Human-wildlife conflict and food security

Wherever protected land meets farmland, villages and smallholdings sit right up against wildlife corridors and park boundaries. As populations inside the parks recover and habitat outside them shrinks, the encounters get more frequent. For a family living off that land, a herd in the field is not crop damage, it is the income and the food for the rest of the year. And it does not stop at the harvest: people get injured, and there are deaths on both sides.

Bears in European mountain regions do the same thing for the same reason. Their forest is shrinking and natural food is getting scarcer, so they come into the villages after bins, fruit trees, beehives and livestock. Every species behaves differently, but the pattern underneath holds. An animal that finds an easy meal once comes back.

And it builds. Every incident lowers tolerance in the village, and the bill ends up with the animal: problem bears get shot or relocated, elephants get killed in retaliation. Meanwhile the means to contain it are thin. Fences get pushed over or fall into disrepair. Villages put people on watch at the fields at night, season after season. That is labour nobody can keep supplying, and in the wrong place it is dangerous as well.

The Smart Deterrent ties detection to response. When an AI camera recognises an animal near a village or a field, the system fires light and sound drawn from a large library, in a different combination every time. That unpredictability is the point. An animal learns to ignore a fixed pattern, but it cannot learn its way around one that changes on every encounter.

It runs non-lethally, on solar power, and nobody has to stay awake at night. We tune the deterrents per species, because an elephant and a brown bear respond to different things.

Detection and response both run autonomously, on their own LoRa network where there is no cell coverage. That lets the system sit on a park boundary or in a mountain valley for months without anyone having to go out to it.