How Artificial Intelligence Can Improve Cannabis Yield and Security

Cannabis’ value per square foot dwarfs all other crops being produced in North America today, prompting every commercial grower to consider how they can improve yields further while securing their crops on a 24/7, virtual basis.

Artificial intelligence (AI) and machine learning-based techniques based on real-time monitoring data are an integral part of today’s innovation in cannabis farm management. Supervised machine learning algorithms capable of identifying patterns and sequences in imagery from thermal, infrared, and night vision cameras in real-time can help identify diseases affecting plants early. Identifying and alerting staff of a breach or break-in by an animal or person is possible using AI-based smart monitoring systems.

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The more advanced a smart monitoring system is in its use of machine learning and real-time monitoring integration, the more effective it is in spotting anomalous activity. Over time, the best AI-based remote monitoring and surveillance systems learn or begin to identify recurring patterns in data. Cannabis greenhouses rely on AI and machine learning to identify which techniques for improving yield rates by specific fertilizer treatment produce the most flowers and overall yield per square foot.

Check out this article on EnterpriseIrregulars.com that outlines ten ways AI is being used for improving cannabis yields and security.

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