AI’s integration in environmental strategies is proving crucial for achieving global sustainability goals.
Following the 78th general assembly of the United Nations on March 21, 2024, the first global resolution on artificial intelligence (AI) was officially approved by the United Nations General Assembly. The resolution aims to regulate and guide AI development in a manner that is “safe, secure and trustworthy”, with the goal of steering its use towards global good and sustainable development for the benefit of all nations.
This initiative aligns with similar regulations worldwide, such as the “Artificial Intelligence Act” passed by the European Union Parliament earlier in March 2024, highlighting a unified desire to regulate AI while still reaping the many benefits of its uses.
One recurring theme across these AI regulations is “smart environmental protection”. This term refers to the use of advanced technologies—like the Internet of Things (IoT), big data and AI—innovative practices and data–driven approaches to enhance environmental protection and conservation efforts. Using innovative devices, we can process and aggregate large volumes of data. Scientists then use sophisticated algorithms to identify patterns and trends, allowing AI models to provide instantaneous feedback and monitoring, build predictive models and anticipate potential hazards and optimize management and systems generally.
Environmental monitoring
AI is transforming environmental monitoring by offering more precise, efficient data collection and analysis capabilities, providing real-time updates on environmental conditions.
For example, AI systems have been used in air quality monitoring and forecasting in industries like mining. Data from a network of IoT sensors that measure pollutants, such as PM2.5 and nitrogen dioxide, is gathered and then analyzed to identify pollution sources, predict pollution levels and provide real-time alerts.
This technology has already been put into use in some countries. For example, in Beijing, China, IBM’s Green Horizon project uses AI to forecast air pollution levels up to 72 hours in advance, which allows authorities to take preemptive measures to protect public health. This initiative has successfully contributed to bringing the Beijing government closer to its environmental goals.
The use of AI in environmental monitoring is versatile. Beyond monitoring air pollution, AI is also used to assess the health of ocean ecosystems. Instead of relying on labor-intensive and expensive conventional methods, new technologies and tools, such as AI-powered underwater drones, have been used to gather large datasets for analysis.
Using AI, conservationists can track and monitor the accumulation of plastic waste in oceans as well as predict the movement and concentration of plastic debris, which can optimize cleanup efforts and monitor coral reefs to assess ocean health. This information can improve the efficiency and effectiveness of conservation initiatives.
Ecological protection and wildlife monitoring
AI has made significant strides in ecological protection and wildlife monitoring, providing new solutions to traditional challenges. It has enhanced the efficiency of monitoring processes, provided insight into ecosystem health and helped track endangered species.
For instance, the Zoological Society of London (ZSL) partnered with Network Rail to develop AI-powered drones that locate and track animals in their natural habitats. This technology has also been applied in China to aid in the preservation of giant pandas and Siberian tigers and by the World Wildlife Fund to identify and catalog images of animals.
This technology significantly reduces the time and effort traditionally required for manual analysis. The vast amounts of data can be used to implement targeted protection strategies and even predict the impact of climate change on animal habits.
Although AI is frequently used for tracking and monitoring, it can also tackle more complex tasks, such as tracking poaching activities and ensuring compliance with laws.
In rainforests, the non-profit organization Rainforest Connection has developed an innovative solution using AI and recycled smartphones. Upcycled smartphones equipped with solar panels are placed on trees and act as listening devices that capture different forest sounds. An AI algorithm analyzes the audio recordings to detect sounds associated with illegal logging, such as chainsaws and trucks. If these sounds are detected, real-time alerts and locations are sent to local rangers, allowing them to respond quickly to investigate and prevent deforestation.
This technology has been implemented in various regions and has contributed to protecting critical habitats and reducing illegal logging activities.
Combating food waste
AI is playing a pivotal role in combating food waste by optimizing supply chains, enhancing food quality monitoring and revolutionizing the way grocery stores and hospitality sectors manage food waste. According to the United Nations, approximately one-fifth of all food goes to waste, which negatively impacts the global economy and exacerbates environmental degradation. AI’s capacity to analyze vast amounts of data and generate actionable insights makes it uniquely suited to address various stages of the food supply chain where waste occurs.
In grocery chains, traditional manual methods of stocking, ordering and food preparation have been prone to inefficiencies, leading to significant waste. However, with the use of AI-driven purchasing systems, such as those implemented by WWF in collaboration with the Pacific Coast Food Waste Commitment (PCFWC), inventory management and ordering can be fine-tuned to align more closely with consumer demand. This approach can be particularly helpful during festive seasons when demands for certain groceries are higher. This precision has cut food waste by 14.8% per store on average, showcasing how AI can ensure fresher produce on shelves and reduce waste.
According to the WWF, if broadly adopted, AI could prevent about 907,372 tons of food waste annually, translating to significant environmental and economic benefits. This would not only mean a reduction of 13.3 million metric tons of CO2 emissions but also a savings of over US$2 billion.
Similarly, in the luxury hospitality sector, Mandarin Oriental Hotel Group has embraced AI food waste solution provider Winnow’s AI technology to tackle food waste across its global portfolio. Following a successful six-month pilot that achieved a 36% reduction in food waste in four flagship hotels—including locations in Hong Kong, London, Miami and Dubai—the Group is expanding this technology to all its properties by 2025.
Winnow’s system uses cameras, smart scales and tablets to identify, weigh and record waste, helping kitchens optimize food preparation and reduce costs. This initiative not only aligns with global sustainability goals but also demonstrates the power of AI in enhancing service quality while significantly lowering environmental impact.
Future outlook
While AI is still evolving, its potential to revolutionize sustainability and conservation is undeniable. The capabilities of machine learning and real-time data processing have already become invaluable tools for scientists, researchers and environmentalists in their quest for a better, greener future.
As global regulations strive to ensure the proper and ethical use of AI, the continued advancement and integration of AI into environmental strategies hold the promise of a more sustainable and resilient future. By harnessing the power of AI, we can address some of the most pressing environmental challenges and unlock new methods of conservation to pave the way for a more sustainable world.
Also read:
- 3 Innovations for a Cleaner Environment You Never Heard Of
- Is Recycling Plastic Really Good for The Environment? Or Is It a Lie?
- How Supercomputers Are Affecting the Environment
Header Image from Freepik
