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ARTIFICIAL
INTELLIGENCE
Can Help Save the Planet
Ways4
As the scale and urgency of the economic and human health
impacts from our deteriorating natural environment grows,
we have an opportunity to look at how AI can help transform
traditional sectors and systems to address climate change,
deliver food and water security, build sustainable cities, and
protect biodiversity and human wellbeing.
SMART AGRICULTURE
AND FOOD SYSTEMS
The most popular applications of AI in Indian
agriculture:
- Crop and Soil Monitoring – Companies are
leveraging sensors and various IoT-based technologies
to monitor crop and soil health.
- Predictive Agricultural Analytics – Various AI and
machine learning tools are being used to predict the
optimal time to sow seeds, get alerts on risks from pest
attacks, and more.
THE DIGITAL EARTH
A real-time, open API, AI-infused, digital geospatial
dashboard for the planet would enable the
monitoring, modelling and management of
environmental systems at a scale and speed never
before possible – from tackling illegal deforestation,
water extraction, fishing and poaching, to air
pollution, natural disaster response and smart
agriculture.
SMART DISASTER
RESPONSE
Machine learning approaches such as predictive
analytics can also analyze past events to identify
and extract patterns and populations vulnerable to
natural calamities. A large number of supervised
and unsupervised learning approaches are used to
identify at-risk areas and improve predictions of
future events.
Machine learning and other data science
approaches can also assist the on-ground relief
teams after the actual emergency. 
NEXGEN WEATHER AND
CLIMATE PREDICTION
In just over a decade, computational power and
advances in AI will enable home computers to have
as much power as today’s supercomputers,
lowering the cost of research, boosting scientific
productivity and accelerating discoveries.
AI techniques may also help correct biases in
models, extract the most relevant data to avoid
data degradation, predict extreme events and be
used for impacts modelling.
Blog - blog.tyronesystems.com
Facebook - www.fb.com/tyronesystems
THANK YOU!

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4 Ways Artificial Intelligence Can Help Save the Planet

  • 2. As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
  • 3. SMART AGRICULTURE AND FOOD SYSTEMS The most popular applications of AI in Indian agriculture: - Crop and Soil Monitoring – Companies are leveraging sensors and various IoT-based technologies to monitor crop and soil health. - Predictive Agricultural Analytics – Various AI and machine learning tools are being used to predict the optimal time to sow seeds, get alerts on risks from pest attacks, and more.
  • 4. THE DIGITAL EARTH A real-time, open API, AI-infused, digital geospatial dashboard for the planet would enable the monitoring, modelling and management of environmental systems at a scale and speed never before possible – from tackling illegal deforestation, water extraction, fishing and poaching, to air pollution, natural disaster response and smart agriculture.
  • 5. SMART DISASTER RESPONSE Machine learning approaches such as predictive analytics can also analyze past events to identify and extract patterns and populations vulnerable to natural calamities. A large number of supervised and unsupervised learning approaches are used to identify at-risk areas and improve predictions of future events. Machine learning and other data science approaches can also assist the on-ground relief teams after the actual emergency. 
  • 6. NEXGEN WEATHER AND CLIMATE PREDICTION In just over a decade, computational power and advances in AI will enable home computers to have as much power as today’s supercomputers, lowering the cost of research, boosting scientific productivity and accelerating discoveries. AI techniques may also help correct biases in models, extract the most relevant data to avoid data degradation, predict extreme events and be used for impacts modelling.
  • 7. Blog - blog.tyronesystems.com Facebook - www.fb.com/tyronesystems THANK YOU!