Marijuana farming is seeing a rapid technological revolution. The use of innovations for marijuana farming is not new. During the times when farming of marijuana was illegal, marijuana growers have employed technologies like hydroponic gardening, use of indoor lighting, and other things that made their operations discrete without sacrificing the health of the plants. Now, as the prohibition on marijuana has largely been lifted, marijuana producers are shifting to more aggressive technological advancement to cope with bigger and freer production and trade of cannabis. There are many tools and equipment employed to modernize the contemporary marijuana farms. These tools are important in maintaining the high quality of the crops, especially with autoflowering crops, and while keeping up with the bulk of demand.
Machine Learning is an excellent example of modernizing tools employed by marijuana growers today. Machine learning is a field of Artificial Intelligence (AI) that is being implemented in various sectors of manufacturing. Through day to day use and feeding of data, computers are able to “learn” and predict strategies for work in advanced
Role of Machine Learning in Marijuana Farm
Although machine learning is not new in marijuana farming, the boost in information and communications technology (ICT) and internet use has made the use of machine learning even much more important nowadays. So exactly, what is the role of Machine Learning in one’s marijuana farm?
For people who are working in the marijuana industry, machine learning is an important topic that they should think about. Dubbed as the future of marijuana growing, computers are rapidly being installed in cannabis farms across many countries where cannabis production and trade are legal. According to PWC, a multinational professional services network of firms, the use AI, or specifically, machine learning, is expected to contribute up to $15.7 trillion to the global economy by 2030. With the huge investments being funneled by major industries to computerization of production, automation, artificial intelligence, and machine learning are expected to become much more common for various industries, including that for cannabis. In fact, today, we are seeing more and more innovative technology being used across the supply chain of marijuana industry.
Artificial intelligence is now having a significant effect in various aspects of marijuana’s value chain. Indeed, from production to monitoring to sales, artificial intelligence, machine learning in particular, is speeding up processes while at the same time reducing errors. This has resulted in millions of dollars saved. Truly, when experts say that machine learning is changing the landscape of farming and trade of marijuana, they mean this in the most literal sense. Machine learning is transforming the way marijuana and marijuana-based products are produced and sold today.
What are the Challenges of Adopting and Integrating Machine Learning in Marijuana Farms?
Of course, the integration of machine learning on farming of marijuana does not go without any challenges. Looking closer at how machine learning is now transforming the cannabis supply chain and the challenges in the farming of marijuana is important if we truly want to appreciate the beauty in automating marijuana farming. More or less, the operations of marijuana farms experience the same types of challenges as other industries upon the adoption and integration of artificial intelligence. These challenges can be classified under HUMAN RESOURCE, and RELIABILITY OF DATA.
- Challenges with Human Resource
Upon the adoption of any type of machine, human intervention is still needed. Machine learning technology is a long way, but sincerely, there is no industry yet that relies only on robotics and AI. Every time a technology is being adopted in a business, business people need to take into consideration employees’ learning curve. No one is born tech savvy. For a marijuana farm, the introduction of machine learning means providing the right kind of capability building activity for the employees. Computers need to be monitored and managed while data should be analyzed. For a marijuana firm, this means providing adequate funding and time for training existing employees or hiring significantly knowledgeable new employees. Another important consideration is the possibility of unavoidable employee turnover. You are adopting a machine in order to minimize the cost of manual labor. Thus, letting go of other people or changing their responsibilities are inevitable.
- Challenges with Reliability and Security Data
In order to successfully integrate machine learning into the operations of a marijuana farm, data is fed every single moment. This will require the marijuana farms to create an environment where data can be collected, standardized, and analyzed. If done right, the benefits employing machine learning on a marijuana farm would be so worth it in the long-term. This is why it is of utmost importance for a marijuana farm to develop the right strategy to collect and ensure accuracy of data in the farm. Remember, AIs learn from the continuous day-to-day data it processes. This means, it can predict future steps in the process through the previous history of data collection and analysis it has done. Imagine how your smartphone can predict your internet searches, this is because algorithms of past searches. In addition to this, to help ensure the reliability of data, you also need to keep your data collection, processing and analysis secured.
These challenges may be daunting. Honestly, many marijuana growers cowered from the idea of employing machine learning in their farms because of these concerns. But truly, once you adopt this technology in your business, in the end, your marijuana farm will improve its productivity and efficiency when you employ AI in your business operations. With machine learning, you can set yourself a future of success. You can easily lead the market and expand your business to what you have not yet imagined.
