Sensor technology and machine learning can be utilised to monitor crop health in real-time, alerting for conditions that may increase instances of environment-related disease. Automatically controlled systems can maintain growing conditions at optimum levels for improved plant health and higher yields, while indoor systems reduce the likelihood of disease transmission and pests. These factors reduce the need for excess fertiliser and chemicals such as pesticides compared to conventional systems, saving time and input costs for the producer.

Real-Time Monitoring and Analysis

Sensors can be deployed within growing environments to collect intelligent data on plant health and disease risk. Minor changes can be detected through detailed analysis and real-time alerts can be sent instantly to enable effective decisions to be made to safeguard crops.

Environmental Sensor Deployment

Controlled growing environments require constant monitoring to maintain high plant health. IoT sensors can be deployed to directly analyse plant growing conditions such as light, humidity, temperature and nutrient availability.

Maintain Optimal Growing Conditions

Farmers can set sensors to monitor growing conditions within optimal ranges, with real-time alerts for sensor measurements outside these levels. This enables fast action to resolve any potential problems and ensures that plant environments are constantly maintained at ideal levels.

Controlled Environments

Real-time sensor data is directly linked to machine learning command and control actions that intuitively adjust environmental conditions to enable continuous maintenance of optimal growing environments.

Fast Disease Detection

Growing plants in controlled environments reduces instances of disease and pests due to the nature of the closed, indoor environment. Adding to this, continual sensor monitoring and analysis enable the real-time alerting of potential problems for fast resolution.

Variable Rate Technology

Sensors deployed in growing environments allow detailed and tailored action on nutrient availability and pesticide use, eliminating the need for blanket treatments while reducing costs and use of harsh chemicals.

Reduced Pesticide Use

Indoor controlled environments reduce the need for pesticides as growing conditions are monitored and maintained at optimal levels, while environments are closed to outdoor transmission of disease and pests. This ensures fewer pesticides are applied to crops, reducing costs and improving sustainability.

Food Security

Environments can be easily controlled through the use of automatic machine learning commands, reducing disease transmission. Plants are grown in closed environments, reducing the chances of outdoor transmission and therefore, increasing food security.

Improved Crop Production

Reducing disease and pest instances through monitoring and controlled conditions ensures high plant health and consequently, improved growth rates and improved yields.

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