Can AI Save "The Planet"?

 

The Answer is, YES!

AI can sustain the delicate balance in the Nature: Conserving Ecosystem.  

AI and Environmental Sustainability

In recent years, artificial intelligence (AI) has become a prominent topic of conversation. Advances in other frontier technologies, such as cloud computing, big data, the Internet of Things (IoT), and virtual reality, have led to some major breakthroughs in artificial intelligence. Aside from the financial and societal benefits of AI applications, the technology is also set to revolutionize environmental sustainability.

 

Scientists argue that one of the main challenges to environmental sustainability is understanding how the ecosystem works, given the number and complexity of interactions within it. The amount of information available is simply too large to be analyzed by the human brain or traditional statistical tools. Using advanced tools and technologies can help us understand the impact of the ecosystem on us and vice versa. Sensors enable the collection of large amounts of data, while AI can help analyze this data and build models to help navigate these complexities and make agile decisions in uncertain and volatile conditions.

 

Impact of AI on the ecosystem and environmental management:

Technologies such as AI and IoT are expected to drive progress in most areas of ecology and biodiversity research, as well as environmental and ecosystem management.

 

Motion-sensing cameras can collect very large amounts of biodiversity data

Motion-detector cameras enable the low-cost and widespread collection of massive amounts of biodiversity data. 

  

Drones equipped with AI technologies can fight deforestation and poaching

The use of drones equipped with AI technology can help reduce deforestation and poaching.  

 

Impact of AI on Water Management

Although AI applications are limited to select cases in the operational water sector, machine learning algorithms are increasingly being used in water science. 

 

Internet of Things, machine learning, and blockchain can be combined to support urban water management

The Internet of Things, machine learning, and blockchain technology can all be used to improve urban water management. Using these three technologies can improve service provision and quality while protecting the sustainability of water resources. Smart water systems, which use an Internet of Things-based approach, are gaining traction in urban water resource management. These smart systems are composed of a network of physical devices (such as the flow meter), a sensor that records data (such as water amount and quality, pictures, etc.), and a communication device that transmits this data in real time to a cloud-based server. Smart water systems improve efficiency and reliability while reducing costs.

 

Impact of AI on Disaster Risk Reduction

AI to improve climate change assessment

Studying the climate and identifying high-risk areas require large amounts of data, ranging from images to sensor data. Machine learning algorithms can help mitigate and manage climate change effects by improving the accuracy of global climate models and predictions. For instance, extreme weather events such as wildfires and hurricanes can be predicted by analyzing data from satellite images and weather station data in real-time.  

 

Impact of AI on Agriculture

AI-based solutions can enhance efficiency in the agricultural sector in practices such as crop yield, irrigation, soil content sensing, crop monitoring, weeding, and crop establishment. AI-based technological solutions can enhance the sector’s resource efficiency by reducing the use of land, water, fertilizers, and pesticides while also enhancing output quality and ensuring a faster time to market for produced commodities.

 

Smart Farming

Using drones, cameras, and sensors along with AI to scan plantations and detect pests, identify areas that are either excessively or poorly irrigated, and intervene more quickly eliminating the need for expensive and fuel-polluting helicopters to monitor the fields. Robots or drones can help with field inspection and early detection of crop diseases, making the process more effective and ensuring future food security. Weed control can also be significantly enhanced using solar-powered robots that can detect weeds and pull them out mechanically (without chemicals). All these developments are providing farmers with the tools to observe, measure, and analyze the needs of their farms, allowing for improved resource management while reducing environmental impact and waste.

 

Conclusion:

The use of artificial intelligence (AI) in environmental sustainability has the potential to significantly improve our understanding of and ability to manage the ecosystem. 

Compiled By: Arjun, Data Scientist