Conservation
Assuring the
planet of a
greener future
with AI.
Across the world, the need to realign developmental activities with sustainability goals is a critical objective. Maintaining ecological balance is a compelling priority for communities and governments. As increasingly catastrophic natural disasters occur, scientists scramble to determine the possible causes and devise preventive measures. These endeavors require the processing of a large amount of data from diverse sources.
AI technologies offer the analytical power, accuracy, and versatility demanded by such research explorations.
Autonomous vehicles and drones facilitate the tracking of endangered animals in dense, inaccessible habitats. Deforestation and land-use patterns can be monitored, while reforestation efforts can be augmented with ML-aided models.
Computer Vision and remote-sensing tools ensure the monitoring of illegal, unreported, and unregulated (IUU) fishing, while small-aperture radar, satellite, and underwater imaging aid in the remote examination of coral reefs.
AI-powered evaluation of air, water, and soil quality, correlated with climatic and ambient parameters, offers insights into the effects of pollution. Mining activities can be controlled with automated, visual and data-backed analytics.
AI arms conservation specialists with a new generation of powerful tools, heralding a better future for the world and the precious lives it sustains.
Domains
Forest Monitoring
Computer Vision-aided and acoustic monitoring of animals, humans, vehicles, and wood-cutting tools, counting of endangered species, poaching prevention
Wildlife Research
GPS and satellite-tracking of animal migration and movements, neural network-powered modeling to determine the impact of climate change on animal habitats, biodiversity analysis
Marine Biodiversity Exploration
Autonomous deep-sea exploration vehicles to discover new marine animals and plants, assessment of pollution, Computer Vision-powered classification and monitoring of coral reefs
Sustainable Fishing
Visual analytics to monitor fishing practices and identification of endangered species in the catch, depletion of fish population in an area, neural network-enabled analysis of the effect of climate changes on the marine ecosystem
Environmental Research
Demand prediction for optimized power generation, traffic planning to cut fuel consumption, deforestation studies, air, soil, and water quality analysis, meteorological research
Farming and Food Security
ML models for sustainable agriculture, AI-powered bioinformatics for improved yield of crops and livestock, disease prevention and control, monitoring of water bodies used for irrigation
