
The cannabis sector's evolution is based on cannabis 3.0, the future of blockchain, and AI in the Cannabis industry.
Fremont, CA: Cannabis 1.0, 2.0, and 3.0 include the industry's advancement and provide a roadmap into true consumerism. This path will be determined using cutting-edge technologies comprising machine learning algorithms, blockchain, regulatory technologies, and consumer input devices, all working together in an extensive data system.
Regulatory requirements and global market conditions have revved the arrival of 3.0
Cannabis 3.0 is observed as the collectivization of individual opinions, biometric tracking, outlining of the products from the source to the consumer, the quality of the products in the marketplace, and brand identification. When someone cares to know who has the best strain of medical cannabis or CBD oil for headaches, joint pain, knees, or anxiety, individuals will have confirmed real-time data, opinions and facts about the market. Brand efficacy will constitute the division between mass producers of gummy edibles, which serves one type of mass usefulness, versus craft or smaller-scale manufacturing, which may be measured to satisfy customer requirements to be enhanced than mass production.
Being able to track the efficacy of how the products are being made, what condition they are helping, and the effectiveness of those products, 3.0 will be the actual test for producing trust in the market. Cannabis 3.0 is essential to the cannabis industry, as doctors can consider real-time data and make real-time suggestions according to the quantitively and qualitatively assembled information on end-users and the delivery of quality patient care and customer protection.
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Framing methodology, system, and apparatus for data storage and data access to medical cannabis products through blockchain
For the last two years, Global Cannabis Applications Corporation (GCAC) has been a Cannabis 3.0 early innovator. GCAC has designed a patent-pending methodology of gathering and storing data allied with a cannabis product and customer feedback on that product's intake throughout a distributed node validation system. The method contains associating data plurality to a record ordered by a one-of-a-kind digital identifier stored on the blockchain for access by one or more authorized users. The documents are then examined with the support of non-directed machine learning algorithms to decide the quality and quantity of expected and undesired components in the cannabis product. The output is a decision of an end-user experience succeeded by storing this data on the blockchain.