Conservation science meets edge AI. RangerSight.AI automates species counting, behavior classification, and pollinator-plant interaction logging—replacing thousands of hours of manual fieldwork with continuous, non-invasive observation.
A 12-gram smart platform that sits beneath a flower cluster. Piezoelectric load cells detect bee landings with 0.01 g resolution, logging visit duration, time-of-day, and estimated pollen load. Mesh-networked via LoRa to a RangerSight camera hub up to 800 m away.
Scatter these matchbook-sized passive infrared nodes along trails. They detect warm-body crossings, estimate animal mass from heat-bloom radius, and wake the nearest camera from sleep mode in 40 ms for a high-res capture. 3-year coin-cell life.
Temperature, humidity, UV index, soil moisture, and ambient light in a waterproof pod the size of a walnut. Correlates environmental conditions with species activity to reveal why bees prefer certain hours or why squirrels avoid a corridor after rain.
Quantify exactly how many bees, butterflies, and hoverflies visit each plant species per hour. Delivers hard data for USDA pollinator health grants and pesticide-impact studies.
Continuous visual sampling feeds Shannon-Wiener diversity calculations automatically. Detect ecosystem stress weeks before it becomes visible to periodic manual surveys.
Thermal + IR triggers capture skunks, raccoons, and opossums without disturbing them. Map movement corridors to inform wildlife-crossing placement on roads.
Build directed graphs showing which species visit which plants. Identify keystone pollinators whose decline would cascade through the local food web.
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