say or touch, but how they feel, what they mean and even the condition of their health. Another promising start-up from Tel Aviv, Optibus has a commendable dynamic transportation scheduling system which uses big-data analytics to dynamically adjust the schedules of drivers and vehicles to improve passenger experience and distribution of public transportation. Optibus technology is field-proven on three continents and received the European Commission’s Seal of Excellence.
One could easily build a superior transportation system with AI and its subsets. Very soon AI and IOT will dictate road traffic signals based on real-time inputs, study road conditions, provide data on the quality of air and add a thousand more functions to its capabilities. IOT will further add value to in-house travel experience in public transport. It will host a lot of features and additions that were unthought-of before. There is no need to go to the pantry of a train to order your food or look for the menu or even get down on the next station and rush to book your next ticket when everything can be done on your wrist-watch, mobile phone or an internal digital console.
Some of the AI deployments we might get to see in lesser than a decade are autonomous driving, data-driven preventive maintenance, powerful surveillance and monitoring systems for transportation and pedestrians, sustainable mobility, advanced traveler infotainment systems and services, emergency management systems, transport planning, design and management systems and at last but not the least, environmental protection and quality improvement systems.
Besides its economic, social, and environmental importance, AI needs a world that controls its human numbers. One cannot afford to allow countries to overpopulate and cause a threat to our own welfare. We live with limited resources and much limited renewable resources. AI promises to play a major role towards a better quality of life and this can only happen with a lesser number of human beings. AI badly needs global governance on all fronts right from conceptualization to implementation.