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Climate Thesis

The 5 Verticals of AI Driven Climate Action

AI's potential to drive climate action in India spans across five key verticals, each of which can significantly enhance the country's environmental efforts. Efforts are bring undertaken in each of these verticals and have been charted by us below, to give the reader a better understanding of the Climate X AI landscape in India.

Boosting Climate data accessibility

Climate data can oftentimes be hard to navigate and make sense of. AI can democratise access to climate data, while making it more understandable and contextual to a wide range of stakeholders in India. By leveraging interactive visualisations, personalised reports, and user-friendly mobile applications, AI can bridge the accessibility divide in a diverse nation like India, where language barriers and varying levels of scientific literacy can hinder the dissemination of climate knowledge.

AI-powered agricultural advisory systems: Machine learning is being used to analyse local climate data, soil conditions, and crop patterns, providing farmers with personalised recommendations in their local languages via SMS or mobile apps. Examples of organisations doing this work in India:

Fasal⁠

Cropin ⁠

etc.

AQI monitoring and alert systems: AI is being used to process data from various sensors and satellite imagery and this is then translated into easy-to-understand air quality forecasts, accessible to citizens through mobile apps and public displays. Example of an organisations doing this work in India is the Indian Meteorological Department.

AI powered climate science education tools would help better visualise and understand better the impact of climate change, spreading awareness.

Synthesising large amounts of Data into actionable insights

The country's vast size, diverse ecosystems, and complex socio-economic landscape generate huge volumes of climate data from various sources. AI can parse through vast amounts of data and unearth patterns, providing actionable to decision and policy makers .

Emission Accounting: AI can monitor and capture the data generated across the value chains of businesses and calculate Scope 1, 2 and 3 emissions, identifying clear emission hotspots. This would unlock huge carbon saving opportunities for industries. Example of an organisation that does this work is

Net0⁠

⁠

Ecosystem Monitoring: AI can parse through huge amounts of data on ecosystem parameters such as tree cover, heat hotspots, wildlife count and providing actionable analysis. Take for example processing large amounts of satellite imagery to find deforestation hotspots as is currently being done by ISRO.

Satsure⁠

is another company that uses AI to monitor ecosystem.

Urban climate data analysis: AI can be used to analyse urban climate data and providing cities with actionable insights on improving their climate resilience. Examples of an organisation doing this work in India:

Enhancing the Accuracy of Predictive Modelling

Global Warming has triggered more intense clashes of weather systems in India resulting in more extreme weather phenomenon . This calls for more accurate predictive modelling.

AI based predictive models offer a promising solution as prediction can be made more accurately while improving the speed and cutting down costs involved.

Enhanced weather forecasting: AI can analyse vast amounts of meteorological data to provide more accurate and timely weather forecasts. Example of an organisation doing this is

Skymet⁠

Disaster prediction and alert systems: AI-powered systems can analyse patterns in weather data, seismic activity, and other environmental factors to predict natural disasters with greater accuracy. This can help authorities issue timely warnings and evacuate vulnerable areas. Example is the work done by the

Indian National Centre for Ocean Information Services (INCOIS)⁠

, who are developing AI-based models to improve tsunami early warning systems.

Climate finance and risk assessment: AI can help financial institutions and businesses assess and manage climate-related risks more effectively. Example of an org in this space is

Arthan Finance⁠

Optimising Complex Systems

AI can play a crucial role in optimising complex systems within India's climate sector, helping to address challenges and improve efficiency across domains. Here are some examples:

Smart Grid Management : AI can optimise electricity distribution in India's power grid, which is crucial given the country's increasing reliance on renewable energy sources. For example, AI algorithms can predict energy demand, manage load balancing, and integrate intermittent renewable sources like solar and wind more efficiently, helping reduce power outages and optimising energy use during peak demand periods. Example of orgs doing this is

Tata Power⁠

Schneider Electric India⁠

etc.

Water Resource Management: AI can help optimise water distribution and usage, particularly in drought prone areas like Tamil Nadu and Maharashtra. For instance, AI-powered systems can analyse data from sensors, weather forecasts, and historical patterns to manage reservoir levels, predict water demand, and detect leaks in distribution systems. Example of orgs doing this in India are

Cranberry Analytics⁠

Wegot⁠

etc.

Transportation and Emissions Reduction: AI can optimise traffic flow in congested cities like Delhi, reducing idle time and lowering emissions. For instance, AI-powered traffic management systems can adjust signal timings in real-time based on traffic patterns and air quality data, helping to reduce both congestion and pollution. Example of an orgs doing this in India is

Siemens Mobility.⁠

⁠

Furthering scientific progress in climate science

By leveraging AI technologies, India can enhance its climate research capabilities, improve decision-making, and develop more effective strategies for mitigation and adaptation.

A summary of Use-cases vis-a-vis our Focus Areas

Data First Agriculture ☘️ || Making Sustainability Accessible and Rewarding for Businesses 🏭 || Building disaster resilient communities 🌊

BOOSTING CLIMATE DATA ACCESSIBILITY

DATA INTO ACTIONABLE INSIGHT

ACCURACY OF PREDICTIVE MODELLING

OPTIMISING COMPLEX SYSTEMS

AI-powered agricultural advisory systems

☘️

Emission Accounting

🏭

Enhanced weather forecasting

☘️ 🌊

Smart Grid Management

AQI monitoring and alert systems

☘️. 🌊

Ecosystem Monitoring

☘️ 🏭 🌊

Disaster prediction and alert systems

🌊

Water Resource Management

☘️ 🌊

AI powered climate science education tools

☘️ 🏭 🌊

Urban climate data analysis

🌊

Renewable Energy Forecasting

Transportation and Emissions Reduction

🏭

There are no rows in this table

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The 5 Verticals of AI Driven Climate Action

Boosting Climate data accessibility

Synthesising large amounts of Data into actionable insights

Enhancing the Accuracy of Predictive Modelling

Optimising Complex Systems

Furthering scientific progress in climate science

A summary of Use-cases vis-a-vis our Focus Areas

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