Vertical Farming and Urban Agriculture AI

Module: Sustainable Tech | Difficulty: Premium

Photosynthetic Photon Flux

Crop Growth Rate

where LAI is leaf area index, RUE is radiation use efficiency, and PAR is photosynthetically active radiation.

Comparison

Python Implementation

import numpy as np

class VerticalFarmOptimizer:
    def __init__(self, n_layers, area_per_layer):
        self.n_layers = n_layers
        self.area = area_per_layer

    def light_schedule(self, crop_type, photoperiod=16):
        schedules = {
            'lettuce': {'ppfd': 200, 'hours': 16, 'dli': 11.5},
            'herbs': {'ppfd': 300, 'hours': 14, 'dli': 15.1},
            'tomatoes': {'ppfd': 500, 'hours': 16, 'dli': 28.8}
        }
        return schedules.get(crop_type, schedules['lettuce'])

    def nutrient_optimization(self, growth_stage, current_nutrients):
        targets = {
            'seedling': {'N': 100, 'P': 30, 'K': 80},
            'vegetative': {'N': 200, 'P': 50, 'K': 150},
            'flowering': {'N': 150, 'P': 80, 'K': 200}
        }
        target = targets.get(growth_stage, targets['vegetative'])
        adjustments = {}
        for nutrient, target_val in target.items():
            current = current_nutrients.get(nutrient, 0)
            adjustments[nutrient] = target_val - current
        return adjustments

    def yield_prediction(self, crop_type, ppfd, temp, co2):
        base_yields = {'lettuce': 100, 'herbs': 60, 'tomatoes': 80}
        base = base_yields.get(crop_type, 80)
        light_factor = min(ppfd / 200, 1.5)
        temp_factor = 1 - abs(temp - 22) / 50
        co2_factor = 1 + (co2 - 400) / 1000
        return base * light_factor * temp_factor * co2_factor

Research Insight: Vertical farms use 95% less water and 99% less land than conventional farming for leafy greens.