As written in my previous article on “A primer on AI and its rise in the greenhouse”, a well-architected AI system can help growers achieve higher yields while optimizing resources efficiency, hence enabling indoor farms to be more sustainable, viable, and profitable. By generating insightful analytics across innate greenhouse operations, AI can support growers in making informed decisions based on data and empower them to be future-minded about efficiency and sustainability. Therefore, the next revolution of agricultural practices is dominated by the combination of artificial intelligence and human wisdom.
It is said that
There’s No AI (Artificial Intelligence) without IA (Information Architecture).
In greenhouse growing, we coin a more specific term for IA: Digital Horticulture. Data is the fuel for AI. The more sophisticated the AI (rocket ship), the greater the need for large amounts of high-quality, clean data (jet fuel). But amidst the rush to jump on the AI bandwagon, companies (and even data scientists and machine learning specialists themselves) overlook the critical need to build a solid foundation for how data is captured, consumed, and shared within the organization.
Digital Horticulture: An Essential Step Toward Autonomous Growing - Greenhouse Canada
Through our article titled "A primer on AI and its rise in the greenhouse", we learned that a well-architected artificial intelligence (AI) system can help growers optimize resource efficiency and achieve higher yields. By uncovering data insights across greenhouse operations, growers can use AI to make more informed decisions, enabling indoor farms to be ultimately more sustainable and profitable.