Australian-based charity ClimateForce and NTT Group are planning to restore the ecological balance of the Daintree Rainforest using artificial intelligence (AI) in a first-of-its-kind move.
ClimateForce will collaborate with global technology giant NTT Group to establish a smart rainforest to protect the region’s biota. The plans involve leaning on NTT Group’s AI-based Smart Management Platform to collect, store, and act on data obtained from the Daintree Rainforest.
“ClimateForce is a proving ground for technologies that protect biodiversity and help mitigate climate change,” said ClimateForce CEO Barney Swan.
Located in Queensland, Daintree is Australia’s largest rainforest, housing over 3,000 plant species and over 12,000 species of insects. However, the rainforest’s biodiversity has been threatened by invasive species, unfavorable weather conditions, and man-made deforestation activities.
In recent years, the region has been plagued by rising temperatures, excessive flooding, and droughts, upsetting the balance of the Daintree’s flora and fauna.
While several attempts have been made to reverse deforestation trends, this is the first time emerging technologies, like AI, will be utilized to preserve the rainforest.
“The generous support from NTT and NTT DATA will help us quickly expand our initiative in the Daintree and speed up our goal of developing replicable models that regenerate ecosystems, protect biodiversity, and foster resilient local economies in other locations,” said Swan.
The plan will entail the collection of atmospheric data from a wide range of sources, including satellites and weather stations. NTT’s Smart Management Platform will collate the data to make informed decisions based on temperature levels, humidity, and wind speeds, amongst others.
Armed with processed data, government officials will be able to stem the tide of unfavorable weather conditions, including the planting of more trees, support for indigenous communities, and deploying sustainable practices.
AI finds utility in weather forecasting
In a recent study, researchers from the Johns Hopkins Applied Physics Laboratory (APL) have experimented with a new AI model for weather forecasting. Dubbed APL’s Deep-Learning Network, the system demonstrated advanced capabilities in predicting weather changes with minimal input data, running several models concurrently.
Other use cases for the technology include drug synthesization, uncovering new materials for batteries, and breast cancer detection. Despite the wide use cases, AI faces a grim future over copyright, privacy, superintelligence, and regulatory concerns.
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Watch: What does blockchain and AI have in common? It’s data
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