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AI in Environmental Engineering and Ecology

Grand Rapids_Michigan_111220A
[Grand Rapids, Michigan State - Forbes]


- Towards Smart and Sustainable Cities

The growing world population puts undue pressure on available resources, leading to a number of social, economic and environmental problems. The world is facing challenges related to the provision of food, shelter, water and infrastructure. Solutions to the sustainability crisis require elucidating complex interactions that do not fit neatly into a single discipline. 

Considering that the Sustainable Development Goals are considered a blueprint for a better and more sustainable future, interdisciplinary research in civil and environmental engineering is essential. 

Interdisciplinary research addresses the needs of the growing urban agglomeration population. Design interdisciplinary solutions to achieve the Sustainable Development Goals, including sustainable cities and communities; affordable and clean energy; clean water and sanitation; responsible consumption and production; industry, innovation and infrastructure; climate action is current needs. 


- AI in Environmental Sustainability

Interdisciplinary research on environmental sustainability can translate real-world complexities such as spatial dynamics and urban pressures, sustainable infrastructure, smart transportation, smart buildings, climate change, air pollutant dispersion and pollution, pollutants through the air, water and soil transport, ocean dynamics, underwater life, and the impact of pollution on flora and fauna, among others, are translated into predictable models through artificial intelligence (AI). 

The main goal of this study is to consolidate the research and application of artificial intelligence (AI) in environmental engineering with the aim of realizing smart and sustainable cities. Emphasis will be given to AI-based solutions and models in the field of environmental engineering and sustainable development, especially smart and sustainable cities. 


[Mittenwald, Bavaria, Germany]

- Environmental AI Infrastructure

AI can help environmental engineers collect, process and analyze large and complex data sets faster and more intelligently than traditional methods. AI can also help integrate variable renewable energy by enabling smart grids that partially match energy demand to sunny and windy periods. 

Using artificial intelligence (AI) to help gather, understand and analyze vast amounts of information has the potential to revolutionize our ability to observe, understand and predict Earth system processes. 

Researchers and scientists are working together to apply modeling techniques such as artificial intelligence (AI) and machine learning (ML) to advance Earth and environmental science. Specifically, the goal of a group of scientists and experts is to incorporate modern technologies into the work of Earth system models, observations and theory, and to provide computing power for speed, accuracy and more informed, agile decision-making. 

We need new AI approaches that combine process understanding and respect for the laws of physics to make predictions of Earth system behavior scalable, credible, and applicable to future climate conditions.


- Research Topics of AI in Environmental Engineering and Ecology

Artificial intelligence (AI) can be used in environmental engineering and ecology to help with tasks such as:

  • Tracking and monitoring environmental impacts, such as water usage or air pollution
  • Identifying potential risks and opportunities related to ESG
  • Developing intelligent systems that can monitor and analyze environmental data in real-time
  • Helping businesses reduce their environmental impact, improve their social responsibility, and strengthen their governance
  • Enhancing the accuracy of global climate predictions
  • Helping to mitigate and manage the risk of catastrophic weather events
  • Designing more energy-efficient buildings
  • Monitoring deforestation
  • Optimizing renewable energy deployment


[More to come ...]

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