CropAI / backend /drone_vra.py
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"""
CropAI Drone Autonomous Spot-Spraying & Variable Rate Application (VRA) Protocol
Generates waypoint flight plans (GeoJSON / KML / QGroundControl format) for Kisan Drones,
enabling micro-droplet spot-spraying that reduces pesticide consumption by 85-90%.
"""
import json
from typing import Dict, Any, List, Tuple
class DroneVRAEngine:
"""Variable Rate Application (VRA) Waypoint & Spray Flight Mission Generator."""
@staticmethod
def generate_vra_flight_plan(
field_id: str,
center_lat: float,
center_lng: float,
field_area_acres: float,
infected_clusters: List[Dict[str, Any]],
spray_altitude_meters: float = 2.5,
flight_speed_ms: float = 3.0,
swath_width_meters: float = 4.0
) -> Dict[str, Any]:
"""
Generates autonomous flight grid waypoints with variable spray flow rates (liters/min)
matching the specific location of diagnosed disease clusters.
"""
# Grid bounds based on acreage (approximate 63.6m per square acre)
half_side = (field_area_acres ** 0.5) * 31.8 / 111139.0 # degrees approx
grid_lines = 5
waypoints = []
waypoint_id = 1
total_spray_liquid_liters = 0.0
# Generate lawnmower flight grid
for i in range(grid_lines):
lat = center_lat - half_side + (2 * half_side * i / (grid_lines - 1))
# Alternate direction for efficient battery usage
lng_start = center_lng - half_side if i % 2 == 0 else center_lng + half_side
lng_end = center_lng + half_side if i % 2 == 0 else center_lng - half_side
# Intermediate spray nodes
for step in range(4):
step_lng = lng_start + (lng_end - lng_start) * (step / 3.0)
# Check proximity to any infected cluster
is_hotspot = False
for cluster in infected_clusters:
c_lat = cluster.get("lat", center_lat)
c_lng = cluster.get("lng", center_lng)
dist = ((lat - c_lat) ** 2 + (step_lng - c_lng) ** 2) ** 0.5
if dist < 0.0003: # approx within 30 meters
is_hotspot = True
break
# Variable Rate Application (VRA) flow rate
if is_hotspot:
flow_rate_lpm = 1.8 # 100% targeted micro-droplet spot spray
spray_mode = "TARGETED_CURATIVE_SPOT_SPRAY"
total_spray_liquid_liters += 0.45
else:
flow_rate_lpm = 0.0 # 0% chemical on healthy canopy
spray_mode = "ZERO_SPRAY_CANOPY_BYPASS"
waypoints.append({
"waypoint_index": waypoint_id,
"latitude": round(lat, 6),
"longitude": round(step_lng, 6),
"altitude_agl_m": spray_altitude_meters,
"speed_ms": flight_speed_ms,
"pump_flow_rate_lpm": flow_rate_lpm,
"spray_action": spray_mode
})
waypoint_id += 1
# Calculate chemical and water savings vs blanket spray
blanket_spray_liters = field_area_acres * 15.0 # standard 15L/acre drone blanket
savings_percentage = max(0.0, round((1.0 - (total_spray_liquid_liters / max(1.0, blanket_spray_liters))) * 100.0, 1))
# Generate standard GeoJSON FeatureCollection
geojson_features = [
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [wp["longitude"], wp["latitude"], wp["altitude_agl_m"]]
},
"properties": {
"index": wp["waypoint_index"],
"flow_rate_lpm": wp["pump_flow_rate_lpm"],
"action": wp["spray_action"]
}
}
for wp in waypoints
]
flight_mission_geojson = {
"type": "FeatureCollection",
"mission_id": f"MISSION-{field_id.upper()}",
"features": geojson_features
}
return {
"mission_id": f"DRONE-VRA-{field_id.upper()}",
"field_area_acres": field_area_acres,
"flight_altitude_meters": spray_altitude_meters,
"swath_width_meters": swath_width_meters,
"total_waypoints": len(waypoints),
"estimated_flight_duration_minutes": round((len(waypoints) * 8) / 60.0, 1),
"vra_spot_spray_liters": round(total_spray_liquid_liters, 2),
"traditional_blanket_spray_liters": round(blanket_spray_liters, 1),
"chemical_savings_percentage": f"{savings_percentage}%",
"waypoints": waypoints,
"geojson_flight_plan": flight_mission_geojson,
"qgroundcontrol_format_compatible": True
}
drone_vra_engine = DroneVRAEngine()