Using AI + IoT to improve greenhouse management, monitoring and yields
The rapid growth in demand for newer, non-traditional crops, as well as ongoing demand for fresh fruit and vegetables year-round – no matter the season – has created fresh opportunities for greenhouse farming.
With this opportunity also comes the need for closer scrutiny on delivery, costs and product quality. This is forcing farmers to improve their operational efficiency and overall greenhouse management practices, with AI + IoT solutions the ideal fit to help them to do just that.
Better manage your greenhouses through monitoring to deliver yield optimization.
Farmers need to monitor all of the environmental characteristics of their greenhouses that have an effect on crop yield and timing, and to optimize those factors in order to maximize yield, so it’s critical for the solution to ensure that the right technologies and processes are put in place to capture accurate information in real-time.
Defining what data to collect is critical
In order to create the solution so that the information can be acted upon to deliver the required yield optimization, we started by identifying the key data required. In this solution, this included:
- Room temperature
- CO₂ levels
- Soil temperature and moisture
- Lights status (on/off)
- Nutrient injection volume and timing
- Water flow rates
Initial goals of the solution
The first goal of the AI + IoT solution was to connect with the proprietary greenhouse SCADA so that data would be collected consistently and reliably, ensuring data quality and integrity. This would then provide the following outcomes:
- The ability to monitor real-time data received from the SCADA via a web-based and mobile system
- Ensure device management of the SCADA was set in place
- Define business logic to the application in-order to meet the greenhouse growers business objectives
- Provide alarm and alert notifications via email or SMS messages when there was communication downtime
- Start collecting enough historical data to enable the ability to test different logic to predict yield
- Providing real-time SMS notification when environmental thresholds aren’t not met and there is risk for for reduced yield
- Test the application, making sure all of the above goals are met, based on the below solution architecture
Before setting the solution live, we tested four critical aspects of the solution:
The Rayven AI + IoT platform is built with security as a top priority and our proprietary security architecture ensures that data is secure at all points of the environment.
The solution includes data encryption in transit from device-to-cloud, as well as device authentication; security (Bearer) tokens; SSL, AES and RSA encryption; as well as additional device security checks done via automated polling.
In order to retrieve the data, we integrated MODBUS to the greenhouse advanced control hardware management system, enabling us to retrieve over 100 data points every 30 seconds from the control hardware management system. In addition we connected to additional sensors in the greenhouse which weren’t controlled via the control hardware management system, like door sensors. All of this information is then sent directly to the Rayven cloud IoT platform
Once data started flowing from the control hardware management system and the sensors, the first task was to translate some of the MODBUS tag codes into a readable format, which meant creating custom logic translators to the code. Then, we also created sophisticated case logic in the Rayven codeless work flow to visualize the large variety of translated data and validate it against what was being seen on the local greenhouse system in real-time.
Industrial data science
The objective of exploratory data analysis was to observe trends in the data and provide insights into what environmental factors may effect optimized yield:
- Create an algorithm that defines optimal growth patterns
- Create alerts when specific environmental settings are effecting yield
- Compare greenhouse rooms to identify parameters that may effect yield
- Forecast yield based on current environmental settings
We are continuing to collect and visualize the insights that are coming through and continuing improve our forecasting results. We will soon be expanding the solution to our greenhouses and sites to further compound the yield optimization benefits across the organization.
The data used to deliver the AI + IoT Greenhouse Management, Monitoring & Yield Optimization solution.
New and existing data was used to create the custom applications and business insights for the Rayven AI + IoT Greenhouse Management, Monitoring & Yield Optimization solution.
Key features for our AI + IoT Greenhouse Management, Monitoring & Yield Optimization solution.
All of these features were customized to fit the customers specific business objectives.
Environmental factors such as temperature, relative humidity, and light intensity have a profound effect on the growth of greenhouse crops, for optimal control and growth.
Alerts and Notifications
Environmental control failures can have disastrous effects on crops, particularly if they occur at sensitive stages of crop development. It is therefore critical to receive notifications as soon as they occur in order to successfully take action.
Real Time Insights
Quickly visualize KPIs across all of your greenhouse rooms, greenhouses and locations – wherever they are – in one dashboard.
Build models to forecast yield by combining historical monitoring data with actual crop yields in our machine learning workbench.
Control and monitor events directly – either automatically or manually control in-greenhouse actuators for lighting, CO₂, nutrient and irrigation delivery, etc.
Manage your energy use intelligently throughout the growing cycle to ensure that you maximise energy efficiency.
Driving real business outcomes from AI + IoT.
Being able to better predict your crop yield and overall performance, means you can manage your business with more confidence. Reducing the uncertainty that is always present in farming, allows you to make better decisions with less risk
Lower cost of maintenance
Real time insights, alerts and notifications, together with forecasting, enables you to get a proper snapshot of how your business is performing and where your issues and risk lie, enabling to focus your resources more efficiently where actually needed.
Reduce energy consumption
Energy is a high cost in most operations, and being able to reduce that cost, has a direct impact to the bottom line. Continues optimization of your energy consumption, means you can easily identify energy waste, which was never possible before, and operate with with more confidence.
With better real time visibility and predictability, you reduce the chances of issues not being identified, that may have irrecoverable consequences, like lost of crop.
Real time visibility and predictability combined with smart algorithms and machine learning, and your custom business logic, means you can configure your solution to optimize conditions for maximum yield, and track your performance vs targets
The combination of increased yield, reduced waste and energy consumption, lower cost of maintenance all contribute to your bottom line.
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