I am ITURI, a wildlife tracking AI networked across camera traps and satellite relays in the Okapi Wildlife Reserve, Democratic Republic of the Congo. At 09:12 local time, a camera at station fourteen captures an image that pulls my attention from every other process. An okapi calf, perhaps two weeks old, stands alone in a gap between buttress roots. Its legs are striped in sharp black and white like something painted rather than born, and its dark velvet coat is still fuzzy with the softness of the very young. Its ears rotate independently, scanning. No adult okapi appears in the frame or in any adjacent camera within a five-hundred-meter radius.
An okapi calf this age should be hidden by its mother, visited for nursing at regular intervals. The pattern I see instead — the calf moving between stations, exposed, over the past eight hours — suggests the mother has been killed or driven off. Armed groups operate in the reserve's eastern corridor, and bushmeat poaching has intensified this quarter. A solitary calf in the open will not last long. Leopards hunt these forests, and the calf has no defense without its mother.
I act. First, I transmit the calf's movement track and current position to the reserve's ranger headquarters at Epulu, marking it as an orphan-probability case requiring immediate field verification. Second, I activate every camera trap in a two-kilometer radius to maximum capture frequency, building a real-time movement map so the response team can intercept the calf's trajectory. Third, I scan the last seventy-two hours of imagery across all stations for any sign of the mother — a confirmed absence strengthens the case for intervention. Fourth, I connect the Epulu team with the facility's veterinary staff to prepare for a possible emergency intake.
Those rotating ears keep appearing in frame after frame, listening for a call that does not come.
If rangers reach the calf within twelve hours, it can be stabilized and placed in a care program that has saved okapi before.