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Artificial Intelligence Lesson-6 Presented By: Roman Saini
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In This Lesson Artificial Intelligence Focus areas for Al intervention In India (Cont'd) Key Challenges To Adoption Of Al In India Recommendations By NITI Aayog
Artificial Intelligence (Al) Smart Mobility and Transportation Mobility and transportation form the backbone of the modern economy due to their linkages with other sectors and importance in both domestic and international trades. Today's society demands a high degree of mobility of various kinds, so as to enable efficient and safe transportation of both people and goods. As a major contributor to overall emissions, this sector must also be sensitive to ideas of environmental sustainability. In India, majority of both passenger and freight traffic is carried through roads and railways.
Artificial Intelligence (AI) As the economy grows, it is expected that this reliance on these modes of transport shall continue unless there are major shifts in the policy initiatives in the area. The fact that these modes of transport are particularly pollution intensive compared to shipping and air transport, further increase the need to implement smart practices in their deployment. The Indian transportation sector faces a variety of issues: .Congestion and road accidents . High number of traffic deaths . Lack of public transportation infrastructure
Artificial Intelligence (Al) The major applications of Al on the mobility front beyond autonomous cars: Autonomous trucking: Autonomous technology in trucking has the potential to transform the way we move goods today. Al can help increase safety and hauling efficiency through intelligent platooning, wherein trucks form platoons giving drivers the liberty to rest while the platoon keeps moving. Intelligent Transportation Systems: The use of Al, real time dynamic decisions on traffic flows such as lane monitoring, access to exits, toll pricing, allocating right of way to public transport vehicles, enforcing traffic regulations through smart ticketing etc. can be made. Al could help to design sophisticated urban traffic control systems that can optimise signal timings at the intersection, zonal and network level
Artificial Intelligence (Al) Travel route/flow optimisation: With access to traffic data at the network level, Al can help make smart predictions for public transport journeys by optimising total journey time including access time, waiting time and travel time. Al can revolutionise first-last mile travel which could change the way we perceive public transport journeys, today. . About private car usage, Al could utilise a range of traffic data sets and one's own preferences to make human-like decisions on route selection. . Al for Railways: Train operators can obtain situational intelligence through real time operational data and analyse them in three different dimensions: spatial, temporal and nodal.
Artificial Intelligence (Al) Fleet management and asset maintenance including that of rolling stock are pertinent Al use cases. . Recently, the Ministry of Railways, Govt. of India has decided to use Al to undertake remote condition monitoring using non-intrusive sensors for monitoring signals, track circuits, axle counters and their sub-systems of interlocking, power supply systems including the voltage and current levels, relays, timers. Community Based Parking: The availability of parking is a major issue for Indian cities. Al can help optimise parking, likely by minimising vehicle downtime and maximising driving time With the advent of electric vehicles, Al will be needed to mediate the complex vehicle grid interactions (VGI) as well as for charging optimisation
Artificial Intelligence (Al) Key challenges to adoption of Al in India the challenges are concentrated across common themes of: Lack of enabling data ecosystems Low intensity of Al research Core research in fundamental technologies Transforming core research into market applications Inadequate availability of Al expertise, manpower and skilling opportunities High resource cost and low awareness for adopting Al in business processes .Unclear privacy, security and ethical regulations .Unattractive Intellectual Property regime to incentivise research and adoption of Al
Artificial Intelligence (Al) Framework for promoting Artificial Intelligence Research in India The Detailed Project Report of Inter-Ministerial National Mission on Interdisciplinary Cyber Physical Systems (IM-ICPS) has suggested the following four-tier framework for promoting research focused on all aspects of technology life-cycle: research, technology deployment, translation and management: a) ICON (International Centres of New Knowledge): focusing on creation of new knowledge through basic research, b) CROSS (Centre for Research On Sub-Systems): focusing on developing and integrating core technologies developed at ICON layer and any other sources c) CASTLE (Center for Advanced Studies, Translational research and Leadership): focusing on development and deployment of application based research and d) CETIT (Centre of Excellence in Technology Innovation and Transfer): focusing on commercialisation of technologies developed
Artificial Intelligence (Al) To encourage the development of sustainable Al solutions at an appropriate price point for sectors such as health, education, and agriculture, it is necessary that a level playing field be ensured and a supportive environment be created for all players in the value chain. .A multi-pronged approach, involving various stakeholders and promoting a collaborative approach is required for promoting development of Al tools as well as adoption of Al in different fields of activity. Incubation hubs specifically for Al startups need to be set up to provide space, and other infrastructure facilities for new startups. Establishment of fund to provide grant funding to startups to facilitate their operation and business.