ADVANCEA - Advancing Controlled Environment Agriculture Through Data-Driven Decision-Making and Workforce Development
Successful environment control and crop management in CEA requires equipment, data, and experience. Skilled growers have been in short supply in the fast-growing CEA industry, challenging its expansion.
Our project team proposes to work on developing novel data acquisition and processing systems that will allow growers to make more effective and efficient environment control and crop management decisions. We propose to develop a platform that integrates data collection, data processing, and decision support tools empowered by emerging techniques such as machine learning (ML) and artificial intelligence (AI).
At the same time, we want to develop a workforce development program that allows growers to learn how they can adopt this novel approach, irrespective of the size of their operations. Given the wide range of technology use, we will evaluate the new approach of climate and crop management in various types of greenhouse structure and climate regions.
Our specific objectives include:
- Development of a data- and model-driven decision-making platform;
- Validating the efficacy of new data- and model-driven decision-making
- Understanding the socioeconomics of greenhouse technology adaptation
- Engaging our stakeholders through professional learning opportunities for workforce development.
This ADVANCEA project team includes industry members and has a strong network with our CEA stakeholders through our previous workshops and short courses over the past 20 years. The cumulative number of stakeholders we reach annually is estimated to exceed 10,000. We will develop training modules for growers and greenhouse managers that will be available for use by universities and businesses.
In addition, we will take a multi-step approach to engage with various stakeholders and organize regular events to discuss strategies and future directions of our R&D efforts. Workshops, webinars, and discussion forums will engage growers. Learning opportunities of core engineering principles (including sensing, modeling, and control) will be offered to our grower stakeholders.
