Researchers at King Abdullah University of Science and Technology has developed an innovative, low-cost drone system powered by artificial intelligence, that can identify and track camels from the air, according to Arab News.
This AI-powered system provides camel herders with an affordable tool to sustain one of Saudi Arabia’s oldest traditions. Meanwhile, it allows scientists to gain deeper insights into camel migration patterns and behaviors.
The technique, developed by Professor Basem Shihada and his research team, relies on affordable commercial drones and cameras, enabling camel herders to monitor their herds in real time without the need for expensive GPS collars or satellite connections.
Through a single drone-mounted camera, the team captured aerial footage of small camel herds in the Kingdom. This footage paved the way for training their AI model using machine learning. Consequently, the models offered new insights into the animals’ behaviors.
“We found their migration patterns were not random but showed identifiable patterns,” said KAUST scientist Chun Pong Lau, who was also involved in the project.
New Insights into Camel Patterns
The team also noticed that camels, particularly the older ones, followed coordinated grazing patterns, traveling long distances throughout the day but always returned to their herder by sunset.
Interestingly, KAUST scientists have kept the drone at least 120 meters above the ground due to the camels’ heightened sensitivity to the drone’s noise.
Camels were a primary means of transportation across vast distances offering a good company to combat the isolation of long journeys. Today the camels remain one of the basic elements of Saudi Arabia’s history and civilization.
However, herding poses a challenge as camels roams up to 50 km a day across isolated terrain. This mobility often causes road accidents, overgrazing and loss of livestock.
To ensure higher performance from the new system, KAUST team plans to collect video of larger camel herds of more heterogeneous sizes and colors to train their models.
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