Setting India up for a successful AI and EV future

Collaboration at every stage and the integration of multiple stakeholders to build solid ecosystems will be the basis for Indian society and its businesses to derive value from these technologies

Published: 10, Jul 2018

Sanjeev Sharma is the managing director of ABB India

Shutterstock
Shutterstock

We live in interesting times. Clean energy-fueled electric race cars are giving their Formula 1 counterparts a run for their money. Robots no longer just take commands, they can even be taught to conduct a symphony orchestra in 14 short hours. The journey has started well in such technologies like electric mobility and artificial intelligence (AI).

But how will a country of more than a billion people reap the inclusive benefits of these tools and address relevant issues in deploying them? Collaboration at every stage and the integration of multiple stakeholders to build solid ecosystems will be the basis for Indian society and its businesses to derive value from these technologies.

More, better, together
When it comes to electric vehicles there are four key things that need to be interlinked to drive success -- the availability of cost-effective vehicles, charging stations, a strong grid and the integration of renewable energy. OEMs, charging companies, and battery manufacturers need to come together to offer more options and seamless delivery of services to end-users.

A strong grid is imperative to support the energy needs of such a massive electric mobility program. Coordination becomes more important as China and India, unlike the West, have created a bottom-up model for EVs, targeting public transportation first.

Utilities, technology providers and government agencies need to be in constant coordination to address issues like divergence in energy, load capacity and issues of local capacity sizing at the distribution transformer or substation level. Structuring tariffs based on time of day pricing and location of charging demand and signaling also require a strong interplay between stakeholders.

Collaboration will be the cornerstone of success in a complex network of multiple agencies, with the backing of a robust grid. Renewable energy requires another degree of collaboration so that it isn’t a mere shift from one kind of fossil fuel to another – like oil to coal – but the adoption of clean energy at every stage. Integrating renewable energy and clean energy technologies is a specialised area, which has offerings at different levels from storage to integration, power quality, reliable data analytics, load balancing and forecasting, etc. Hence it is important for such niche companies to work together.

Interconnectivity of the digital kind is also a must for cloud-connected charging stations. These connections enable smart planning for travelers by indicating the location of the next charging station. For operators, it helps them perform key functions like combining remote monitoring and configuring, servicing equipment, flexibility to connect to any charging network, energy management, etc.

A focus on any one factor, while ignoring the others might pose challenges to long-term sustainability.

AI joining the dots for a stronger foundation
Artificial intelligence has become the new buzzword in India. AI will play a critical role in developing concrete, scalable solutions across utilities, industry, infrastructure and transportation. In addition, a key factor would be using AI to solve social issues in sectors like healthcare, education and agriculture. Balancing commercial initiatives and national strategies that benefit the majority would be crucial. This would require a holistic platform where the government, public and private companies, platform integrators and technical institutes collaborate to address pressing issues like data collection, analytics and security while adapting to AI.

The rich mix of AI application ranging from shop floors to agricultural fields, has to be supported by an ecosystem robust enough to nurture all kinds of projects. As increasing customisation makes production lines smarter, no matter the scale, it is important to not perceive AI in isolation, but as a progression of levels of automation, digitalisation, and machine or deep learning.

Every level of progression comprises of individual discrete layers of significance and connections. Skipping one layer might make the foundation of the super-structure rather unstable. These interconnections will also help broaden the base of AI application and provide requisite training to small, medium and large organisations to realise the potential of AI in a graded and gradual manner.

The foundation of AI is reliable, high quality data and good connectivity, since the quality and type of learning will depend on the collected data. This is where a lot of companies will struggle, making the need for cooperation critical. We have to collaborate on solutions and the industry needs to come together to create a common database of best practices for everyone to learn from. We need to work together to learn and address issues that arise in deploying cutting-edge technology, but most importantly, create a customised and flexible model of awareness and skill development to optimise these technology applications for our nation.

In times to come, these technologies can then become the drivers for key national initiatives be it Make in India, Skill India, enhancing farm productivity, providing access to reliable energy and infrastructure by driving the fourth industrial revolution.

The author is managing director of ABB India.

Post Your Comment
Required
Required, will not be published
All comments are moderated
Prev
Intelligence on the edge: What does the future hold?
Next
Click fraud: A bane of contention in the digital ad ecosystem