Written by: Niko Simos and Edgecom Energy

February 29, 2024

AI-Driven Energy Solutions: An Agricultural Revolution

In recent years, the intersection of agriculture and architecture, commonly known as agritecture, has gained significant attention as a potential solution to the growing challenges of food production. Agritecture embraces diverse elements, encompassing high-tech vertical farms and greenhouses, while fostering a sense of community by including communal gardens. In the face of climate change and the urgent need for sustainable practices, integrating artificial intelligence (AI) into agritecture practices has emerged as a game-changer, particularly in energy management. AI is being used to optimize energy consumption in agricultural operations, reducing costs and environmental impact.

This article delves into the transformative impact of AI on energy usage in greenhouses and vertical farms exploring how it reduces costs and fosters eco-friendly practices.

Demand-Side Management: A Strategic Approach

One of the key contributions of AI in the greenhouses and vertical farms lies in its ability to optimize demand-side management. AI can analyze large amounts of data from various sources to identify energy inefficiencies and suggest improvements. By meticulously analyzing historical consumption patterns and real-time data, AI systems can predict peak and off-peak energy demand periods. This foresight allows for strategically scheduling energy-intensive tasks during off-peak hours, effectively reducing overall energy costs and minimizing the environmental impact of high-demand periods.

Real-time Monitoring and Control: Precision in Action

Take an irrigation system as an example. With an AI monitoring system, farmers can adapt watering schedules based on changes in weather patterns or plant growth stages. If a heatwave suddenly hits, intelligent algorithms can adjust the irrigation system to provide plants with more water. Conversely, if a cold snap is expected, watering can be reduced to prevent overwatering and potential frost damage. 

When it comes to lighting, the applications of AI are equally impressive. Artificial lighting, which is crucial for indoor farming, can consume significant energy. AI can dynamically adapt lighting conditions based on several factors - time of the day, specific crop needs, or even spectral analysis to adjust the color, intensity, and duration of light exposure. Such smart adjustments not only save energy but also enhance plant growth, leading to higher yields and better quality produce. 

Internally linked climate control systems can also benefit tremendously from AI interventions. By analyzing multiple data points like temperature, humidity, and CO2 levels, AI enables a more synchronized operation of heating, cooling, and ventilation systems. This translates to an efficient use of energy while creating the most ideal conditions for crop growth. 

What's more, these AI-powered monitoring systems are increasingly leveraging the power of machine learning. Machine learning, a subset of AI, allows systems to learn from past data and predict future energy needs. For instance, these smart systems can "learn" from previous weather patterns and adjust energy usage preemptively, even before a weather change begins. This predictive capability can be a powerful tool in managing energy needs and costs in the future. 

To sum it up, integrating AI with energy monitoring and control in agriculture facilitates a level of precision and adaptability previously unthinkable. As a result, farmers are able to increase the efficiency of their operations, reduce energy use and improve crop yields, all while supporting a more sustainable future.

Data-Driven Decision-Making: Harnessing Insights for Sustainability

The data analytics capabilities of AI empower greenhouses and vertical farm stakeholders to make informed decisions regarding energy consumption. Farmers and facility managers can identify opportunities for further cost savings, fine-tune energy management strategies, and adapt to changing environmental and market conditions by analyzing historical data, real-time information, and predictive insights. This data-driven decision-making process enhances operational efficiency and contributes to the overall sustainability of agritecture practices.

Energy Harvesting and Storage: Sustainable Power for Agritecture

Renewable energy sources are pivotal in achieving sustainable agritecture. Many farms are now harnessing solar, wind, and bioenergy to power their operations. Solar panels are used to generate electricity for farm buildings and irrigation systems, while wind turbines can provide power for various farm operations. Bioenergy, derived from agricultural waste, is also increasingly being used as a source of heat and power.

AI efficiently harvests and stores energy from renewable sources like batteries, solar panels, and wind turbines. Machine learning algorithms, leveraging historical data, weather forecasts, and crop growth patterns, predict energy demand. This enables the system to store excess energy during periods of low demand and release it during peak times, ensuring a consistent and reliable power supply for greenhouses and vertical farming operations.

Economic and Environmental Benefits: A Win-Win Scenario

Adopting AI in energy management within greenhouses and vertical farms yields economic and environmental benefits. AI can reduce energy consumption in agriculture by up to 15%.  Farmers can significantly reduce operational costs by optimizing energy consumption, making their operations more economically viable. Furthermore, the reduced environmental impact, lower carbon footprint, and sustainable practices associated with AI-driven agritecture contribute to the broader goal of creating resilient and eco-friendly food systems.

IoT Monitoring for Energy Data Insights: Precision through Connectivity

Energy audits are becoming a common practice in the agricultural sector. These audits help farmers identify areas where energy is being wasted and where improvements can be made. They can also provide recommendations for energy-saving equipment and practices, contributing to more efficient and sustainable farming operations.

In greenhouses and vertical farms, the Internet of Things (IoT) has emerged as a powerful tool for real-time monitoring and data collection. IoT devices, equipped with sensors and strategically placed throughout agricultural facilities, capture detailed information on energy consumption, equipment performance, and environmental conditions. This wealth of data unprecedentedly enhances energy management when coupled with AI analytics. From real-time monitoring to optimizing resource allocation, predictive maintenance, and data-driven decision-making, the synergy between AI and IoT transforms greenhouses and vertical farms into a smart and sustainable agricultural paradigm.

Sensors on Electric, Gas, and Water mains and sensors that measure electricity from assets send data to a main LoRa hub. From here, data is transferred to the cloud and displayed on a real-time dashboard. This way, it is possible to attain immediate insights to cut costs, minimize machine downtime, and boost production yield.

A Transformative Approach to Sustainable Agriculture

As the world grapples with the challenges of feeding a growing population while mitigating the impacts of climate change, the integration of AI into greenhouses and vertical farms represents a transformative approach to sustainable agriculture. The synergy between AI technologies and energy management systems in greenhouses and vertical farms reduces energy costs and promotes eco-friendly practices, making agritecture a key player in the global shift towards a more sustainable and resilient future. The continued advancement of AI in greenhouses and vertical farms promises to revolutionize energy management and the entire landscape of greenhouses and vertical farms, paving the way for a more sustainable and efficient future.

About Edgecom Energy

Edgecom Energy, empowers large energy consumers to take control of their energy costs and reduce emissions by harnessing the power of IoT and AI solutions. Their innovative technology helps you optimize energy usage, save money, and contribute to a greener, more sustainable future. Their pioneering AI Energy CoPilot is central to this suite, employing artificial intelligence to furnish real-time insights and tailored recommendations, revolutionizing energy management. Accompanied by dataTrack^TM, a real-time dashboard for monitoring energy, water, and gas usage. Gain immediate insights to cut costs, minimize machine downtime, and boost production yield. Our user-friendly platform presents up-to-the-minute data, empowering you to make informed decisions. It also detects inefficiencies and proactively addresses machinery issues to prevent costly disruptions. dataTrack™ seamlessly integrates into your operations, leveraging our plug-and-play IoT hardware or integrating with existing systems through our open API.