IoT technologies are improving our understanding and comprehension of climate change. AI, machine learning and deep learning are fueling a new field called climate informatics. Climate Informatics bridges the gap between climate scientists and AI researchers to explore the full potential to better understand what is happening with our climate. As these various fields become fused, climate research becomes more effective. In turn, this effectiveness enables predictive and proactive steps to be taken, perhaps quickly enough to preempt an impending climate disaster. The following article does an excellent job in detailing four key ways in which this approach can be implemented. 

New technologies, such as the Internet of Things (IoT), artificial intelligence (AI), and applied data science in general, have the potential to advance our understanding and ability to effectively address climate change.

One promise of IoT is to make all kinds of devices and environments more efficient and responsive to real-time fluctuations in use. What this means is that IoT systems at various levels of implementation can affect energy use and emissions. In 2015, researchers found that “the information and communications technology industry (which includes IoT) could help reduce greenhouse gas emissions by up to 63.5 gigatons, or 15%, across all industrial sectors by 2030.”

It’s no secret that overpopulation is negatively impacting our environment. Researchers predict that by 2050, two-thirds of the world’s population will live in cities, so it will only become more important to make those cities energy efficient. Smart cities can use IoT systems to make the water supply more efficient, improve congestion to reduce time spent in cars, and provide more reliable public transit. Smart cities can also implement energy-saving measures by encouraging remote working and monitoring trash and pollution.

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