It is vital to address any environmental issues before they become more severe. What better way to do this than to use current technology? As a result, this article addresses the critical topic, “How can Machine Learning save the environment?
1. Smart Pollution Control
Pollution is a major problem in major cities. A smart urban pollution control system that is based on IoT/Machine Learning is essential!
IoT can collect data about city pollution such as pollen levels, car emissions, airflow direction and weather conditions. Machine Learning algorithms automatically assess the data after collecting it. They then modify the appropriate prediction models according to many factors, including the current season and topologies within the city. Machine Learning algorithms can use this research to create pollution projections for different areas of the city and notify municipal officials before a problem develops.
2. Smart Wildlife Protection
Many wild animals are being endangered or made extinct in many countries. It is our responsibility to ensure that these species remain in their natural habitats. This includes ensuring that wild grasslands and woods are preserved as they are.
WildTrack is a company that specializes in this. They employ a footprint identification technique (FIT) in conjunction with IoT and ML algorithms to determine an animal’s species, age, and gender-based on its distinctive footprint. This unique data can then be used to identify patterns related to animal migrations and male to female ratios. It also helps in conserving many endangered species.
3. Smart Disaster Response and Prediction
Machine Learning can forecast many natural disasters such as earthquakes, flash floods, and hurricanes.
This is evident in the example of an Earthquake Detection System, which uses deep learning networks. It was developed by Harvard and Google experts and can predict aftershocks after a large earthquake. This technique uses seismic data to identify patterns that are difficult to evaluate using existing technologies. There are many elements that can influence the likelihood of aftershocks, including ground composition, seismic plates contact, energy transmission through soil, and so forth.
4. Smart Agricultural Practices
There is sufficient food to meet everybody’s needs, but not everybody’s greed. On the other hand, humans are greedy. Nearly 815 million people are hungry around the world. That’s one in ten people. These people are mostly from developing or undeveloped countries. Machine Learning could be used to address the problem of malnutrition. It combines modern agricultural technology and crop production to increase crop yields and reduce hunger.
5. Smart Electric Vehicles
Are you breathing in more carbon dioxide than oxygen in your city? If so, you could be one of the main culprits for the air pollution caused by cars. And Smart Electric Vehicles are a “smart” way to rescue the environment and also our lungs! These vehicles will run on electricity, which reduces air pollution in cities. It is estimated that an oil-powered car emits twice the amount of carbon pollution as an electric one.
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