How digital twins are transforming controlled environment agriculture and solving the global issue of food insecurity
Drastic climate change and overpopulation have led to unsustainable traditional agricultural practices, resulting in a rise in global food insecurity. Even economically affluent countries like Canada are experiencing an alarming increase in household food insecurity. To address these challenges, agriculture companies are turning to controlled environment agriculture (CEA) techniques, such as indoor farming. However, the complexity of CEA requires computer-aided support. This is where digital twins, digital representations of physical objects or processes, come into play. Developed at McMaster University’s Sustainable Systems and Methods (SSM) lab, digital twins offer a solution to optimize crop growth, reduce energy consumption, and revolutionize the way we produce food.
The Rise of Controlled Environment Agriculture and the Need for Computer-Aided Support
Controlled environment agriculture involves growing crops in isolated environments with precise control over factors like temperature, humidity, and lighting. These environments, equipped with complex machinery and sensors, enable better yield and quality while minimizing waste. However, finding the optimal growth strategy and reducing energy consumption in these environments is a complex task beyond human capabilities.
The Role of Digital Twins in Controlled Environment Agriculture
Digital twins act as high-fidelity simulations of physical systems, aiding decision-making and control in real-time. In precision agriculture, digital twins are used to monitor and control environmental conditions, ensuring optimal and sustainable crop growth. They provide live dashboards to observe environmental conditions and can even autonomously control the environment. This technology is particularly useful in reducing energy consumption, a key goal in precision agriculture.
Designing New Greenhouses and Experimentation
Digital twins can also be utilized in the design of new greenhouses. By collecting data over a long period, a digital twin can provide valuable insights and aid in the experimentation process when designing new facilities. This allows for more efficient and sustainable greenhouse designs, reducing costs and maximizing productivity.
Economic Feasibility and Challenges of Digital Twin Adoption
The adoption of digital twins in controlled environment agriculture comes with associated costs. Hardware elements and software development are the main cost drivers in developing digital twins. While home-brew solutions and gradual expansion of functionality can be cost-effective initial steps, professional grower settings require industry-grade sub-systems that come with higher costs. Digital maturity, including cloud providers, data strategies, and software licenses, is crucial for successful adoption but can pose organizational challenges and additional costs.
Overcoming Obstacles and Collaborative Efforts
The agricultural sector is among the least digitalized industries, making digital maturity a prerequisite for adopting digital twins. Overcoming organizational challenges and establishing a digitalization mindset are crucial in this process. Collaborations between academia and industry have shown promising results in helping agricultural companies navigate the digitalization journey.
Conclusion:
As the need for food security and sustainable production becomes increasingly urgent, digital twins offer a transformative solution for agriculture. With the constantly decreasing costs of hardware and computing power, digitally driven smart agriculture is becoming a reality. By leveraging digital twins, controlled environment agriculture can optimize crop growth, reduce energy consumption, and pave the way for a paradigm shift in agriculture towards eradicating global hunger by 2030, as envisioned by the United Nations.
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