Future Trends

Emerging contribution of AI has undoubtedly transformed the domain of Environmental Science. AI based techniques such as machine learning is improving efficiency by providing better possibility of decision making, backed by data prediction, has reshaped the definition of sustainability for environment. AI innovations such as deep learning, remote sensing, computer vision, machine learning etc. are playing a pivotal role in supplementing climate modeling, tailing ecological changes, optimization of resources and conservation of biodiversity by predicting the future trends by analyzing available data and studies. Prediction models developed with the help of machine learning or deep learning are of use in predicting extreme weather events by analyzing vast scope of datasets, mapping of habitats, optimization of energy usage and ecological restoration. Sensors, deployed for gathering data from surroundings, assist in environmental monitoring such as remote sensing, electrochemical sensing, temperature sensing help in mitigating or alleviating challenges such as pollution or air quality index, temperature, soil composition etc. AI along with IOT spotlights the domains such as smart agriculture, tracking and reduction of carbon footprint, water and energy optimization and sustainability in energy restoration. Having said that, along with major perks, come associated restrictions and dilemmas such as data collection, dataset availability and accessibility, data biases, efficiency of interpretation, ethical aspects and global sustainability implementation. But overall, AI possesses immense potential being a considerable aid for advancing in environmental science promising efficient conservation strategies and a healthier planet.