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10 Ways AI Is Improving Cannabis Yields And Security

Bottom Line:  With an average yield per acre of $1.1 million, legal cannabis agriculture dwarfs all other crops in revenue potential while also providing the resources needed to fund AI-based monitoring to improve yields and security. 

Cannabis’ value per acre 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. Recent studies by the USDA, The Rand Corporation, and the Marijuana Cultivators of Oregon find that at an average price of $1,948 per pound at Colorado prices, an acre of marijuana can yield more than $1.1 million per acre. The studies compared the most widely grown crops in the U.S., including corn, soybeans, oats, and wheat, which all yield less than $1,000 per harvested acre. The following graphic from New Frontier Data illustrates how profitable an acre of marijuana is to cultivate than other crops. 

Using AI to Protect & Grow a Cash Crop

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 farm staff of a breach or break-in by an animal or person is possible using AI-based smart monitoring systems.

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 farms 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 acre.

The following are ten ways AI is being used for improving cannabis yields and security:

  1. Monitoring real-time video feeds of remote cannabis fields using machine learning-based surveillance systems can identify a breach by an animal or human then send an alert immediately.  Given how valuable a single acre of cannabis is to a farm, knowing in real-time if there’s been an attempted breach or break-in can save thousands of dollars in potential crop damage and theft. Federated cannabis farms with multiple remote locations are starting to use AI and machine learning-based remote monitoring to secure their operations. Machine-learning based video surveillance systems can be programmed or trained over time to identify employees versus unknown people and easily spot animals attempting to break into a field.  The following image from Twenty20 Solutions illustrates how machine learning is used for identifying activity at a remote location:
  1. Define access privileges across a farm facility by the level of access every employee needs to do their job, which is especially useful for new hires. New hires often start in the field and don’t need access to the front offices or the accounting department, for example. One of the most challenging aspects of running a cannabis business is cash management. Using an AI-based surveillance and monitoring system integrated into the local security system and intelligent locks, employees are provided the level of access they need on the first day to be productive.
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