First 12 Months Strategic partnership (PrecisionHawk Inc.) Collaborations: Acadia, NSCC (AGRG), Dal Ag Projects: wild blueberries, potatoes, corn, soybean, canola, cultivated blueberries, cranberries, onions, forestry, aggregates, aquaculture Inexpensive Efficient Versatile DRONE ADVANTAGES YIELD HARVEST THREATS WASTE Predictive resource allocation to increase yields. Early disease, pest, and weed detection. Optimize harvesting based on accurate crop load analysis. Reduce inputs. Increase outputs. TARGETED ISSUES BASELINE CONDITIONS CORN and SOYBEAN PASTURE POTATOES HIGH-BUSH BLUEBERRIES WILD BLUEBERRIES Data Analytics/ PatternAnalysis Machine DataCalibration Learning F ield O bject C lassification A nd L ocation Our FOCAL model has a sensitivity of 93% and classification accuracy of 88%. Dirt Road Healthy Field Rock Run-off Ditching Vehicles Trees Buildings Area of Interest Unique layers for quantifying data PRECISION INTERVENTIONS Weed detection by type and distribution for targeted applications AGGREGATE TO ACTIONABLE Output files for actionable outcomes Legend > 80% Concentration % Concentration % Concentration % Concentration < 20% Concentration = 1m 2 17% 4% 5% 8% 65% Density CHALLENGES Endurance: flight-time, carrying capacity, GPS accuracy, weather tolerance Regulatory framework: FAA, Transport Canada, BVLOS Early adopters, measuring ROI FUTURE THINK Full autonomy Inductive charging Cloud-connected Swarm capabilities Targeted payload delivery